Patterns of sexual exploitation following stranger abduction.


Physical evidence collected from abduction scene.


Exploitation of victim's young age and limited ability to resist or escape.


Use of apartment or residential unit for victim isolation and exploitation.


Use of blunt objects as weapons to threaten and control victim.


Use of specific clothing to alter appearance or blend into environment.


Methods used to enforce victim compliance with perpetrator demands.


Victim compliance due to weapon threats or intimidation.


Exploitation in environment controlled by perpetrator to prevent escape or discovery.


Delayed disclosure due to trauma, threats, or other factors.


Use of disguises or concealment methods to hide identity during approach and abduction.


Disguise items or concealment materials recovered as evidence.


Victim's attempts to escape during or after abduction.


Physical evidence collected from exploitation location.


Concealment of facial features to prevent identification.


Forcing victim to climb fire escapes to enter buildings through windows.


Use of firearm to threaten and control victim during abduction.


Forcing victim to enter buildings, apartments, or other locations for exploitation.


Use of hooded clothing to partially conceal identity.


Exploitation designed to humiliate and degrade victim beyond sexual assault.


Immediate disclosure of abduction and assault upon release or escape.


Sexual exploitation occurring immediately following abduction without delay.


Threats suggesting weapon possession without displaying actual weapon.


Victim's initial attempts to resist abduction or escape.


Targeting children who are alone without adult supervision or companions.


Exploitation of victim being alone without potential helpers or witnesses.


Use of knife or bladed weapon to threaten and control victim.


Exploitation occurring at specific location following victim transportation.


Use of isolated or secluded locations to prevent victim escape or discovery.


Use of masks or face coverings to hide identity.


Physical or psychological restriction of victim movement and escape attempts.


Spontaneous targeting and exploitation of vulnerable children encountered by chance.


Targeting based on immediate opportunity rather than planned surveillance.


Combination of physical force and weapon use to control victim.


Use of physical presence and intimidation to control victim behavior.


Victim's reporting of abduction and exploitation to authorities or family.


Abduction occurring in public spaces such as parks, playgrounds, or commercial areas.


Selection of victim based on opportunity rather than specific targeting or grooming.


Exploitation following specific ritualized patterns (forced showering, specific commands).


Targeting children during predictable routine activities (school, recreation, errands).


Abduction of child while traveling to or from school or educational activities.


Targeting children on routes to or from school when they are alone and vulnerable.


Movement of victim to secondary location for enhanced control and exploitation.


Specific threats or actions to prevent victim from calling for help.


Exploitation of victim's small physical size relative to perpetrator.


Use of ski mask or balaclava to conceal identity during approach.


Abduction of child by unknown perpetrator without prior relationship or contact.


Specialized investigation of stranger abduction and sexual exploitation cases.


Abduction occurring on public streets or sidewalks during victim's routine activities.


Video or photographic surveillance evidence of abduction or related activity.


Victim behavior focused on survival and minimizing harm.


Use of threats to maintain victim compliance and prevent resistance.


Use of non-standard entry methods to avoid detection or surveillance.


Use of vehicles to conceal approach or provide mobile concealment.


Use of verbal threats to maintain victim compliance.


Victim's response to stranger abduction and exploitation attempts.


Methods used to maintain control over victim during abduction and exploitation.


Patterns of victim selection and targeting in stranger abduction cases.


Exploitation of specific victim vulnerabilities during stranger abduction.


Use of weapons to threaten, intimidate, and control victims during abduction and exploitation.


Display of weapon to intimidate victim into compliance without direct threats.


Weapons used in abduction and coercion recovered as evidence.


Forcing victim to enter location through windows rather than doors.


Witness testimony regarding abduction or suspicious activity.


Duration of abduction from initial contact to victim release in hours.


Specific location where abduction occurred.


Difficulty of accessing exploitation location (easy, moderate, difficult).


Method used to approach victim (direct_confrontation, deception, force).


Primary reason for victim compliance (fear, weapon_threat, physical_force).


Level of identity concealment (partial, full, complete).


Links perpetrator to disguise items used for concealment.


Links disclosure to person or agency receiving disclosure.


Method of disclosure (family, police, school, medical).


Effectiveness of disguise in preventing identification.


Type of disguise used (ski_mask, hood, mask, clothing, vehicle).


Links evidence to abduction it documents.


Links abduction to coercion methods employed.


Method used to enter exploitation location (fire_escape, window, door, roof).


Links abduction to exploitation pattern that follows.


Number and accessibility of potential escape routes from location.


Percentage of expected evidence successfully recovered.


Links perpetrator to control mechanisms they employ.


Links victim to vulnerability they exhibit.


Links abduction to victim vulnerability being exploited.


Links abduction methods to exploitation they facilitate.


Links abduction to forced entry into exploitation location.


Links investigation to abduction being investigated.


Duration of investigation from report to resolution in days.


Links abduction to location used for victim isolation.


Level of isolation of exploitation location (high, moderate, low).


Links abduction to location where it occurs.


Duration of opportunity window for abduction in minutes.


Links perpetrator to stranger abduction they commit.


Links evidence to location where it was recovered.


Time delay between incident and reporting in hours.


Links victim to abduction reporting they make.


Level of victim resistance (none, minimal, moderate, strong).


Links victim to resistance efforts against abduction.


Links victim response to abduction they are responding to.


Links abduction evidence to criminal charges it supports.


Duration of pre-abduction surveillance if any, in days.


Criteria used for victim selection (age, size, isolation, opportunity).


Links targeting pattern to victim being targeted.


Effectiveness of threats in controlling victim behavior.


Specificity of threats made (vague, specific, detailed, graphic).


Links perpetrator to weapon used for threats.


Time of day when abduction occurred (morning, afternoon, evening, night).


Links abduction location to exploitation location.


Links victim reporting to investigation it triggers.


Links abduction to disguise methods used.


Links abduction to weapon used for coercion.


Activity victim was engaged in when abducted (walking_to_school, playing, shopping).


Links victim to stranger abduction they experience.


Whether weapon was visibly displayed to victim.


Type of weapon used for coercion (knife, firearm, blunt_object, implied).


Number of witnesses identified during investigation.


Existing CSAM that has been modified using AI techniques to alter appearance, age, or other characteristics. Enhanced as gUFO Object with alteration tracking.


Investigation specifically focused on AI-generated child sexual abuse material, requiring specialized techniques and legal frameworks. Enhanced as gUFO Event for complex investigation modeling.


Enhanced validation shape for AI-CSAM investigation instances with comprehensive gUFO Event and Situation validation.


Process of identifying AI-generated or AI-altered content to distinguish from authentic material during investigations. Enhanced as gUFO Event for forensic process modeling.


Enhanced validation shape for AI content detection instances with comprehensive gUFO Event validation.


Process of creating artificial CSAM using machine learning models, neural networks, or other AI technologies. Enhanced as gUFO Event for precise temporal and causal modeling.


Enhanced validation shape for AI content generation instances with comprehensive gUFO Event validation.


Complex situation involving multiple stakeholders, technologies, and legal frameworks for investigating AI-generated CSAM.


AI Content Investigation Situation Shape

SHACL shape for AI content investigation situations with comprehensive gUFO Situation validation.


Anti-rigid phase during which AI-generated content undergoes detection and analysis processes.


SHACL shape for AI detection phases with anti-rigid gUFO Phase validation.


Software tool specialized for detecting AI-generated content in digital media. Enhanced as gUFO Object for tool modeling.


Enhanced validation shape for AI detection tool instances with gUFO Object validation.


Anti-rigid role of specialist analyzing AI-generated content for authenticity and generation methods.


SHACL shape for AI forensic analyst roles with anti-rigid gUFO Role validation.


Child sexual abuse material fully generated by artificial intelligence without depicting real victims, but still contributing to objectification and sexualization of children. Enhanced as gUFO Object for precise foundational modeling.


Enhanced validation shape for AI-generated CSAM instances with comprehensive gUFO Object validation.


Enhanced validation that AI-generated content has associated gUFO Event generation processes.


Anti-rigid role of specialist identifying and analyzing AI models used for content generation.


AI technique for artificially aging or de-aging subjects in content, potentially creating illegal material from legal content. Enhanced as gUFO Event.


Validation of anti-rigidity constraints for gUFO Phases in AI-CSAM contexts.


Analysis of digital artifacts and inconsistencies that may indicate AI generation, such as compression patterns or noise characteristics. Enhanced as gUFO Event.


Analysis of biometric inconsistencies in AI-generated content, such as unnatural eye movements or facial feature distortions. Enhanced as gUFO Event.


Anti-rigid phase during which AI systems generate illegal content.


SHACL shape for content generation phases with anti-rigid gUFO Phase validation.


Situation involving detection and analysis of AI-generated content across multiple platforms and technologies.


CSAM created by using AI to alter genuine content, potentially making real victims appear in fabricated scenarios or altering existing abuse material. Enhanced as gUFO Object with manipulation tracking.


Enhanced validation shape for deepfake CSAM instances with gUFO Object validation and manipulation tracking.


Specialized analysis for detecting deepfake technology use in content, including face replacement and manipulation. Enhanced as gUFO Event.


Anti-rigid role of specialist focused on detecting and analyzing deepfake technology use.


Tool specifically designed to identify deepfake content and face manipulation techniques. Enhanced as gUFO Object.


Enhanced validation that detection gUFO Events occur after content generation gUFO Events.


Enhanced validation that AI detection processes use appropriate gUFO Object tools.


AI technique for replacing faces in existing content with different faces, potentially placing victims in abusive scenarios. Enhanced as gUFO Event.


Anti-rigid phase during which AI-generated content undergoes detailed forensic examination.


Validation of forensic integrity for AI content detection processes.


Enhanced data quality validation for AI-related gUFO entities with foundational ontology compliance.


Enhanced temporal consistency validation for AI-related gUFO Events using gUFO temporal framework.


Investigation process to identify the source, tools, and methods used to generate AI-CSAM. Enhanced as gUFO Event.


Content combining real and AI-generated elements, making it difficult to distinguish between authentic and artificial material. Enhanced as gUFO Object with composition modeling.


Enhanced validation shape for hybrid CSAM instances with gUFO Object composition validation.


Generation of static images using AI models such as diffusion models, GANs, or other generative techniques. Enhanced as gUFO Event.


Tool for analyzing metadata patterns that may indicate AI generation or manipulation. Enhanced as gUFO Object.


Process of identifying the specific AI model or algorithm used to generate illegal content. Enhanced as gUFO Event.


Process of training AI models on datasets that may include illegal content for the purpose of generating new CSAM. Enhanced as gUFO Event with training phases.


Enhanced validation shape for model training instances with gUFO Event validation and training phases.


AI content generation/manipulation process that produces synthetic nudity (e.g., 'nudifying apps' / nudifying functionalities) from existing media. Modeled as a gUFO Event and UCO Action.


Validation shape for nudification actions producing synthetic nudity, consistent with AI generation process modeling.


Software tool or functionality capable of performing AI-enabled nudification (synthetic nudity) of existing media.


Validation shape for tools capable of AI-enabled nudification (synthetic nudity).


Child sexual abuse material created by AI-enabled nudification (synthetic nudity) of an existing image or video. This models 'nudifying functionalities' discussed in policy contexts.


Validation shape for nudified CSAM outputs.


Tool for detecting synthetically generated images using machine learning classifiers. Enhanced as gUFO Object.


Forensic analysis of media to determine if it was artificially generated and identify generation techniques used. Enhanced as gUFO Event.


Enhanced validation shape for synthetic media analysis instances with gUFO Event and specialist role validation.


Completely synthetic media generated using AI models trained on large datasets, creating realistic but artificial depictions. Enhanced as gUFO Object for synthetic media modeling.


Enhanced validation shape for synthetic media CSAM instances with gUFO Object validation.


Anti-rigid role of expert examining synthetic media for forensic artifacts and generation signatures.


SHACL shape for synthetic media examiner roles with specialized gUFO Role validation.


Situation requiring coordination between technical experts, forensic analysts, and legal teams for AI content analysis.


SHACL shape for technical analysis situations with coordination validation.


Analysis of datasets potentially used to train AI models for generating illegal content. Enhanced as gUFO Event.


Generation of video content using AI models capable of creating temporal sequences and motion. Enhanced as gUFO Event.


Type of AI model used for generation (e.g., 'Stable Diffusion', 'GAN', 'VAE', 'Transformer').


Links investigation to training data analysis performed.


Specific artifacts indicating AI generation (compression_anomalies, facial_inconsistencies, lighting_errors).


Degree of artificial generation (fully_synthetic, partially_altered, minimally_modified).


Links generation process to the AI model used.


Links AI-CSAM to legal framework challenges it creates.


Links AI-generated content to victim identification processes it affects.


Links AI-generated content to detection analysis performed.


Confidence level of AI detection analysis (0.0-1.0).


Method used for AI detection (neural_network, statistical_analysis, artifact_detection, metadata_analysis).


Admissibility of AI-detection evidence in court (accepted, challenged, rejected, unclear).


Rate of false positives in AI detection (0.0-1.0).


Links AI-generated content to the generation process used.


Technical sophistication level (basic, intermediate, advanced, expert).


Specific technique used for content generation (e.g., 'text-to-image', 'image-to-image', 'style transfer').


Difficulty level of investigating AI-CSAM (low, moderate, high, extreme).


Challenges in existing legal frameworks for AI-generated content (legislation_gaps, jurisdiction_issues, evidence_admissibility).


Technique used for nudification (synthetic nudity) generation (e.g., 'nudify', 'clothing_removal', 'synthetic_nudity').


Links nudified content to its source media from which synthetic nudity was generated.


Time required for AI detection analysis in seconds.


Difficulty in prosecuting AI-CSAM cases (low, moderate, high, extreme).


Whether content depicts or is based on a real victim.


Quality of AI-generated output (low, medium, high, photorealistic).


Links AI-CSAM investigation to specialized prosecution approaches needed.


Links detection analysis to artifacts discovered.


Degree to which generation source can be traced (untraceable, limited, moderate, high).


Links AI-generated content to investigations examining it.


Level of technical expertise needed to generate content (basic, intermediate, advanced, expert).


Links source tracking to identified origin or creator.


Links detection process to tools used for analysis.


Links a nudification process to the nudification tool/functionality used.


Links generation process to tools used for creation.


Difficulty in identifying real victims when AI content is involved (none, low, moderate, high, impossible).


A measure, control, or workflow technique used to reduce human exposure to traumatic content while enabling effective review and classification (e.g., blur/previews, hash-only review, progressive reveal).


Validates exposure mitigation measures with a controlled mitigationType vocabulary.


Manual Classification Exposure Mitigation Shape

Ensures that any exposure mitigation referenced from manual classification actions is properly typed.


Occupational harm experienced by investigators or content analysts arising from exposure to traumatic materials or sustained operational stressors.


Validates occupational harm situations with optional harmSeverity.


Ensures that any occupational harm referenced from persons is properly typed.


Occupational stress reactions arising from indirect exposure to others' trauma, including exposure through content review and investigative materials.


A form of occupational harm in which repeated exposure to traumatic material produces trauma-like impacts in the reviewer.


Links a person (analyst/investigator) to an occupational harm situation they experience.


Severity of occupational harm (low, medium, high) when captured.


Type/category of exposure mitigation measure (e.g., hash_only_review, blurred_preview, progressive_reveal, frame_sampling).


Links a manual classification/review action to an exposure mitigation measure used to minimize traumatic exposure.


Validation of anti-rigidity constraints for gUFO Phases in asset forfeiture contexts.


Action to assess the value and ownership of assets for potential forfeiture. Enhanced as gUFO Event with assessment phases.


Legal action to forfeit assets derived from or used in child exploitation crimes. Enhanced as gUFO Event for comprehensive temporal and causal modeling of forfeiture proceedings.


Enhanced validation shape for asset forfeiture actions with comprehensive gUFO Event validation.


Officer specializing in asset identification and forfeiture proceedings. Enhanced as anti-rigid gUFO Role supporting dynamic assignment.


SHACL shape for asset forfeiture officer roles with anti-rigid gUFO Role validation.


Phase during which assets are identified and assessed for potential forfeiture. Anti-rigid gUFO Phase supporting dynamic operational transitions.


SHACL shape for asset identification phases with anti-rigid gUFO Phase validation.


Enhanced validation that asset forfeiture actions target appropriate gUFO Object assets.


Expert responsible for determining market value of assets for forfeiture proceedings. Enhanced as anti-rigid gUFO Role.


SHACL shape for asset valuation expert roles with specialized gUFO Role validation.


Investigation conducted by Criminal Assets Confiscation Taskforce targeting assets of child exploitation offenders. Enhanced as gUFO Event.


Enhanced validation shape for CACT investigations with gUFO Event validation and investigation phases.


Complete forfeiture of property to the Commonwealth or state. Enhanced as gUFO Object.


Enhanced validation shape for complete forfeiture with gUFO Object validation.


Court order agreed to by parties for financial penalty payment. Enhanced as gUFO Object.


Specialized taskforce responsible for asset restraint and forfeiture in child exploitation cases. Enhanced as gUFO Organization with structured operational frameworks.


Criminal Assets Confiscation Taskforce Shape

Enhanced validation shape for CACT with gUFO Organization validation and operational framework validation.


Seizure of equipment used in commission of child exploitation offenses. Enhanced as gUFO Event for seizure operations.


Bank account or financial instrument subject to restraint or forfeiture. Enhanced as gUFO Object for financial asset modeling.


Enhanced validation shape for financial accounts with gUFO Object validation and financial verification.


Court-ordered financial penalty equal to benefits derived from child exploitation offenses. Enhanced as gUFO Event for penalty proceedings.


Enhanced validation shape for financial penalty actions with gUFO Event penalty modeling.


Specialist in tracing financial assets and determining proceeds of crime. Enhanced as anti-rigid gUFO Role.


SHACL shape for forensic accountant roles with specialized gUFO Role validation.


Result of asset forfeiture proceedings. Enhanced as gUFO Object for outcome modeling.


Enhanced data quality validation for asset forfeiture gUFO entities with foundational ontology compliance.


Enhanced temporal consistency validation for asset forfeiture gUFO Events using gUFO temporal framework.


High-value household items including electronics, furniture, and appliances subject to forfeiture. Enhanced as gUFO Object for personal property modeling.


Assets used as instruments in the commission of child exploitation offenses. Enhanced as gUFO Object.


Complex coordination situation involving multiple legal jurisdictions for asset forfeiture operations. gUFO Situation for inter-jurisdictional modeling.


SHACL shape for jurisdictional coordination situations with comprehensive gUFO Situation validation.


Legal justification and framework for asset forfeiture action. Enhanced as gUFO Object for legal framework modeling.


Legal counsel specialized in asset forfeiture law and proceedings. Enhanced as anti-rigid gUFO Role.


Validation of legal integrity for asset forfeiture proceedings.


Phase during which formal forfeiture proceedings occur in court. Anti-rigid gUFO Phase.


SHACL shape for legal proceedings phases with anti-rigid gUFO Phase validation.


Complex situation involving courts, legal counsel, and multiple parties in forfeiture proceedings. gUFO Situation for legal process coordination.


SHACL shape for legal proceedings situations with multi-party validation.


Asset forfeiture operation spanning multiple Australian states and territories. Enhanced as gUFO Situation for complex multi-jurisdictional coordination.


Enhanced validation shape for multi-state forfeiture with gUFO Situation validation and jurisdictional coordination.


Assets of offenders who were not accused of profiting from their crimes, representing first-of-kind forfeiture precedent. Enhanced as gUFO Object.


Forfeiture of a percentage of property value (e.g., 50% of market value). Enhanced as gUFO Object.


Enhanced validation shape for partial forfeiture with gUFO Object validation and percentage constraints.


Enhanced validation that asset forfeiture gUFO Events follow logical phase sequences.


Validation of precedent-setting asset forfeiture cases.


Assets that are proceeds or benefits derived from child exploitation offenses. Enhanced as gUFO Object.


Legal action resulting in permanent forfeiture of property to the Commonwealth or state. Enhanced as gUFO Event with completion modeling.


Enhanced validation shape for property forfeiture actions with gUFO Event completion validation.


Specialist responsible for managing restrained and forfeited property. Enhanced as anti-rigid gUFO Role.


Legal action to restrain property pending forfeiture proceedings, preventing disposal or transfer. Enhanced as gUFO Event with restraint temporal modeling.


Enhanced validation shape for property restraint actions with gUFO Event validation and restraint temporal modeling.


Phase during which forfeited assets are recovered and transferred to appropriate authorities. Anti-rigid gUFO Phase.


SHACL shape for recovery phases with anti-rigid gUFO Phase validation.


Residential home subject to restraint or forfeiture in child exploitation cases. Enhanced as gUFO Object for comprehensive property modeling.


Enhanced validation shape for residential property with gUFO Object validation and property assessment.


Phase during which property is restrained pending forfeiture proceedings. Anti-rigid gUFO Phase.


SHACL shape for restraint phases with anti-rigid gUFO Phase validation.


State Supreme Court with jurisdiction over forfeiture proceedings. Enhanced as gUFO Organization for judicial institution modeling.


Taskforce Involvement Cross Reference Shape

Enhanced validation that asset forfeiture actions involve appropriate gUFO Organization taskforces.


Technical equipment used in child exploitation offenses (cameras, computers, drones, etc.). Enhanced as gUFO Object for equipment modeling.


Enhanced validation shape for technical equipment with gUFO Object validation and forensic verification.


Vehicle used in or purchased with proceeds from child exploitation offenses. Enhanced as gUFO Object for vehicle asset modeling.


Amount of funds in financial accounts subject to forfeiture. Enhanced with gUFO Object financial quantification.


Links a person to their assigned forfeiture role. gUFO Role modeling for dynamic assignment.


Court jurisdiction for forfeiture proceedings (e.g., 'NSW', 'VIC', 'SA'). Enhanced with gUFO Situation context.


Links asset forfeiture action to its current operational phase. gUFO Phase modeling for operational state management.


Type of technical equipment (e.g., 'camera equipment', 'drone', 'scuba diving gear'). Enhanced with gUFO Object classification.


Estimated total value of restrained assets (e.g., $30,000). Enhanced with gUFO Object aggregation.


Amount of financial penalty equal to benefits derived from offenses. Enhanced with gUFO Event outcome modeling.


Date when property was forfeited to the Commonwealth. Superseded by gUFO temporal framework.


Percentage of property value subject to forfeiture (e.g., 50%). Enhanced with gUFO outcome quantification.


Links asset forfeiture action to phase transition events.


Links forfeiture action to coordination situations involving multiple jurisdictions.


Links forfeiture action to the CACT or other taskforce involved. Enhanced with gUFO Organization participation.


Number of household items forfeited (e.g., 48 household items). Enhanced with gUFO Object quantification.


Market value of property subject to forfeiture (e.g., $850,000). Enhanced with gUFO Object value modeling.


Links an entity to a role it plays in forfeiture operations.


Indicates whether this forfeiture set a legal precedent (e.g., first restraint of non-profit offender home). Enhanced with gUFO precedential significance.


Criminal charges related to the asset forfeiture action. Enhanced with gUFO Event relationships.


Date when property restraint order was issued. Superseded by gUFO temporal framework.


Asset that is the target of forfeiture action. Enhanced with gUFO Object targeting.


Exploitation focused on body parts and anatomy under guise of athletic training. Enhanced as gUFO Event.


Validation of anti-rigidity constraints for gUFO Phases in athletic exploitation contexts.


Assistant coaching role with delegated authority over specific training aspects. Enhanced as anti-rigid gUFO Role.


Athletic coaching role with authority over team members and training activities. Enhanced as anti-rigid gUFO Role.


Enhanced validation shape for athletic coach roles with anti-rigid gUFO Role validation.


Child sexual exploitation committed by athletic coaches using sports authority, team dynamics, and physical training as coercion mechanisms. Enhanced as gUFO Event for comprehensive temporal and causal modeling of exploitation patterns.


Enhanced validation shape for athletic coaching exploitation with comprehensive gUFO Event validation.


Escalation of physical contact within legitimate athletic training context. Enhanced as gUFO Event.


Athletic Exploitation Cross Reference Shape

Enhanced validation that athletic coaching exploitation involves appropriate gUFO foundational entities.


Discovery of athletic coaching exploitation through various reporting mechanisms. Enhanced as gUFO Event.


Enhanced validation shape for athletic exploitation discovery with gUFO Event validation.


Physical athletic facilities and sports venues where exploitation occurs. Enhanced as gUFO Object.


Exploitation occurring in athletic facilities and sports venues. Enhanced as gUFO Event occurring in gUFO Objects.


Enhanced validation shape for athletic facility exploitation with gUFO Event validation and facility Object modeling.


Enhanced validation shape for athletic facilities with gUFO Object validation.


Exploitation on outdoor athletic fields, courts, and sports venues. Enhanced as gUFO Event.


Threats to athletic opportunities, advancement, and sports career prospects. Enhanced as gUFO Situation.


Phase during which coaching authority and control over athletes is established. Anti-rigid gUFO Phase.


SHACL shape for authority establishment phases with anti-rigid gUFO Phase validation.


Validation of coaching integrity for athletic exploitation cases.


Reporting through community and parent networks rather than direct victim disclosure. Enhanced as gUFO Event.


Use of physical conditioning exercises as coercion mechanism for sexual compliance. Enhanced as gUFO Event.


Enhanced validation shape for conditioning coercion with gUFO Event validation.


Phase during which exploitation is discovered through various reporting mechanisms. Anti-rigid gUFO Phase.


SHACL shape for discovery phases with anti-rigid gUFO Phase validation.


Exploitation leveraging multiple coaching positions across different teams or institutions. Enhanced as gUFO Event.


Enhanced validation shape for dual coaching role exploitation with gUFO Role multiplicity validation.


Exercise continuation contingent on sexual compliance and exposure demands. Enhanced as gUFO Event.


Physical exhaustion to reduce resistance and force compliance with sexual demands. Enhanced as gUFO Event.


Enhanced validation shape for exhaustion-based coercion with gUFO Event validation.


Active exploitation phase using established authority and coercion mechanisms. Anti-rigid gUFO Phase.


SHACL shape for exploitation phases with anti-rigid gUFO Phase validation.


Enhanced data quality validation for athletic exploitation gUFO entities with foundational ontology compliance.


Enhanced temporal consistency validation for athletic exploitation gUFO Events using gUFO temporal framework.


Initial phase where coach establishes trust and authority before exploitation. Anti-rigid gUFO Phase supporting dynamic operational transitions.


SHACL shape for grooming phases with anti-rigid gUFO Phase validation.


Exploitation using team group dynamics, peer pressure, and collective authority. Enhanced as gUFO Situation.


Exploitation in gymnasium and indoor athletic facilities. Enhanced as gUFO Event.


Head coaching role with primary authority over team and training decisions. Enhanced as anti-rigid gUFO Role.


Enhanced validation shape for head coach roles with leadership gUFO Role validation.


Use of sexual topics and education as exploitation method disguised as coaching. Enhanced as gUFO Event.


Employment termination following discovery of athletic coaching exploitation. Enhanced as gUFO Event.


Institutional Oversight Validation Shape

Validation of institutional oversight for school-based athletic exploitation.


Exploitation of legitimate athletic physical contact for sexual purposes. Enhanced as gUFO Event.


Exploitation in locker rooms and changing areas with privacy expectations. Enhanced as gUFO Event.


Exploitation through extensive masturbation discussions during athletic training. Enhanced as gUFO Event.


Athletic equipment, benefits, or opportunities offered as coercion for sexual compliance. Enhanced as gUFO Situation.


Enhanced validation shape for material benefit coercion with gUFO Situation validation.


Over Clothing to Under Clothing Escalation

Progression from over-clothing to under-clothing contact during athletic activities. Enhanced as gUFO Event.


Discovery through parent community networks and team family communications. Enhanced as gUFO Event.


Enhanced validation shape for parent network discovery with gUFO Event validation.


Enhanced validation that athletic exploitation gUFO Events follow logical phase sequences.


Phase involving physical training coercion and conditioning for compliance. Anti-rigid gUFO Phase.


SHACL shape for physical coercion phases with anti-rigid gUFO Phase validation.


Escalation of physical contact within athletic training context. Enhanced as gUFO Event.


Exploitation of physical endurance requirements and athletic performance demands. Enhanced as gUFO Event.


Use of physical training, conditioning, and exercise as coercion mechanism for sexual exploitation. Enhanced as gUFO Event.


Enhanced validation shape for physical training coercion with comprehensive gUFO Event validation.


Exploitation during regular practice sessions and training activities. Enhanced as gUFO Event.


Specific exploitation focused on pubic hair viewing and discussion. Enhanced as gUFO Event.


Discovery through rumor circulation among families and team communities. Enhanced as gUFO Event.


Enhanced validation shape for rumor circulation discovery with gUFO Event validation.


Coaching role within school-based athletic programs with institutional authority. Enhanced as anti-rigid gUFO Role.


Exploitation within school-based athletic programs leveraging institutional authority. Enhanced as gUFO Event.


Investigation initiated by educational institution following exploitation reports. Enhanced as gUFO Event.


Use of sexual topics and education as exploitation method within athletic context. Enhanced as gUFO Event.


Grooming through inappropriate sexual discussions during athletic activities. Enhanced as gUFO Event.


Physical abuse within sports training context disguised as coaching. Enhanced as gUFO Event.


Exploitation using team dynamics, group pressure, and collective team authority. Enhanced as gUFO Situation for complex team coordination.


Enhanced validation shape for team-based exploitation with comprehensive gUFO Situation validation.


Exploitation using team membership, group dynamics, and athletic authority structures. Enhanced as gUFO Situation.


Enhanced validation that team-based exploitation involves appropriate gUFO Situation coordination.


Threats to team membership and participation as coercion for sexual compliance. Enhanced as gUFO Situation.


Enhanced validation shape for team membership coercion with gUFO Situation validation.


Use of team selection and roster decisions for sexual coercion and compliance. Enhanced as gUFO Situation.


Inappropriate touching disguised as athletic training and coaching instruction. Enhanced as gUFO Event.


Exploitation during intensive training camps or extended athletic sessions. Enhanced as gUFO Event.


Use of training drills and exercises for exploitation demands and sexual compliance. Enhanced as gUFO Event.


Coaching role for travel or club sports teams with enhanced authority and access. Enhanced as anti-rigid gUFO Role.


Enhanced validation shape for travel team coach roles with specialized gUFO Role validation.


Exploitation within travel or club sports teams where coach has enhanced authority and access to players. Enhanced as gUFO Event.


Enhanced validation shape for travel team exploitation with gUFO Event validation and enhanced authority modeling.


Links coach to team they coach. Enhanced with gUFO Role-Organization relationships.


Years of coaching experience. Enhanced with gUFO Role temporal modeling.


Links athletic exploitation to its current operational phase. gUFO Phase modeling for exploitation state management.


Links athletic exploitation to phase transition events.


Links person to coaching role they hold. Enhanced with gUFO Role assignment.


Number of coaching roles held simultaneously. Enhanced with gUFO Role multiplicity.


Links exploitation to athletic facility where it occurs. Enhanced with gUFO Object location.


Links entities to team dynamics situations they participate in.


Links player to team they participate in. Enhanced with gUFO participation modeling.


Frequency of practice sessions per week. Enhanced with gUFO Event frequency modeling.


Type of sport (baseball, basketball, soccer, football, tennis, etc.). Enhanced with gUFO Object classification.


Type of team (travel, school, club, recreational, competitive). Enhanced with gUFO Organization classification.


Links facility exploitation to specific athletic space used. Enhanced with gUFO Object utilization.


Phase during which active investigation activities occur including evidence collection and analysis. Anti-rigid gUFO Phase.


SHACL shape for active investigation phases with anti-rigid gUFO Phase validation.


Administrative review of case management, resource allocation, and procedural compliance. Enhanced as gUFO Event.


Assignment of analysts for data analysis, intelligence gathering, and technical support. Enhanced as gUFO Event linking to anti-rigid gUFO Role.


Validation of anti-rigidity constraints for gUFO Phases in case management contexts.


Legal documentation for arrest warrants including applications, approvals, and execution records. Enhanced as gUFO Object.


Role responsible for case analysis, intelligence gathering, and data processing. Enhanced as anti-rigid gUFO Role.


Assignment of personnel and resources to specific cases with defined roles and responsibilities. Enhanced as gUFO Event linking to gUFO Roles.


Enhanced validation shape for case assignment with comprehensive gUFO Event validation and Role relationships.


Formal case closure process including disposition, appeals status, and archival procedures. Enhanced as gUFO Event for closure processes.


Comprehensive documentation management for case files, reports, evidence logs, and legal documents. Enhanced as gUFO Object for document management.


Enhanced validation shape for case documentation with gUFO Object validation.


Metrics tracking case duration from opening to closure across different stages. Enhanced as gUFO Object.


Initial phase where case is opened and basic assignment occurs. Anti-rigid gUFO Phase supporting dynamic operational transitions.


SHACL shape for case initiation phases with anti-rigid gUFO Phase validation.


Comprehensive management framework for ICAC cases including status tracking, priority assignment, and resource allocation. Enhanced as gUFO Object for comprehensive structural modeling and property management.


Enhanced validation that case management involves appropriate gUFO foundational entities.


Enhanced validation shape for case management with comprehensive gUFO Object validation.


Role responsible for overall case management coordination and oversight. Enhanced as anti-rigid gUFO Role.


Enhanced validation shape for case manager roles with anti-rigid gUFO Role validation.


Performance metrics and analytics for case management including duration, resolution rates, and resource utilization. Enhanced as gUFO Object for metric management.


Role responsible for legal review, charging decisions, and prosecution activities. Enhanced as anti-rigid gUFO Role.


Formal case report documenting investigation findings, evidence, and recommendations. Enhanced as gUFO Object.


Formal review processes for case quality assurance, supervisory oversight, and legal compliance. Enhanced as gUFO Event for review processes.


Enhanced validation shape for case review with gUFO Event validation.


Systematic tracking of case progress, updates, and status changes across multiple systems and jurisdictions. Enhanced as gUFO Object for systematic monitoring.


Structured workflow stages and processes for managing case progression from intake to disposition. Enhanced as gUFO Event for comprehensive temporal and causal modeling.


Enhanced validation shape for case workflow with comprehensive gUFO Event validation.


Management protocols for cold cases including periodic review and new evidence integration. Enhanced as gUFO Situation for cold case coordination.


Specialized management for complex cases involving multiple offenses, victims, or extensive evidence. Enhanced as gUFO Situation for complexity coordination.


Financial metrics tracking costs associated with case investigation and prosecution. Enhanced as gUFO Object.


Legal documents filed with courts including motions, briefs, and procedural filings. Enhanced as gUFO Object.


Phase during which court proceedings occur including trials and hearings. Anti-rigid gUFO Phase.


Final phase involving case disposition, sentencing, and closure activities. Anti-rigid gUFO Phase.


Final case disposition workflow including sentencing, appeals, and case closure procedures. Enhanced as gUFO Event.


Comprehensive log of all evidence collected, analyzed, and maintained for the case. Enhanced as gUFO Object.


Expert analysis reports including forensic findings, psychological evaluations, and technical assessments. Enhanced as gUFO Object.


External review by independent parties for oversight, audit, or specialized expertise. Enhanced as gUFO Event.


Enhanced data quality validation for case management gUFO entities with foundational ontology compliance.


Enhanced temporal consistency validation for case management gUFO Events using gUFO temporal framework.


Enhanced management protocols for critical and high-priority cases requiring expedited processing. Enhanced as gUFO Situation for priority coordination.


Initial case intake and assessment workflow including triage and preliminary evaluation. Enhanced as gUFO Event.


Enhanced validation shape for intake workflow with gUFO Event validation and specialized temporal modeling.


Documentation of interviews conducted with victims, witnesses, and suspects. Enhanced as gUFO Object.


Active investigation workflow including evidence collection, analysis, and suspect identification. Enhanced as gUFO Event.


Specific assignment of investigators to cases with experience levels, caseload management, and specialization tracking. Enhanced as gUFO Event with Role relationships.


Primary investigator role with leadership responsibilities for case investigation. Enhanced as anti-rigid gUFO Role.


Legal review of case materials, procedures, and prosecution readiness. Enhanced as gUFO Event.


Specialized management for cases spanning multiple jurisdictions with coordination requirements. Enhanced as gUFO Situation for complex coordination.


Multi Jurisdictional Case Management Shape

Enhanced validation shape for multi-jurisdictional case management with gUFO Situation validation.


Peer review process for case methodology, analysis, and conclusions. Enhanced as gUFO Event.


Lead investigator assignment with primary responsibility for case management and coordination. Enhanced as gUFO Event linking to anti-rigid gUFO Role.


Phase involving preparation for prosecution including legal review and case building. Anti-rigid gUFO Phase.


Prosecution preparation and court proceedings workflow including case presentation and trial management. Enhanced as gUFO Event.


Assignment of prosecutors for legal review, charging decisions, and court representation. Enhanced as gUFO Event linking to anti-rigid gUFO Role.


Systematic quality assurance review ensuring compliance with standards and procedures. Enhanced as gUFO Event.


Quality assessment metrics evaluating case management effectiveness and outcomes. Enhanced as gUFO Object.


Metrics tracking case resolution rates including conviction and closure statistics. Enhanced as gUFO Object.


Metrics tracking resource allocation and utilization efficiency across cases. Enhanced as gUFO Object.


Legal documentation for search warrants including applications, approvals, and execution records. Enhanced as gUFO Object.


Supporting investigator assignment providing specialized skills or additional resources. Enhanced as gUFO Event linking to anti-rigid gUFO Role.


Supervisory assignment for case oversight, quality assurance, and administrative guidance. Enhanced as gUFO Event linking to anti-rigid gUFO Role.


Formal supervisory review of case progress, decisions, and quality standards. Enhanced as gUFO Event.


Validation of workflow integrity for case management.


Access level for case information (public, restricted, confidential, classified, need_to_know, compartmented).


Status of any appeals (no_appeal, appeal_pending, appeal_denied, appeal_granted, remanded, overturned).


Links documentation to approving authority.


Date when case materials were archived.


Links case closure to archival location.


Links assignment to assigning authority.


Name or identifier of the assigned investigator.


Links assignment to assigned personnel.


Links case assignment to specific role being assigned.


Date when the assignment was made.


Status of the assignment (active, inactive, transferred, completed, suspended, terminated).


Type of assignment (primary_investigator, secondary_investigator, lead_detective, analyst, supervisor, prosecutor).


Benchmark or target value for the metric.


Links metrics to benchmark standards.


Date when the case was officially closed.


Date when the case was officially opened.


Priority level of the case (critical, high, medium, low, routine, administrative). Enhanced with gUFO Situation priority modeling.


Current status of the case (open, active, pending, suspended, closed, archived, transferred, merged). Enhanced with gUFO Object state modeling.


Type of case (possession, distribution, production, trafficking, exploitation, grooming, sextortion, multi_offense).


Number of active cases assigned to the investigator.


Certification level of the investigator (basic, intermediate, advanced, expert, specialized, master).


Security classification level (unclassified, law_enforcement_sensitive, confidential, restricted, classified, top_secret).


Links case closure to closing authority.


Date when the case was closed.


Reason for case closure (conviction, plea_agreement, dismissal, insufficient_evidence, statute_limitations, death_of_suspect, administrative_closure).


Links reviewer to review process.


Date when the document was created.


Links case management to its current operational phase. gUFO Phase modeling for case state management.


Status of the document (draft, review, approved, filed, sealed, archived, destroyed).


Type of document (case_report, evidence_log, interview_notes, search_warrant, arrest_warrant, court_filing, expert_report).


Links documentation to creating personnel.


Final legal disposition (guilty_verdict, not_guilty_verdict, plea_guilty, plea_no_contest, charges_dropped, case_dismissed, no_charges_filed).


Links workflow stage to preceding stage.


Links case to workflow stages and processes. Enhanced with gUFO Event sequence modeling.


Links case to performance metrics and analytics.


Links case to personnel assignments. Enhanced with gUFO Role assignment relationships.


Links case to associated documentation.


Links case management to phase transition events.


Links person to case management role they hold. Enhanced with gUFO Role assignment.


Years of experience of the assigned investigator.


Level of jurisdiction (local, state, federal, multi_state, international, joint_jurisdiction).


Date when the document was last modified.


Date and time of the last update to case tracking.


Links case management to specific investigations. Enhanced with gUFO Object-Event relationships.


Unit of measurement (days, hours, percentage, count, dollars, score, ratio).


Links metrics to performance measurement targets.


Type of metric (case_duration, resolution_rate, conviction_rate, resource_utilization, cost_per_case, quality_score).


Numerical value of the metric.


Links entities to case management situations they participate in.


Links workflow stage to subsequent stage.


Number of recommendations made during the review.


Period for metric reporting (daily, weekly, monthly, quarterly, annually, case_based).


Links case to closure information and final disposition.


Document retention period in days.


Date when the review was conducted.


Outcome of the review (approved, approved_with_conditions, requires_revision, rejected, escalated, deferred).


Type of review (supervisory_review, peer_review, quality_assurance, legal_review, administrative_review, external_review).


Links documentation to reviewing personnel.


Role of the reviewer (supervisor, senior_investigator, prosecutor, legal_counsel, quality_assurance, external_expert).


Links review to case being reviewed.


Area of specialization (digital_forensics, undercover_operations, victim_services, legal_analysis, technical_analysis, general_investigation).


Duration of the workflow stage in days.


Date when the workflow stage ended.


Outcome of the workflow stage (completed, pending, escalated, transferred, suspended, terminated).


Date when the workflow stage began.


Links assignment to supervising personnel.


Links case to tracking systems and processes.


Unique tracking number for the case.


System used for tracking (local_system, state_system, federal_system, ncmec_system, multi_system, custom_system).


Links case to review processes.


Frequency of updates (real_time, daily, weekly, bi_weekly, monthly, as_needed).


Current stage in the case workflow (intake, initial_review, investigation, evidence_analysis, prosecution_review, court_proceedings, disposition).


Percentage of workload allocated to this assignment.


Phase when custodial relationship is actively maintained and operational. Modeled as anti-rigid gUFO Phase.


Validates active custody phases.


Abuse of authority position to exploit or harm children. Modeled as gUFO SubKind with authority relationship violations.


Individual in position of authority, trust, or power over children. Modeled as anti-rigid gUFO Role with relational foundation.


Validates authority figures as anti-rigid gUFO roles.


Validation shape for authority position instances.


Validates authority role exclusivity constraints.


Validation shape for authorization process instances.


Individual temporarily caring for children in parents' absence. Modeled as anti-rigid gUFO Role with temporary scope.


Background verification conducted for custodial or care position. Modeled as gUFO Object with verification results.


Validation shape for background check instances.


Validates background check temporal consistency.


Failure to provide appropriate care while in custodial role. Modeled as gUFO SubKind with care obligation failures.


Relationship involving responsibility for child's care, welfare, or supervision. Modeled as gUFO SubKind of CustodialRelationship.


Validation shape for caregiver relationship instances.


Professional childcare or daycare provider. Modeled as anti-rigid gUFO Role with professional care obligations.


Sports or activity coach with authority over young participants. Modeled as anti-rigid gUFO Role with activity-based authority.


Abuse committed by someone in custodial or caregiving role. Modeled as gUFO SubKind of TrustViolation with role-based context.


Official authorization granting custodial rights or responsibilities. Modeled as gUFO Object with legal authority.


Emergency situation requiring immediate custodial intervention. Modeled as gUFO Situation with crisis characteristics.


Validates cross-references between custodial relationships and related entities.


Custodial gUFO Foundational Type Consistency Shape

Validates proper gUFO foundational typing for custodial entities.


Validates coherent participation in custodial relationships.


Legal or informal relationship involving custody, care, or supervision of a child. Modeled as gUFO Object with Kind typing for rigid identity criteria.


Validates custodial relationship instances with gUFO foundational constraints.


Validation shape for custodial relationship instances.


Validates custodial situations with gUFO constraints.


Validates temporal consistency across custodial relationships and events.


Formal or informal arrangement for child custody or care. Modeled as gUFO Object with temporal arrangement characteristics.


Validates custody phases as anti-rigid gUFO phases.


Validates data quality for custodial relationships.


Temporary custody arrangement due to emergency circumstances. Modeled as anti-rigid gUFO Phase with crisis response characteristics.


Family-based relationship with natural or assumed custodial responsibilities. Modeled as gUFO SubKind with inherent care obligations.


Friend of family with trusted access to children. Modeled as anti-rigid gUFO Role with social trust basis.


Legally established custody arrangement with court orders or official documentation. Modeled as gUFO SubKind with legal foundation.


Legal or appointed guardian responsible for child's welfare. Modeled as anti-rigid gUFO Role with legal authority.


Informal custody arrangement without legal documentation. Modeled as gUFO SubKind with social agreement basis.


Adult mentor or role model with trusted relationship with child. Modeled as anti-rigid gUFO Role with developmental basis.


Validation shape for neighbor relationship instances.


Consent given by parent or guardian for custodial arrangement. Modeled as gUFO Object with authorization characteristics.


Role or position that grants special access to or authority over children. Modeled as anti-rigid gUFO Role with temporal participation.


Validates position of trust with gUFO anti-rigid role constraints.


Validation shape for position of trust instances.


Phase when custodial relationship is under evaluation or supervision. Modeled as anti-rigid gUFO Phase.


Professional relationship involving child care or supervision duties. Modeled as gUFO SubKind with professional obligations.


Family member in position of trust or authority over child. Modeled as anti-rigid gUFO Role with familial basis.


Validation shape for residential proximity access instances.


Situation where supervision systems have failed or become inadequate. Modeled as gUFO Situation with system failure characteristics.


Failure to properly supervise or protect child while in position of authority. Modeled as gUFO SubKind with supervision duty violations.


Validation shape for supervision failure instances.


Phase when custodial relationship is temporarily suspended but not terminated. Modeled as anti-rigid gUFO Phase.


Educational professional with authority over students. Modeled as anti-rigid gUFO Role with institutional authority.


Validates temporal consistency in custodial relationships.


Short-term custody arrangement or supervision of a child. Modeled as anti-rigid gUFO Phase with temporal boundaries.


Phase when custodial relationship has been formally ended. Modeled as anti-rigid gUFO Phase.


Validates terminated custody phases.


Situation arising from violation of trust or authority position. Modeled as gUFO Situation with trust violation context.


Validates trust breach situations.


Validates trust level consistency in violations.


Action that violates a position of trust or custodial responsibility. Modeled as gUFO Event with temporal boundaries and participation patterns.


Validates trust violations as gUFO events with temporal boundaries.


Validation shape for trust violation instances.


Scheduled visitation or contact arrangement with child. Modeled as gUFO SubKind with temporal scheduling patterns.


Situation where child vulnerability factors create elevated risk. Modeled as gUFO Situation with protection need characteristics.


Level of access to child (supervised, unsupervised, unrestricted, private).


Links trust violation to criminal offense as aggravating factor. Enhanced with gUFO causal patterns.


Level of authority over child (limited, moderate, extensive, complete).


Scope of authority (physical_care, educational, medical, financial, legal).


Level of authorization granted (basic, intermediate, full, emergency).


Duration of trust violation in days.


Scope of background check (criminal, employment, reference, comprehensive).


Status of background check (passed, failed, pending, waived).


Scope of activities covered by consent (general_care, specific_activities, emergency_care).


Status of parental consent (given, withdrawn, conditional, disputed).


Links custodial event to situation it creates or modifies. Enhanced with gUFO causation patterns.


Duration of custody arrangement in days.


Schedule or pattern of custody (weekdays, weekends, alternating, specific_dates).


Type of custody (legal, physical, joint, sole, temporary).


Links authority figure to their authority position. Enhanced with gUFO role patterns.


Temporal begin point when custodial relationship started.


Temporal end point when custodial relationship terminated.


Links custodial relationship to all phases it has experienced. Enhanced with gUFO phase history.


Temporal begin point when authority role started.


Temporal end point when authority role ended.


Temporal begin point when trust violation started.


Temporal end point when trust violation ceased.


Links individual to position of trust or authority they hold. Enhanced with gUFO role instantiation patterns.


Links custodial relationship to its current phase. Enhanced with gUFO phase transitions.


Links custodial relationship to the child under care. Enhanced with gUFO participation patterns.


Links custodial relationship to the custodian or authority figure. Enhanced with gUFO participation patterns.


Links custodial arrangement to the parent or legal guardian. Enhanced with gUFO participation patterns.


Links custodial event to situation in which it occurs. Enhanced with gUFO situation modeling.


Links trust violation to the authority figure who perpetrated it. Enhanced with gUFO event participation patterns.


Duration of custodial relationship in months.


Frequency of contact or care (daily, weekly, monthly, occasional).


Level of closeness in relationship (distant, moderate, close, very_close).


Type of custodial relationship (guardian, babysitter, relative, teacher, coach, mentor, daycare).


Links custodial relationship to ICAC investigation. Enhanced with gUFO relevance patterns.


Links child to authority figure who has control over them. Enhanced with gUFO role relationships.


Level of supervision provided (none, minimal, moderate, close, constant).


Level of trust placed in authority figure (low, moderate, high, complete).


Links trust violation to the position of trust that was violated. Enhanced with gUFO event causation patterns.


Links trust violation to the custodial relationship that was violated. Enhanced with gUFO event impact patterns.


Pattern of violation (isolated, repeated, escalating, systematic).


Severity level of trust violation (minor, moderate, severe, extreme).


Type of trust violation (abuse_of_authority, breach_of_care, exploitation, negligence).


Factors that increase child's vulnerability (isolation, dependency, trust, fear).


The action of using automated systems to detect potential CSAM content. Modeled as gUFO Event.


Validates automated detection action instances with gUFO Event constraints.


Validates COPINE classification concept instances with gUFO enhancements.


Classification Action Result Cross Reference Shape

Validates that classification actions produce classification results.


The result of content classification using standard scales like SAR or COPINE. Modeled as gUFO Object.


Validates classification result instances with gUFO Object constraints.


Validates classification schemes as gUFO Objects.


Validates confidence score consistency and reasonableness.


Role of professional analyzing flagged content for classification. Modeled as anti-rigid gUFO Role.


The action of generating cryptographic or perceptual hashes for content identification and matching. Modeled as gUFO Event.


Validates content hashing action instances with gUFO Event constraints.


A tool for generating perceptual or cryptographic hashes for content matching (e.g., PhotoDNA, pHash, MD5). Modeled as gUFO Object.


Validates content hashing tool instances with gUFO foundational constraints.


Situation involving detection across multiple platforms and services. Modeled as gUFO Situation.


The action of comparing content against known CSAM hash databases. Modeled as gUFO Event.


Database Match Input Cross Reference Shape

Validates that database match actions have hash inputs.


A tool for matching content against known CSAM databases (e.g., NCMEC hash database, INTERPOL ICSE database). Modeled as gUFO Object.


Validates detection actions as gUFO Events with temporal boundaries.


Detection Action Result Cross Reference Shape

Validates that detection actions produce appropriate results.


Validates data quality for detection tool entities.


Detection gUFO Foundational Type Consistency Shape

Validates proper gUFO foundational typing for detection entities.


Validates detection phases as anti-rigid gUFO phases.


Validates proper sequencing of detection phases.


The result of a content detection action including confidence scores and classification. Modeled as gUFO Object.


Validates detection results as gUFO Objects.


Validates detection result instances with gUFO Object constraints.


Validates detection roles as anti-rigid gUFO roles.


Validates detection role participation constraints.


Validates detection situations with gUFO constraints.


Validates temporal consistency across detection events and phases.


Validates detection tools as gUFO Objects with foundational constraints.


Validates temporal workflow progression in detection processes.


The action of analyzing and documenting false positive detections to improve accuracy. Modeled as gUFO Event.


Situation focused on managing and reducing false positive detection rates. Modeled as gUFO Situation.


Role of specialist working with hash databases and matching systems. Modeled as anti-rigid gUFO Role.


Validates hash artifacts as gUFO Objects.


Phase of comparing content hashes against known databases. Modeled as anti-rigid gUFO Phase.


Validates hash format and consistency.


Hashing Action Result Cross Reference Shape

Validates that hashing actions produce hash artifacts.


Phase of initial automated content detection and flagging. Modeled as anti-rigid gUFO Phase.


A tool using machine learning algorithms to detect CSAM content (e.g., Google's CSAI Classifier, Facebook's neural networks). Modeled as gUFO Object.


gUFO Machine Learning Detection Tool Shape

Validates machine learning detection tool instances with gUFO foundational constraints.


Role of specialist developing and maintaining ML detection systems. Modeled as anti-rigid gUFO Role.


The action of human review and classification of suspected CSAM content. Modeled as gUFO Event.


Validates manual classification action instances with gUFO Event constraints.


Phase of human expert review and classification. Modeled as anti-rigid gUFO Phase.


A tool supporting human review and classification of potentially illegal content. Modeled as gUFO Object.


Situation involving analysis of large volumes of content requiring coordinated detection systems. Modeled as gUFO Situation.


Validates mass content analysis situations.


A hash that captures visual similarity rather than exact bit patterns (e.g., pHash, aHash, dHash). Modeled as gUFO Object.


Validates perceptual hash instances with gUFO foundational constraints.


A Microsoft PhotoDNA hash for robust image matching that survives common transformations. Modeled as gUFO Object.


Validates PhotoDNA hash instances with gUFO foundational constraints.


Role focused on validating detection accuracy and managing quality metrics. Modeled as anti-rigid gUFO Role.


Phase of generating reports and notifications to authorities. Modeled as anti-rigid gUFO Phase.


The action of producing a risk-stratified assessment to prioritize downstream review and operational response beyond raw detection flags (e.g., risk-tiering, scoring, rationale).


Validates risk stratification actions that produce explainable prioritization outputs.


A risk-stratified output artifact (tier/score/rationale) produced from detection or tip signals to support explainable prioritization.


Validates risk stratification result artifacts with optional tier/score and explainability rationale.


Validates SAR classification concept instances with gUFO enhancements.


Phase of validating detection results and reducing false positives. Modeled as anti-rigid gUFO Phase.


Estimated age or age range of depicted individuals.


The confidence score (0.0-1.0) of the detection or classification result.


Links content to its COPINE classification level.


Links a detection action to the content that was analyzed.


Duration of detection action from start to completion.


The threshold value used for determining positive detection.


The reason why content was determined to be a false positive.


Links a hashing action to the hash that was generated.


Temporal begin point for detection action.


Temporal end point for detection action.


Temporal begin point for detection phase.


Temporal end point for detection phase.


Temporal begin point for detection role.


Temporal end point for detection role.


The specific algorithm used for perceptual hashing (e.g., 'pHash', 'aHash', 'dHash').


The type of match found (e.g., 'exact', 'near-duplicate', 'variant').


Links a match action to the database that contained the matching hash.


The version of the machine learning model used for detection.


The perceptual hash value as a hexadecimal string.


Duration of detection phase.


The PhotoDNA hash value as a hexadecimal string.


Links a risk stratification action to the risk stratification result it produced.


The decision made during manual review (e.g., 'confirmed', 'rejected', 'uncertain').


Links a classification action to the person who performed the review.


Explainable rationale describing why a given tier/score was assigned (features, rules, evidentiary factors, or analyst judgment summary).


Links a risk stratification result to the observable object it pertains to (e.g., detected content, a tip artifact, or another observable signal).


Numeric risk score used for prioritization (0.0-1.0 or other documented scale). Exact scale should be documented in risk rationale or associated documentation.


Categorical risk tier assigned for prioritization (e.g., critical/high/medium/low).


Duration of individual's detection role.


Links content to its SAR (1-5) classification level.


The similarity score for perceptual hash matches (0.0-1.0).


Links a risk stratification action to the detection result it stratifies for prioritization.


Tanner stage assessment for physical development (1-5).


Exploitation occurring during academic activities such as assignments, tests, or tutoring. Enhanced as gUFO Event.


Use of academic authority to intimidate and create vulnerability in students. Enhanced as gUFO Event.


Anti-rigid phase representing academic terms during which exploitation may occur.


Administrative role within educational institution with oversight responsibilities. Enhanced as anti-rigid gUFO Role.


Exploitation occurring in classroom setting outside normal school hours. Enhanced as gUFO Object.


Exploitation occurring while student is completing assignments or homework in classroom. Enhanced as gUFO Object.


Harassment through inappropriate comments written on student assignments or homework. Enhanced as gUFO Event.


Sexual exploitation occurring within classroom setting during academic activities. Enhanced as gUFO Event.


Specific classroom situations and contexts where exploitation occurs. Enhanced as gUFO Object for context modeling.


Athletic or activity coaching role with student interaction. Enhanced as anti-rigid gUFO Role.


Counseling role providing guidance and support to students. Enhanced as anti-rigid gUFO Role.


Exploitation targeting students from multiple educational institutions. Enhanced as gUFO Event with multi-institutional coordination.


Cross Institutional Investigation Situation

Situation requiring coordination between multiple educational institutions, law enforcement, and regulatory bodies.


Degrading or humiliating written comments designed to undermine student confidence. Enhanced as gUFO Event.


Complex situation involving educational institutions, educators, students, families, and legal systems in exploitation cases.


Educational institution where child exploitation occurs, including schools, colleges, and educational programs. Enhanced as gUFO Organization for comprehensive institutional modeling.


Child sexual exploitation committed by educational institution personnel using their position of trust and authority. Enhanced as gUFO Event for comprehensive temporal and causal modeling.


Professional role within educational institution with access to students. Enhanced as anti-rigid gUFO Role for role evolution modeling.


High-status educational institution with selective admission and affluent student body. Enhanced as gUFO Organization.


Anti-rigid phase representing educator's employment period during which exploitation occurs.


Anti-rigid phase representing escalation of exploitative behavior over time.


Physical education teacher role with student interaction in athletic contexts. Enhanced as anti-rigid gUFO Role.


Sexual exploitation involving immediate physical contact without prior grooming or relationship building. Enhanced as gUFO Event.


Private independent school, often with elite status and specialized educational programs. Enhanced as gUFO Organization.


Situation involving institutional response to exploitation allegations, including investigation, disciplinary action, and prevention measures.


Intermediate or middle school serving grades 6-8, typically ages 11-14. Enhanced as gUFO Organization.


Anti-rigid phase representing institutional or legal investigation of exploitation allegations.


Mathematics teacher role with specialized subject matter expertise. Enhanced as anti-rigid gUFO Role.


Middle school serving grades 6-8 or similar intermediate grade levels. Enhanced as gUFO Organization.


Situation involving multiple victims across multiple institutions or time periods.


Exploitation during individual academic assistance or tutoring sessions. Enhanced as gUFO Object.


Exploitation leveraging educator's position of trust and authority over students. Enhanced as gUFO Event.


Private educational institution with tuition-based funding. Enhanced as gUFO Organization.


Public educational institution funded by government entities. Enhanced as gUFO Organization.


Temporary teaching role covering for regular teachers. Enhanced as anti-rigid gUFO Role with temporary status.


Teaching role with direct instructional responsibility for students. Enhanced as anti-rigid gUFO Role.


Sexual exploitation of students by teachers using position of authority and trust. Enhanced as gUFO Event.


Exploitation occurring while student is taking tests or examinations. Enhanced as gUFO Object.


Harassment through written comments on student work, assignments, or academic materials. Enhanced as gUFO Event.


Type of academic activity during which exploitation occurred.


Level of access to students and institutional resources.


Links disclosure to mandatory reporting activation.


Actual age of perpetrator.


Links safeguarding measure to vulnerability it addresses.


Type of assignment on which harassment was written.


Links student victim to educational institution they attend.


Bail amount set for defendant.


Specific body part inappropriately touched.


Bond amount alternative to cash bail.


Number of charges filed.


Degree of criminal charge (first, second, third).


Links criminal charge to defendant being charged.


Classroom number or identifier where exploitation occurred.


Links investigation to evidence collected.


Links exploitation to communication platform used.


Duration of physical contact in seconds.


Frequency of inappropriate physical contact incidents.


Type of inappropriate physical contact.


Links investigation to coordinating agencies.


Links evidence to victim account it corroborates.


Links impersonation to victim being deceived.


Duration of impersonation in months.


Level of degradation in written comments (mild, moderate, severe).


Links degrading comments to victim being degraded.


Links victim disclosure to staff member receiving disclosure.


Method used by victim to disclose exploitation.


Links evidence to exploitation it documents.


Links written harassment evidence to harassment it documents.


Links exploitation to specific academic activity.


Age of educator at time of exploitation.


Links educator to institution where they were employed.


Duration of employment at educational institution in months.


Links charge to enhancement factors.


Links initial contact to escalated contact patterns.


Location where evidence was found or collected.


Type of evidence collected.


Duration of exploitation activity in months.


Primary location where exploitation occurred.


Primary method used for exploitation (digital, physical, combined).


Links exploitation to isolation vulnerability.


Links exploitation to educator position being exploited.


Links targeting to vulnerability being exploited.


Number of fake accounts used for impersonation.


Links sentence to post-release supervision period.


Level of force used in physical contact (minimal, moderate, significant).


Links forcible touching to victim.


Grade level taught by educator.


Grade range served by institution (e.g., 6-8, K-12).


Content of written harassment message or comment.


Frequency of written harassment incidents.


Medium used for written harassment (assignment, test, note).


Links institution to vulnerability factors present.


Links targeting to vulnerability identification.


Age claimed during impersonation.


Links impersonation to age deception.


Links institution to safeguarding measures implemented.


Number of educational institutions involved in exploitation.


Geographic location of educational institution.


Reputation level of institution (elite, prestigious, standard).


Type of educational institution (independent, public, private, elite).


Links investigation to victim interviews.


Links academic intimidation to student being intimidated.


Links investigation to exploitation being investigated.


Links exploitation to physical contact patterns.


Links exploitation to written harassment activities.


Level of isolation during exploitation (alone, few_students, class_present).


Links exploitation to academic power vulnerability.


Links IP address evidence to physical location.


Links impersonation to multiple account deception.


Whether mandatory reporting requirements were triggered.


Maximum possible sentence for charge in years.


Links staff reporting to principal notification.


Links exploitation to classroom or institutional context.


Digital platform used for impersonation and exploitation.


Time from notification to police response in hours.


Links victim account evidence to victim who provided it.


Links exploitation to evidence it provides.


Links staff member to report they receive.


Time delay between incident and reporting in days.


Role of staff member who received initial report.


Links victim to staff member they report to.


Links conviction to sex offender registration requirement.


Links exploitation to legal charges filed.


Physical address of educational institution.


Links targeting strategy to selected victim.


Links perpetrator to content sent to victims.


Length of prison sentence in years.


Links solicitation to victim being solicited.


Total number of students enrolled at institution.


Number of other students present during exploitation.


Academic subject taught by educator.


Duration of post-release supervision in years.


Links exploitation to specific classroom or location.


Age range of targeted victims.


Gender preference in victim targeting.


Method used to identify and target victims.


Links age-specific targeting to targeted age group.


Links targeting activity to student victim.


Links exploitation to victim targeting strategy.


Time of day when exploitation occurred.


Links physical contact to victim being touched.


Links principal notification to police notification.


Links exploitation to digital impersonation method used.


Links exploitation to specific methods used.


Number of victims involved in exploitation.


Specific vulnerability factor exploited in targeting.


Links witness testimony to exploitation witnessed.


Content of written harassment evidence.


Links written harassment to academic material it was written on.


Years of teaching or educational experience.


Extremist group with accelerationist goals seeking to hasten societal collapse through criminal activities including child exploitation.


System controlling access to enterprise channels and resources based on member status and content contributions.


System of alternate accounts (alts) used to evade platform restrictions and maintain operations.


Coercion of victims to abuse pets or animals as part of exploitation and control.


Criminal enterprise as defined in 18 U.S.C. § 2252A(g) engaging in coordinated child exploitation activities with multiple participants and systematic operations.


Recruitment of new members based on quality and notoriety of content they produce.


System for compiling, editing, and organizing exploitative content within criminal enterprise.


Action of curating and organizing exploitative content for enterprise purposes.


System using exploitative content as valuable currency within criminal enterprise for advancement and access.


Process of editing and organizing victim content into compilations for enterprise distribution.


Role focused on producing high-quality exploitative content for enterprise operations.


Assessment of content value based on quality, notoriety, and enterprise utility.


Role coordinating activities across different platforms and channels within enterprise.


Operation using online covert employees (OCE) to infiltrate and monitor extremist networks.


Coordination of enterprise activities across multiple internet platforms and channels.


Correlation of evidence across multiple platforms to establish identity and network connections.


Extremist network operating primarily through digital platforms and encrypted communications.


Infiltration of encrypted channels used by extremist networks for evidence collection.


Network of encrypted messaging channels used for enterprise coordination and content sharing.


Organizational hierarchy within child exploitation enterprise defining leadership and member roles.


Leadership role within child exploitation enterprise, directing and coordinating activities.


Role within child exploitation enterprise structure.


Coercion of victims to engage in extreme degrading activities beyond typical exploitation.


Operational cell within larger extremist network conducting specialized activities.


Analysis correlating multiple accounts and identities across platforms to establish single individual control.


Elite inner core of enterprise members with access to restricted channels and advanced activities.


Role of member within enterprise inner core with access to restricted channels and advanced operations.


Leadership structure of enterprise including multiple leaders and their areas of control.


Edited compilation of victim content including images, videos, and personal information organized by enterprise members.


System governing member advancement within enterprise based on content contributions and activities.


Membership tier within enterprise hierarchy determining access and privileges.


Targeting of minors with mental health challenges and psychological vulnerabilities.


Coercion of victims to cut enterprise member names into their bodies as ownership marking.


Investigation mapping the structure and relationships within extremist child exploitation networks.


Criminal network engaging in child exploitation as part of broader nihilistic violent extremism goals including social unrest and downfall of current world order (e.g., 764 network).


Strategy for migrating operations between platforms when accounts are terminated or restricted.


Management of private groups and channels with restricted access for enterprise operations.


Hierarchy governing recruitment of new members based on content quality and notoriety.


Role specializing in recruiting new members based on content quality and enterprise needs.


Coercion of victims to engage in self-harm activities including cutting, burning, and extreme degradation.


Coercion of victims to set themselves on fire or engage in burning activities.


Coercion of victims to abuse siblings or family members as part of exploitation.


Systematic social engineering campaign to gain victim trust and facilitate exploitation.


Coercion of victims toward suicide as ultimate form of exploitation and control.


Process of building trust with vulnerable victims before exploitation begins.


Organized compilation of content obtained from specific victim through exploitation and coercion.


Development of detailed victim profiles including vulnerabilities and exploitation opportunities.


Systematic targeting of vulnerable populations including minors with mental health challenges.


Level of access to enterprise resources and channels.


Criteria required for advancement to higher membership levels.


Number of alternate accounts maintained per member.


Links social engineering to trust building process.


Number of channels maintained in encrypted network.


Links enterprise role to victims coerced into self-harm.


Effectiveness of coercion methods in victim compliance.


Severity level of coercion methods used (moderate, severe, extreme, life_threatening).


Complexity level of content compilation and editing.


Links compilation system to content it compiles.


Links lorebook to victim content it contains.


Notoriety level of content within enterprise and broader network.


Assessed value of content within enterprise currency system.


Number of individual content items in compilation.


Links enterprise to cross-platform coordination activities.


Links coordinator to activities they coordinate.


Links investigation to evidence correlation performed.


Links coercion events to victimization situations they create.


Level of degradation and humiliation involved in coercion.


Quality level of content editing and organization.


Level of encryption used in communications (basic, strong, military_grade).


Quality level of evidence obtained through covert operations.


Links enterprise role to victims they exploit.


Begin date of coercion event using gUFO temporal framework.


Links encrypted network to its encryption capability as a mode.


Links enterprise to exploitation relator mediating perpetrator-victim relationships.


Links network to the event of its formation.


Links enterprise to its organizational hierarchy.


Links enterprise to its inner core structure.


Begin date of investigation event using gUFO temporal framework.


Links enterprise to leadership relator mediating leader-follower relationships.


Links enterprise to its members using gUFO collection membership pattern.


Links extremist network to its operational cells.


Links network to its functional components using gUFO component-of pattern.


Links network to its notoriety as a reified quality.


Begin date of enterprise operational period using gUFO temporal framework.


End date of enterprise operational period using gUFO temporal framework.


Links enterprise to its operational time period.


Links enterprise to its recruitment operation mode.


Complexity level of enterprise hierarchy (simple, moderate, complex, highly_complex).


Captures historical dependence between enterprise events and prior enabling events.


Links individual to leadership role in enterprise.


Links investigation to network members identified.


Accuracy level of identity correlation across platforms (0.0-1.0).


Ideological framework driving network activities (nihilistic, accelerationist, anarchist).


Links covert operation to network being infiltrated.


Duration of covert infiltration operation in days.


Number of members in enterprise inner core with advanced access.


Number of individuals in leadership roles within enterprise.


Links enterprise member to alternate accounts they maintain.


Links coordinator to private groups they manage.


Links mapping investigation to network structure mapped.


Member level within enterprise hierarchy (novice, member, advanced, inner_core, leader).


Requirements for enterprise membership and advancement.


Completeness of network mapping investigation (0.0-1.0).


Level of notoriety and recognition of network within extremist communities.


Estimated size of extremist network in number of participants.


Links network to child exploitation enterprise it operates.


Links enterprise operations to the situation context they occur in.


Geographic scope of network operations (local, national, international).


Links persons to coercion events they participate in.


Links individual to inner core membership.


Links persons to recruitment events they participate in.


Number of platforms used for coordination and operations.


Links content producer to lorebook they create.


Links recruitment specialist to members they recruit.


Type of self-harm coerced (cutting, burning, bruising, other).


Complexity level of social engineering campaigns.


Precision level of vulnerability targeting methods.


Links targeting action to specific vulnerability exploited.


Duration of trust building process before exploitation begins in days.


Links content currency system to content used as currency.


Links enterprise to encrypted channel networks used.


Type of vulnerability targeted (mental_health, isolation, trauma, substance_abuse).


Phase involving forensic acquisition of digital evidence.


Specialized search techniques for locating digital evidence.


Phase involving detailed forensic analysis of acquired evidence.


Automated analysis of large volumes of content using machine learning and AI for rapid classification and triage.


Validation shape for automated content analysis instances.


Analysis creating unique behavioral fingerprints from user activities to identify individuals across platforms.


Validation shape for behavioral fingerprinting instances.


An action that documents evidence handling, transfer, and custody maintaining legal admissibility.


Analysis of communication patterns to identify relationships and networks.


Analysis correlating content across multiple users and platforms for identifying networks and relationships.


Analysis correlating evidence across multiple platforms and services to identify coordinated criminal activities.


Validation shape for cross platform correlation instances.


Cross-referencing of digital evidence across multiple cases and international databases for victim identification.


Documentation recording the handling and transfer of evidence maintaining chain of custody.


Validates data quality for forensic entities.


Integration and correlation against multiple international databases and intelligence sources.


Assistance provided by trained detection dogs in forensic searches.


Forensic processing distributed across multiple systems and locations for handling massive evidence volumes.


Specialized detection of electronic storage devices using K9 or advanced scanning methods.


Electronic Storage Device Detection Shape

Validation shape for electronic storage device detection instances.


Role of a person responsible for evidence custody and security.


Automated system for triaging massive evidence volumes to prioritize high-value targets and critical cases.


Validation shape for evidence triage system instances.


The action of verifying evidence integrity using cryptographic hashes and comparison methods.


Evidence Verification Action Extended Shape

Extended validation shape for evidence verification action instances.


Investigation timeline spanning weeks, months, or years for complex child exploitation cases.


The action of creating a forensically sound copy of digital evidence using write-blocking and verification procedures.


Forensic Acquisition Action Extended Shape

Extended validation shape for forensic acquisition action instances.


Forensic Acquisition Cross Reference Shape

Validates cross-references between forensic acquisition and related entities.


Role of a person conducting digital forensic examination and analysis.


A bit-for-bit copy of digital media created using forensically sound methods, maintaining evidence integrity.


Extended validation shape for forensic image instances with comprehensive digital evidence requirements.


A tool specialized for creating forensic images of digital media using write-blocking and verification methods (e.g., FTK Imager, dd, Guymager, PALADIN).


Correlation analysis based on geographic and location data from multiple sources.


A tool specialized for generating cryptographic hashes for evidence verification (e.g., hashdeep, md5deep, NIST NSRL).


Recovery of concealed or hidden electronic storage devices during search operations.


Validation shape for hidden device recovery instances.


Image Analysis for Victim Identification

Analysis of seized images to identify and remove child victims from continued exploitation.


Validation shape for image analysis for victim identification instances.


Processing of evidence collected from international operations requiring coordination across multiple forensic labs.


Forensic process enhanced by K9 detection capabilities for electronic storage devices.


Validation shape for K9 assisted forensics instances.


AI/ML-powered correlation analysis to identify complex patterns not visible through traditional methods.


Processing of massive volumes of digital evidence requiring specialized automated tools and distributed processing systems (terabytes of data from platforms with millions of users).


Validation shape for mass digital evidence processing instances.


Validates mass digital evidence processing consistency.


A snapshot of volatile system memory captured for forensic analysis.


A tool specialized for analyzing volatile memory dumps (e.g., Volatility, Rekall, MAGNET RAM Capture).


Correlation analysis of metadata across multiple files and platforms.


The action of extracting metadata from digital artifacts including EXIF, file system timestamps, and application metadata.


A tool specialized for mobile device forensics including logical and physical extraction (e.g., Cellebrite UFED, MSAB XRY, Oxygen Detective Suite).


Extended validation shape for mobile forensic tool instances.


A capture of network traffic packets for forensic analysis.


A tool specialized for network traffic analysis and packet capture (e.g., Wireshark, NetworkMiner, Xplico).


Analysis of network traffic patterns to identify suspicious communications and data transfers.


Real-time correlation analysis for immediate identification of related evidence and ongoing activities.


A file recovered from deleted or unallocated space on digital media through forensic analysis techniques.


Extended validation shape for recovered file instances.


Phase involving preparation of forensic reports and findings.


Hash analysis systems capable of processing millions of files against large databases of known illegal content.


Validation shape for scalable hash analysis instances.


Analysis of temporal patterns and timing correlations across different pieces of evidence.


Validation shape for temporal pattern analysis instances.


Validates temporal consistency in forensic actions.


Phase involving expert testimony and courtroom presentation.


The action of creating chronological sequences of digital artifacts and events for investigation analysis.


Forensic analysis of user behavior patterns across massive user databases for investigation prioritization.


Validates evidence verification timing.


Systematic process for identifying child victims from seized images and videos during long-term investigations.


Validation shape for victim identification process instances.


Role of specialist focused on identifying child victims from digital evidence.


Action taken to remove identified victims from further harm and exploitation.


Validates write blocking usage in forensic acquisitions.


The method used for forensic acquisition (e.g., 'physical', 'logical', 'live', 'chip-off').


Links processing to user behavior forensic analysis.


Links user behavior analysis to communication pattern analysis.


Links user behavior analysis to network traffic analysis.


Links content correlation to temporal pattern analysis.


Number of arrests resulting from forensic investigations (e.g., 654 for SA JACET).


Percentage of processing performed through automated analysis.


Number of distinct behavior patterns identified in user analysis.


Number of unique behavioral fingerprints created from analysis.


The official exhibit number assigned to evidence for legal proceedings.


Complexity measure of communication graph analysis (simple, moderate, complex, highly_complex).


Links mass processing to international evidence processing coordination.


Links analysis to cross-platform correlation performed.


Links automated analysis to content correlation analysis.


Average latency for real-time correlation analysis in milliseconds.


Strength of content correlation found (weak, moderate, strong, very_strong).


Links user behavior analysis to fingerprinting performed.


Whether cross-border data sharing protocols are enabled.


Number of matches found across different platforms.


The reason for the custody transfer (e.g., 'forensic analysis', 'court exhibit', 'secure storage').


Links a chain of custody action to the person or organization transferring custody.


Links a chain of custody action to the person or organization receiving custody.


Volume of data transfers analyzed in terabytes.


Number of international databases integrated for intelligence correlation.


Accuracy rate of detection method (0.0-1.0).


Method used for device detection (K9, manual, electronic scanning).


Number of hidden devices recovered during search.


Links content correlation to criminal networks discovered.


Links mass processing to distributed processing systems.


Links automated analysis to real-time correlation capabilities.


The physical or logical location where evidence was found (e.g., 'bedroom computer', 'cloud storage', 'mobile device').


Links an acquisition action to the original evidence item that was seized.


Total volume of evidence in terabytes requiring processing.


False positive rate for automated content analysis (0.0-1.0).


Number of feature vectors used in machine learning analysis.


Number of files processed in millions for large-scale operations.


Accuracy of behavioral fingerprint matching (0.0-1.0).


Links an acquisition action to the forensic copy that was created.


Number of forensic laboratories involved in international evidence processing.


Duration of forensic phase.


Links a forensic action to its associated report or documentation.


Links real-time correlation to alerts generated.


Links triage system to results generated.


Geographic distribution of processing nodes (countries involved).


Geographic radius of correlation analysis in kilometers.


Accuracy of geospatial correlation analysis in meters.


Temporal begin point for forensic phase.


Temporal end point for forensic phase.


Temporal begin point for forensic role.


Temporal end point for forensic role.


Size of hash database used for comparison in millions of entries.


Number of hash matches found against known illegal content databases.


Links cross-platform analysis to activities identified.


Links geospatial analysis to geographic clusters identified.


Links network analysis to anomalies identified.


Links user behavior analysis to patterns identified.


Links temporal analysis to time-based clusters identified.


Links mass processing to database intelligence integration.


Number of intelligence hits found across integrated databases.


Duration of extended investigation (e.g., 'weeks', 'months', 'years').


Links international processing to participating forensic laboratories.


Whether K9 assistance was provided during forensic acquisition.


Number of location points included in geospatial analysis.


Accuracy of machine learning correlation models (0.0-1.0).


Number of network connections identified through content correlation.


Number of network sessions included in traffic analysis.


Whether parallel processing capabilities are enabled.


Links evidence processing to geospatial correlation analysis.


Links automated analysis to scalable hash analysis systems.


Correlation score across platforms (0.0-1.0).


Number of platforms included in cross-platform correlation analysis.


Priority classification assigned by triage system (critical, high, medium, low).


Links mass processing system to evidence being processed.


Number of processing nodes used in distributed forensic processing.


Processing speed in files per hour for automated systems.