Organization
San Jose State University
Description
The report examines how biometric (facial) search combined with voice can be used to identify abuse survivors and perpetrators, by searching for matches in other child sexual abuse material videos.
File
Link
https://search.informit.org/doi/epdf/10.3316/informit.366337180343788
Tags
Child Sexual Abuse Material (CSAM)Perpetrators
Type
Research (peer reviewed)
Year
2022
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Child Sexual Abuse Material (CSAM)Generative AI
Stella Polaris Summit 2024 Summary
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BI Norwegian Business School, Norwegian University of Science and Technology
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InternetPolicyDetectionprosecutionPost-crime effortsCriminal investigation
Guarding the Guardians: Automated Analysis of Online Child Sexual Abuse
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Criminal investigationNatural Language Processing
Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts
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Cornell University
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Machine learningNatural Language Processing
Black and Latinx Primary caregiver considerations for developing and implementing a machine learning-based model for detecting child abuse and neglect with implications for racial bias reduction: A qualitative study
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BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier
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B. S. Abdur Rahman Crescent Institute of Science and Technology
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PreventionDetectionClustering/Classification
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King Faisal Specialist Hospital and Research Centre Princess Nora bint Abdul Rahman University Mississippi State University
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DetectionChild-focusedNeural networks
Determining Child Sexual Abuse Posts based on Artificial
Intelligence
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Intelligence
Technological University Dublin
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Child Sexual Abuse Material (CSAM)Clustering/Classification
Identifying Online Child Sexual Texts in Dark Web through
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Machine Learning and Deep Learning Algorithms
Technological University Dublin
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Child Sexual Abuse Material (CSAM)Machine learningDeep Learning
Discovering Child Sexual Abuse Material Creator´s Behaviors and
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Preferences on the Dark Web
Technological University Dublin
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Child Sexual Abuse Material (CSAM)PerpetratorsClustering/Classification
Generative AI: New Attack Vector for Trust & Safety
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Activefence
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Artificial intelligenceChild Sexual Abuse Material (CSAM)Generative AI
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Activefence
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Generative AIChild Sexual Abuse Material (CSAM)Artificial intelligence
How AI is being abused to create child sexual abuse imagery
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Internet Watch Foundation
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…det var en känsla av att han befann sig i rummet bredvid
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Zurich Institute of Forensic Medicine
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Perpetrators
Developing automated methods to detect and match face and voice biometrics in child sexual abuse videos
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San Jose State University
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Child Sexual Abuse Material (CSAM)Perpetrators
Child Sexual Abuse Material Online: The Perspective of Online Investigators on Training and Support
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Griffith University
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University of Warwick
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Hand-Based Person Identification Using Global and Part-Aware Deep Feature Representation Learning
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Lancaster University
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Artificial intelligenceprosecutionChild Sexual Abuse Material (CSAM)Machine learning
Out of the Shadows Index
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The Economist Intelligence Unit
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Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions
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Suojellaan Lapsia
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Unga sex och internet #MeToo
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Stiftelsen Allmänna Barnahus
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PreventionChild Sexual Abuse Material (CSAM)Child-focused
Internetrelaterade sexuella övergrepp mot barn
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Riksrevisionen
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PreventionChild Sexual Abuse Material (CSAM)prosecution
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Napier
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Australian Institute of Criminology
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Auckland University of Technology
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Oslo Metropolitan University
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Criminal investigationprosecution
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Humboldt Universitat zu Berlin
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Natural Language ProcessingClustering/Classification
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Child Sexual Abuse Material (CSAM)prosecution
Keeping Children Safe Online With Limited
Resources: Analyzing What is Seen and Heard
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Resources: Analyzing What is Seen and Heard
Singidunum University
Research (peer reviewed)
PreventionClustering/ClassificationNeural networks
Suspicious activity detection using deep learning in secure assisted living IoT environments
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Nalla Malla Engineering College, Galgotias University, Vellore Institute of Technology
Research (peer reviewed)
Child Sexual Abuse Material (CSAM)Neural networks
Prediction of the development of depression and post-traumatic stress disorder in sexually abused children using a random forest classifier
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Uskudar University Medical Faculty, Istanbul, Turkey
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Clustering/ClassificationMachine learningPost-crime effortsChild-focusedPost-traumatic stress (PTS)
NetClean Report 2020 - Covid-19 Impact
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NetClean
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Karolinska Institutet
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Sexuella övergrepp via nätet lika allvarliga som IRL
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Göteborgs Universitet
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Child-focusedChild Sexual Abuse Material (CSAM)Prevention
Summary Paper on Online Child Sexual Exploitation
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ECPAT
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PreventionChild Sexual Abuse Material (CSAM)Perpetrators
Curbing the Surge
in Online Child Abuse
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in Online Child Abuse
European Parliament
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PreventionNeural networks
Action to End child Sexual Abuse and Exploitation
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Unicef
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Brief version: Action to End child Sexual Abuse and Exploitation
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Unicef
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Child Sexual Abuse Material (CSAM)Prevention
An Integrative Review of Historical Technology and Countermeasure Usage Trends in Online Child Sexual Exploitation Material Offender
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University of Edinburgh and George Mason University
Research (peer reviewed)
Child Sexual Abuse Material (CSAM)PerpetratorsCriminal investigationPrevention
How Facial Recognition Is Helping Fight Child Sexual Abuse
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Griffeye
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Child Sexual Abuse Material (CSAM)Criminal investigationMachine learningArtificial intelligence
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University of Haifa
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Artificial intelligencePerpetratorsCriminal investigationSupervised learningNeural networksMachine learningChild-focusedChild Sexual Abuse Material (CSAM)
Estimation of the Development of Depression and PTSD in Children Exposed to Sexual Abuse and Development of Decision Support Systems by Using Artificial Intelligence
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Inonu University
Research (peer reviewed)
Child-focusedPost-traumatic stress (PTS)Post-crime efforts
AI Roundtable 2019 Summary
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World Childhood Foundation
Report
PreventionArtificial intelligence
Artificial Intelligence: combating online sexual abuse of children
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Bracket Foundation
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PreventionNeural networksChild Sexual Abuse Material (CSAM)
Out of the Shadows Whitepaper
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The Economist Intelligence Unit
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PreventionChild Sexual Abuse Material (CSAM)
What Works to Prevent Sexual Violence Against Children
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Together for girls
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Child Sexual Abuse Material (CSAM)PreventionFinancial transactions
Child Online Safety:
Minimizing the Risk of Violence,
Abuse and Exploitation Online.
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Minimizing the Risk of Violence,
Abuse and Exploitation Online.
ITU/UNESCO Broadband Commission for Sustainable Development
Report
PreventionPerpetrators
A Practitioner Survey Exploring the Value of Forensic Tools, AI, Filtering, & Safer Presentation for Investigating Child Sexual Abuse Material (CSAM)
A Practitioner Survey Exploring the Value of Forensic Tools, AI, Filtering, & Safer Presentation for Investigating Child Sexual Abuse Material (CSAM)
University of New Haven / Digital Forensic Research Workshop
Research (peer reviewed)
Artificial intelligencePreventionNeural networks
Therabot: An Adaptive Therapeutic Support Robot
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Institute of Electrical and Electronics Engineers (IEEE) and Mississippi State University
Research (peer reviewed)
Post-crime effortsChild-focusedRoboticsPost-traumatic stress (PTS)
Offender strategies for engaging children in online sexual activity
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Department of Psychology, University of Gothenburg
Research (peer reviewed)
PreventionChild Sexual Abuse Material (CSAM)
Study on the Effects of New Information Technologies on the Abuse and Exploitation
of Children
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of Children
UNODC
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PreventionChild Sexual Abuse Material (CSAM)
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University of Queensland
Research (peer reviewed)
PreventionNeural networks