Organization
Griffith University
Description
A study of what police officers believe they need to more effectively counter child sexual abuse material. The main training/support mentioned that organisations should provide included: communication, training on different types of perpetrators, and psychological support.
File
The Perspective of Online Investigators on Training and Support.pdf
Link
Tags
Child Sexual Abuse Material (CSAM)prosecutionPerpetrators
Type
Research (peer reviewed)
Year
2022
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Dark Web forum posts
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Anglia Ruskin University
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Stella Polaris Summit 2024 Summary
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World Childhood Foundation
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Generative AI - A New Threat for Online Child Sexual
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World Childhood Foundation
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Child Sexual Abuse on the Internet: Report on the Analysis of Technological Factors that Affect the Creation and Sharing of Child Sexual Abuse Material on the Internet.
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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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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
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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
Child predator abuse of generative AI
Child predator abuse of generative AI
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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Artificial intelligencePerpetratorsPreventionChild Sexual Abuse Material (CSAM)Generative AI
…det var en känsla av att han befann sig i rummet bredvid
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World Childhood Foundation
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Sperm hunting on optical microscope slides for forensic analysis with deep convolutional networks – a feasibility study
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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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5Rights Foundation
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Adhiyamaan College of Engineering
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Applying Artificial Intelligence for Age Estimation in Digital Forensic Investigations
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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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PreventionChild Sexual Abuse Material (CSAM)
Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions
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Columbia University
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EthicsDetectionPrevention
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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
How SARs fight online child sexual abuse by flagging financial crime
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Napier
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Predicting Prolific Live Streaming of Child Sexual Abuse
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Australian Institute of Criminology
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Financial transactionsArtificial intelligenceSupervised learningMachine learningCriminal investigationChild Sexual Abuse Material (CSAM)
Automated Biometric Identification using Dorsal Hand Images and Convolutional Neural Networks
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Auckland University of Technology
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Multimodal Virtual Avatars for Investigative Interviews with Children
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Oslo Metropolitan University
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Criminal investigationprosecution
Early Detection of Sexual Predators in Chats
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Humboldt Universitat zu Berlin
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Natural Language ProcessingClustering/Classification
When “Sweetie” is not so Sweet: Artificial Intelligence and its Implications for Child Pornography
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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
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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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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
Summary Paper on Online Child Sexual Exploitation
ECPAT
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PreventionChild Sexual Abuse Material (CSAM)Perpetrators
Curbing the Surge
in Online Child Abuse
Curbing the Surge
in Online Child Abuse
European Parliament
Report
PreventionNeural networks
Action to End child Sexual Abuse and Exploitation
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Unicef
Report
Child Sexual Abuse Material (CSAM)Prevention
Brief version: Action to End child Sexual Abuse and Exploitation
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Unicef
Report
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
Research (peer reviewed)
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
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Child-focusedPost-traumatic stress (PTS)Post-crime efforts
AI Roundtable 2019 Summary
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World Childhood Foundation
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PreventionArtificial intelligence
Artificial Intelligence: combating online sexual abuse of children
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Bracket Foundation
Report
PreventionNeural networksChild Sexual Abuse Material (CSAM)
Out of the Shadows Whitepaper
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The Economist Intelligence Unit
Report
PreventionChild Sexual Abuse Material (CSAM)
What Works to Prevent Sexual Violence Against Children
What Works to Prevent Sexual Violence Against Children
Together for girls
Report
Child Sexual Abuse Material (CSAM)PreventionFinancial transactions
Child Online Safety:
Minimizing the Risk of Violence,
Abuse and Exploitation Online.
Child Online Safety:
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
Therabot: An Adaptive Therapeutic Support Robot
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
Report
PreventionChild Sexual Abuse Material (CSAM)
Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users
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University of Queensland
Research (peer reviewed)
PreventionNeural networks