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Stella Polaris Knowledge Center
The reports database is where we collect recent scientific research reports on child sexual abuse and artificial intelligence. Each report is tagged to give you an overview of its contents, and you can sort them by publication date and other factors. Clicking on a report will provide you with additional information such as the year of publication, institution, author, and more.
To ensure the quality of our database, we only include research reports that meet our criteria. We aim to ensure that every source is deemed correct and credible by a minimum of 1 person who is an expert in the field. In general, reports should meet the following criteria:
- The source should be created by a credible organization.
- The organization should have experts in the field covered by the source
- The source should be regularly updated
We hope that this database will be a valuable resource for anyone seeking to stay up-to-date with the latest research in these important fields.
If you have a suggestion for a publication that you think should be included, please feel free to contact us through the contact form.
Contact UsGuarding the Guardians: Automated Analysis of Online Child Sexual AbuseGuarding the Guardians: Automated Analysis of Online Child Sexual Abuse
Criminal investigationNatural Language Processing
2023
Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive TextsFine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts
Cornell University
Machine learningNatural Language Processing
2023
BS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking ClassifierBS-SC Model: A Novel Method for Predicting Child Abuse Using Borderline-SMOTE Enabled Stacking Classifier
B. S. Abdur Rahman Crescent Institute of Science and Technology
PreventionDetectionClustering/Classification
2023
Applications of artificial intelligence in predicting the risk of child abuse: A literature reviewApplications of artificial intelligence in predicting the risk of child abuse: A literature review
King Faisal Specialist Hospital and Research Centre
Princess Nora bint Abdul Rahman University
Mississippi State University
DetectionChild-focusedNeural networks
2023
Discovering Child Sexual Abuse Material Creator´s Behaviors and
Preferences on the Dark WebDiscovering Child Sexual Abuse Material Creator´s Behaviors and
Preferences on the Dark Web
Technological University Dublin
Child Sexual Abuse Material (CSAM)PerpetratorsClustering/Classification
2023
Developing automated methods to detect and match face and voice biometrics in child sexual abuse videosDeveloping automated methods to detect and match face and voice biometrics in child sexual abuse videos
San Jose State University
Child Sexual Abuse Material (CSAM)Perpetrators
2022
Child Sexual Abuse Material Online: The Perspective of Online Investigators on Training and SupportChild Sexual Abuse Material Online: The Perspective of Online Investigators on Training and Support
Griffith University
Child Sexual Abuse Material (CSAM)prosecutionPerpetrators
2022
Child Abuse Risk Prediction and Prevention Framework using AI and Dark WebChild Abuse Risk Prediction and Prevention Framework using AI and Dark Web
Adhiyamaan College of Engineering
Child Sexual Abuse Material (CSAM)PreventionNeural networks
2022
Applying Artificial Intelligence for Age Estimation in Digital Forensic InvestigationsApplying Artificial Intelligence for Age Estimation in Digital Forensic Investigations
University of Warwick
Artificial intelligenceNeural networks
2022
Sperm hunting on optical microscope slides for forensic analysis with deep convolutional networks – a feasibility studySperm hunting on optical microscope slides for forensic analysis with deep convolutional networks – a feasibility study
Zurich Institute of Forensic Medicine
Perpetrators
2022
Developing machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutionsDeveloping machine learning-based models to help identify child abuse and neglect: key ethical challenges and recommended solutions
Columbia University
EthicsDetectionPrevention
2022
Hand-Based Person Identification Using Global and Part-Aware Deep Feature Representation LearningHand-Based Person Identification Using Global and Part-Aware Deep Feature Representation Learning
Lancaster University
Artificial intelligenceprosecutionChild Sexual Abuse Material (CSAM)Machine learning
2022
Automated Biometric Identification using Dorsal Hand Images and Convolutional Neural NetworksAutomated Biometric Identification using Dorsal Hand Images and Convolutional Neural Networks
Auckland University of Technology
Neural networksPerpetrators
2021
Multimodal Virtual Avatars for Investigative Interviews with ChildrenMultimodal Virtual Avatars for Investigative Interviews with Children
Oslo Metropolitan University
Criminal investigationprosecution
2021
Early Detection of Sexual Predators in ChatsEarly Detection of Sexual Predators in Chats
Humboldt Universitat zu Berlin
Natural Language ProcessingClustering/Classification
2021
Keeping Children Safe Online With Limited
Resources: Analyzing What is Seen and HeardKeeping Children Safe Online With Limited
Resources: Analyzing What is Seen and Heard
Singidunum University
PreventionClustering/ClassificationNeural networks
2021
Suspicious activity detection using deep learning in secure assisted living IoT environmentsSuspicious activity detection using deep learning in secure assisted living IoT environments
Nalla Malla Engineering College, Galgotias University, Vellore Institute of Technology
Child Sexual Abuse Material (CSAM)Neural networks
2021
Predicting Prolific Live Streaming of Child Sexual AbusePredicting Prolific Live Streaming of Child Sexual Abuse
Australian Institute of Criminology
Financial transactionsArtificial intelligenceSupervised learningMachine learningCriminal investigationChild Sexual Abuse Material (CSAM)
2021
Prediction of the development of depression and post-traumatic stress disorder in sexually abused children using a random forest classifierPrediction of the development of depression and post-traumatic stress disorder in sexually abused children using a random forest classifier
Uskudar University Medical Faculty, Istanbul, Turkey
Clustering/ClassificationMachine learningPost-crime effortsChild-focusedPost-traumatic stress (PTS)
2021
Estimation of the Development of Depression and PTSD in Children Exposed to Sexual Abuse and Development of Decision Support Systems by Using Artificial IntelligenceEstimation of the Development of Depression and PTSD in Children Exposed to Sexual Abuse and Development of Decision Support Systems by Using Artificial Intelligence
Inonu University
Child-focusedPost-traumatic stress (PTS)Post-crime efforts
2020
Sexuella övergrepp via nätet lika allvarliga som IRLSexuella övergrepp via nätet lika allvarliga som IRL
Göteborgs Universitet
Child-focusedChild Sexual Abuse Material (CSAM)Prevention
2020
Illegal Online Sexual Behavior During the COVID-19 PandemicIllegal Online Sexual Behavior During the COVID-19 Pandemic
Karolinska Institutet
PreventionPerpetratorsChild Sexual Abuse Material (CSAM)Financial transactions
2020
An Integrative Review of Historical Technology and Countermeasure Usage Trends in Online Child Sexual Exploitation Material OffenderAn Integrative Review of Historical Technology and Countermeasure Usage Trends in Online Child Sexual Exploitation Material Offender
University of Edinburgh and George Mason University
Child Sexual Abuse Material (CSAM)PerpetratorsCriminal investigationPrevention
2020
Therabot: An Adaptive Therapeutic Support RobotTherabot: An Adaptive Therapeutic Support Robot
Institute of Electrical and Electronics Engineers (IEEE) and Mississippi State University
Post-crime effortsChild-focusedRoboticsPost-traumatic stress (PTS)
2018
Child Abuse and Domestic Abuse: Content and Feature Analysis from Social Media DisclosuresChild Abuse and Domestic Abuse: Content and Feature Analysis from Social Media Disclosures
Victoria University and University of Melbourne
Artificial intelligenceMachine learningPreventionChild Sexual Abuse Material (CSAM)
2018
Offender strategies for engaging children in online sexual activityOffender strategies for engaging children in online sexual activity
Department of Psychology, University of Gothenburg
PreventionChild Sexual Abuse Material (CSAM)
2017
Predictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service UsersPredictive Risk Modelling to Prevent Child Maltreatment and Other Adverse Outcomes for Service Users
University of Queensland
PreventionNeural networks
2015
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