Investigation, Detection and Prevention of Online Child Sexual Abuse Materials: A Comprehensive Survey-Reference-Cited by-同舟云学术

Investigation, Detection and Prevention of Online Child Sexual Abuse Materials: A Comprehensive Survey

Published:2022-12-20 Issue: Volume: Page:
ISSN:
Container-title:2022 RIVF International Conference on Computing and Communication Technologies (RIVF)
language:
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Author:

Ngox Vuong M.¹,Thorpe Christina²,Dang Cach N.³,Mckeever Susan¹

Affiliation:

1. School of Computer Science Technological University,Dublin,Ireland

2. School of Informatics and Cybersecurity Technological University,Dublin,Ireland

3. Science and Technology Application for Sustainable Development (STASD) Research Group Ho Chi Minh City University of Transport,Vietnam

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10013784/10013785/10013853.pdf?arnumber=10013853

Reference45 articles.

1. Developing automated methods to detect and match face and voice biometrics in child sexual abuse videos;hole;Trends and Issues in Crime and Criminal Justice,2022

2. Short text classification approach to identify child sexual exploitation material;ai-nabki;ArXiv Preprint,2020

3. Shield: Smart Detection System to Protect Children from Sexual Abuse

4. Detection and Characterization of Human Trafficking Networks Using Unsupervised Scalable Text Template Matching

5. Cyberbullying Detection on Social Networks Using Machine Learning Approaches

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1. Role of Artificial Intelligence in the Prevention of Online Child Sexual Abuse: A Systematic Review of Literature;Journal of Applied Security Research;2024-04

2. Discovering child sexual abuse material creators' behaviors and preferences on the dark web;Child Abuse & Neglect;2024-01

3. Guarding the Guardians: Automated Analysis of Online Child Sexual Abuse;2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW);2023-10-02

4. Metadata-Based Detection of Child Sexual Abuse Material;IEEE Transactions on Dependable and Secure Computing;2023