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  4. Detecting child sexual abuse material: A comprehensive survey
 
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2020
Journal Article
Titel

Detecting child sexual abuse material: A comprehensive survey

Abstract
Victims of child sexual abuse suffer from physical, psychological, and emotional trauma. The detection and deletion of illicit online child sexual abuse material (CSAM) helps in reducing and even stopping the continuous re-victimization of children. Furthermore, automatic detection may also support legal authorities to search for and review the masses of suspected CSAM. Due to tech-savvy offenders and technological advances, continuous efforts in keeping up with current developments are crucial and need to be considered in the implementation of detection algorithms. The present research provides a comprehensive synthesis and an interpretation of the current research accomplishments and challenges in the CSAM detection domain, explicitly considering the dimensions of policy and legal framework, distribution channels, and detection applications and implementations. Among other aspects, it reveals and aggregates knowledge related to image hash database, keywords, web-crawler, detection based on filenames and metadata, and visual detection. The findings suggest that CSAM detection applications yield the best results if multiple approaches are used in combination, such as deep-learning algorithms with multi-modal image or video descriptors merged together. Deep-learning techniques were shown to outperform other detection methods for unknown CSAM.
Author(s)
Lee, Hee-Eun
Humboldt University of Berlin
Ermakova, Tatiana
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Ververis, Vasilis
Humboldt University of Berlin / University of Amsterdam / University Institute of Lisbon
Fabian, B.
Zeitschrift
Forensic Science International : FSI. Digital Investigation
Thumbnail Image
DOI
10.1016/j.fsidi.2020.301022
Language
English
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Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS
Tags
  • child sexual abuse material

  • CSAM

  • online crime detection

  • social analysis of technology

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