Identifying Online Child Sexual Texts in Dark Web through Machine Learning and Deep Learning Algorithms

Organization

Technological University Dublin

Description

In this paper, we propose a novel model based on artificial intelligence algorithms to automatically detect CSA text messages in dark web forums. Our algorithms have achieved impressive results in detecting CSAM in dark web, with a recall rate of 89%, a precision rate of 92.3% and an accuracy rate of 87.6%. Moreover, the algorithms can predict the classification of a post in just 1 microsecond and 0.3 milliseconds on standard laptop capabilities. This makes it possible to integrate our model into social network sites or edge devices to for real-time CSAM detection.

File
Identifying Online Child Sexual Texts in Dark Web through Machine.pdf
Link
https://arrow.tudublin.ie/scschcomcon/393/
Tags
Child Sexual Abuse Material (CSAM)Machine learningDeep Learning
Type
Report
Year
2023
Stella Polaris Knowledge Center
Stella Polaris Knowledge Center
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