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Techniques to detect terrorists/extremists on the dark web: a review

Hanan Alghamdi (Umm Al-Qura University, AlQunfidhah, Saudi Arabia)
Ali Selamat (Universiti Teknologi Malaysia, Skudai, Malaysia)

Data Technologies and Applications

ISSN: 2514-9288

Article publication date: 6 January 2022

Issue publication date: 23 August 2022

685

Abstract

Purpose

With the proliferation of terrorist/extremist websites on the World Wide Web, it has become progressively more crucial to detect and analyze the content on these websites. Accordingly, the volume of previous research focused on identifying the techniques and activities of terrorist/extremist groups, as revealed by their sites on the so-called dark web, has also grown.

Design/methodology/approach

This study presents a review of the techniques used to detect and process the content of terrorist/extremist sites on the dark web. Forty of the most relevant data sources were examined, and various techniques were identified among them.

Findings

Based on this review, it was found that methods of feature selection and feature extraction can be used as topic modeling with content analysis and text clustering.

Originality/value

At the end of the review, present the current state-of-the- art and certain open issues associated with Arabic dark Web content analysis.

Keywords

Citation

Alghamdi, H. and Selamat, A. (2022), "Techniques to detect terrorists/extremists on the dark web: a review", Data Technologies and Applications, Vol. 56 No. 4, pp. 461-482. https://doi.org/10.1108/DTA-07-2021-0177

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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