Techniques to detect terrorists/extremists on the dark web: a review
Data Technologies and Applications
ISSN: 2514-9288
Article publication date: 6 January 2022
Issue publication date: 23 August 2022
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
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