在暗网上发现恐怖分子/极端分子的技术:综述

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Data Technologies and Applications Pub Date : 2022-01-06 DOI:10.1108/dta-07-2021-0177
H. Alghamdi, A. Selamat
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引用次数: 2

摘要

随着互联网上恐怖主义/极端主义网站的激增,检测和分析这些网站上的内容变得越来越重要。因此,以前的研究集中于识别恐怖主义/极端主义团体的技术和活动,正如他们在所谓的暗网上的网站所揭示的那样,数量也有所增加。设计/方法/方法本研究回顾了暗网上用于检测和处理恐怖主义/极端主义网站内容的技术。审查了40个最相关的数据来源,并在其中确定了各种技术。在此综述的基础上,发现特征选择和特征提取方法可以作为主题建模与内容分析和文本聚类。原创性/价值在回顾结束时,呈现当前的艺术状态和某些与阿拉伯暗网内容分析相关的开放问题。
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Techniques to detect terrorists/extremists on the dark web: a review
PurposeWith 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/approachThis 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.FindingsBased 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/valueAt the end of the review, present the current state-of-the- art and certain open issues associated with Arabic dark Web content analysis.
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来源期刊
Data Technologies and Applications
Data Technologies and Applications Social Sciences-Library and Information Sciences
CiteScore
3.80
自引率
6.20%
发文量
29
期刊介绍: Previously published as: Program Online from: 2018 Subject Area: Information & Knowledge Management, Library Studies
期刊最新文献
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