A Review of Web Classifier Approach with Possible Research Direction to Detect Cyber Extremists

Hassan Awad Hassan Al-Sukhni, M. Saudi, Azuan Ahmad
{"title":"A Review of Web Classifier Approach with Possible Research Direction to Detect Cyber Extremists","authors":"Hassan Awad Hassan Al-Sukhni, M. Saudi, Azuan Ahmad","doi":"10.1109/ICSGRC.2019.8837077","DOIUrl":null,"url":null,"abstract":"The internet is ever expanding and online information is booming, making identification and detection of different web information vitally important, particularly those of dark web or Cyber extremists. Webpages with extremist and terrorist content are believed to be main factors in the radicalization and recruitment of disaffected individuals who might be involved in terrorist activities at home or those who fight alongside terrorist groups abroad. In fact, the sheer volume of online data makes it practically impossible for authorities to carry out the individual examination for every webpage, post or conversational thread that might or might not be relevant to terrorism or contain terrorist sympathies. As terrorists exist within every nation and every religion, hence this paper presents a review and systematic analysis of existing webpages on Cyber Terrorists. This include of existing database of Cyber extremists words and existing techniques of web classifier for keywords. Based on this paper systematic analysis, it will be the input for the formation of a new Cyber extremists WorldNet.","PeriodicalId":331521,"journal":{"name":"2019 IEEE 10th Control and System Graduate Research Colloquium (ICSGRC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 10th Control and System Graduate Research Colloquium (ICSGRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSGRC.2019.8837077","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The internet is ever expanding and online information is booming, making identification and detection of different web information vitally important, particularly those of dark web or Cyber extremists. Webpages with extremist and terrorist content are believed to be main factors in the radicalization and recruitment of disaffected individuals who might be involved in terrorist activities at home or those who fight alongside terrorist groups abroad. In fact, the sheer volume of online data makes it practically impossible for authorities to carry out the individual examination for every webpage, post or conversational thread that might or might not be relevant to terrorism or contain terrorist sympathies. As terrorists exist within every nation and every religion, hence this paper presents a review and systematic analysis of existing webpages on Cyber Terrorists. This include of existing database of Cyber extremists words and existing techniques of web classifier for keywords. Based on this paper systematic analysis, it will be the input for the formation of a new Cyber extremists WorldNet.
基于Web分类器的网络极端分子检测研究综述
互联网规模不断扩大,网络信息蓬勃发展,识别和检测不同的网络信息至关重要,特别是那些暗网或网络极端分子的信息。含有极端主义和恐怖主义内容的网页被认为是激进化和招募心怀不满的个人的主要因素,这些人可能在国内参与恐怖主义活动,或在国外与恐怖组织并肩作战。事实上,庞大的网络数据量使得当局几乎不可能对每个网页、帖子或对话线索进行单独检查,这些网页、帖子或对话线索可能与恐怖主义有关,也可能不与恐怖主义有关,或者包含对恐怖主义的同情。由于恐怖分子存在于每个国家和每个宗教中,因此本文对现有的网络恐怖分子网页进行了回顾和系统分析。这包括现有的网络极端分子词数据库和现有的关键词网络分类器技术。基于本文的系统分析,这将是形成一个新的网络极端分子世界网络的输入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信