An Evidential Clustering Based Framework for Cyber Terrorist Cells Topology Identification

Firas Saidi, Zouheir Trabelsi, Henda Ben Ghazela

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Nowadays, social networks media are heavily used by cyber terrorist organizations to exchange information, and manage their malicious activities. Effective approaches to understand cyber terrorist organizations structures, working strategies, and operation tactics are required to develop security solutions to prevent their activities. Usually, a terrorist organization includes several sub-groups sharing common proprieties. However, the subgroups may differ in their degree of activities and roles. Hence, understating the topology of a terrorist organization and its operations methods is important to develop efficient prevention solutions. In this paper, we discuss the foundation of an approach for detecting cyber terrorist subgroups, as well as its evaluation and efficiency using data on cyber terrorist groups. The approach is based on an evidential clustering method. In fact, objects (known also as network members) within a cyber terrorist group can be classified into various sub-classes, such as military, finance and local leaders committees. Belief functions are used to describe the membership of nodes to clusters (sub-communities). The efficiency of the proposed approach is demonstrated through a set of clustering results, regarding the classification of cyber terrorist actors and the allocation of the appropriate degree to each member of a given class. Experimental results show the efficiency and the accuracy of our CECM based approach not only in classifying cyber terrorist actors into the aforementioned communities, but also in allocating a degree of membership for each member to each sub-class.

Original languageEnglish
Title of host publicationProceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages436-443
Number of pages8
ISBN (Print)9781538643877
DOIs
Publication statusPublished - Sep 5 2018
Event17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018 - New York, United States
Duration: Jul 31 2018Aug 3 2018

Publication series

NameProceedings - 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018

Other

Other17th IEEE International Conference on Trust, Security and Privacy in Computing and Communications and 12th IEEE International Conference on Big Data Science and Engineering, Trustcom/BigDataSE 2018
Country/TerritoryUnited States
CityNew York
Period7/31/188/3/18

Keywords

  • CECM
  • Cyber Community detection
  • Cyber security
  • Cyber terrorism
  • ECM

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

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