Int. J. of Collaborative Intelligence   »   2016 Vol.1, No.4

 

 

Title: Insights from terrorism intelligence and eradication efforts - Al-Qaeda, ISIS, Boko Haram - for more pragmatic botnet countermeasures

 

Authors: Emmanuel C. Ogu; Michael I. Ogu; Chiemela Ogu

 

Addresses:
Department of Computer Science, School of Computing and Engineering Sciences, Babcock University, Ilishan-Remo, Ogun State, Nigeria
Department of Political Science and Public Administration, Veronica Adeleke School of Social Sciences, Babcock University, Ilishan-Remo, Ogun State, Nigeria
Department of Computer Science, School of Computing and Engineering Sciences, Babcock University, Ilishan-Remo, Ogun State, Nigeria

 

Abstract: Bots are fast becoming the infamous insurgents lurking around network infrastructures and the internet, with arguably at least one of such compromised machines sitting in homes and offices around the world. These malicious network tenants have shown similar resilience to such real-life terrorist networks as ISIS, Al-Qaeda, Boko Haram, and other armed conflict groups. This paper discusses perspectives, and provides insights into how Botnets are not very different from real-life terrorist networks, and why similar efforts to those which have been used to laudably impair and destabilise terrorist networks globally can equally be applied towards ridding network infrastructures and the internet of these malignant insurgents (especially those of the order of sophistication of Conficker). A review of existing literature juxtaposed with verifiable facts put together from an interpretivist and analytical standpoint, form the crux of the methodology that is used in investigating the cardinal discourse of this study.

 

Keywords: insurgency; terrorism; cyber-terrorism; terrorist networks; armed conflict; cyber-threats; information security; intrusion; terrorism intelligence; botnets; network security.

 

DOI: 10.1504/IJCI.2016.10004907

 

Int. J. of Collaborative Intelligence, 2016 Vol.1, No.4, pp.258 - 274

 

Submission date: 28 Sep 2016
Date of acceptance: 29 Nov 2016
Available online: 02 May 2017

 

 

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