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Leveraging anonymised network traces for the assessment of the potential virulence of contemporary network worm outbreaks

Leveraging anonymised network traces for the assessment of the potential virulence of contemporary network worm outbreaks

Tidy, Luc and Woodhead, Steve (2015) Leveraging anonymised network traces for the assessment of the potential virulence of contemporary network worm outbreaks. In: 2015 2nd International Conference on Communications and Network Engineering (ICCNE 2015). DESTech Publications, Inc.

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Abstract

Network worms present a persistent threat to cyber-security, with novel wormable vulnerabilities being discovered regularly. In order to assess the potential impact of a network worm outbreak that has yet to occur, both the vulnerability that is going to be exploited, as well as the number of susceptible hosts needs to be identified. Although detailed information is being catalogued and classified, issues persist in determining a representative metric for the number of susceptible hosts for a given vulnerability. This paper presents a novel analytical method of leveraging network traces for the assessment of potential network worm outbreaks, with case studies provided for three recent wormable vulnerabilities (circa. 2012-2014). The resulting metrics are then used as inputs to the Internet Worm Simulator to demonstrate the cyber-epidemiological assessment that can be provided using this method.

Item Type: Conference Proceedings
Title of Proceedings: 2015 2nd International Conference on Communications and Network Engineering (ICCNE 2015)
Additional Information: Conference held from 10th to 11th December 2015, Amsterdam, Netherlands
Uncontrolled Keywords: Network Security; Malware
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty / Department / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Faculty of Engineering & Science > Internet Security Research Laboratory
Related URLs:
Last Modified: 19 Oct 2016 08:31
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/15869

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