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The V-Network testbed for malware analysis

The V-Network testbed for malware analysis

Ahmad, Mmuhammad, Woodhead, Steve and Gan, Diane (2017) The V-Network testbed for malware analysis. In: 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). IEEE, pp. 629-635. ISBN 978-1-4673-9546-5 (doi:10.1109/ICACCCT.2016.7831716)

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Abstract

This paper presents a virtualised network environment that serves as a stable and re-usable platform for the analysis of malware propagation. The platform, which has been developed using VMware virtualisation technology, enables the use of either a graphical user interface or scripts to create virtual networks, clone, restart and take snapshots of virtual machines, reset experiments, clean virtual machines and manage the entire infrastructure remotely. The virtualised environment uses open source routing software to support the deployment of intrusion detection systems and other malware attack sensors, and is therefore suitable for evaluating countermeasure systems before deployment on live networks. An empirical analysis of network worm propagation has been conducted using worm outbreak experiments on Class A size networks to demonstrate the capability of the developed platform.

Item Type: Conference Proceedings
Title of Proceedings: 2016 International Conference on Advanced Communication Control and Computing Technologies (ICACCCT)
Additional Information: Conference held from 25 May - 27 May 2016, Syed Ammal Engineering College, Ramanathapuram, India
Uncontrolled Keywords: Malware analysis; testbed; virtualisation
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Computing & Information Systems
Faculty of Engineering & Science
Faculty of Engineering & Science > Department of Engineering Science
Related URLs:
Last Modified: 14 Nov 2017 09:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/15871

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