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Proceedings Paper

Bio-inspired diversity for increasing attacker workload
Author(s): Stephen Kuhn
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Paper Abstract

Much of the traffic in modern computer networks is conducted between clients and servers, rather than client-toclient. As a result, servers represent a high-value target for collection and analysis of network traffic. As they reside at a single network location (i.e. IP/MAC address) for long periods of time. Servers present a static target for surveillance, and a unique opportunity to observe the network traffic. Although servers present a heightened value for attackers, the security community as a whole has shifted more towards protecting clients in recent years leaving a gap in coverage. In addition, servers typically remain active on networks for years, potentially decades. This paper builds on previous work that demonstrated a proof of concept leveraging existing technology for increasing attacker workload. Here we present our clean slate approach to increasing attacker workload through a novel hypervisor and micro-kernel, utilizing next generation virtualization technology to create synthetic diversity of the server's presence including the hardware components.

Paper Details

Date Published: 28 May 2014
PDF: 7 pages
Proc. SPIE 9119, Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII, 91190I (28 May 2014); doi: 10.1117/12.2058682
Show Author Affiliations
Stephen Kuhn, Dartmouth College (United States)

Published in SPIE Proceedings Vol. 9119:
Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII
Misty Blowers; Jonathan Williams, Editor(s)

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