Bio-inspired diversity for increasing attacker workload

Stephen Kuhn

doi:10.1117/12.2058682

28 May 2014 Bio-inspired diversity for increasing attacker workload

Stephen Kuhn

Proceedings Volume 9119, Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII; 91190I (2014) https://doi.org/10.1117/12.2058682
Event: SPIE Sensing Technology + Applications, 2014, Baltimore, MD, United States

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.

Citation Download Citation

Stephen Kuhn "Bio-inspired diversity for increasing attacker workload", Proc. SPIE 9119, Machine Intelligence and Bio-inspired Computation: Theory and Applications VIII, 91190I (28 May 2014); https://doi.org/10.1117/12.2058682

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KEYWORDS

Operating systems

Biomimetics

Interfaces

Network security

Computer intrusion detection

Surveillance

Computing systems

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