Network Diversity: A Security Metric for Evaluating the Resilience of Networks Against Zero-Day Attacks

• Published in: IEEE transactions on information forensics and security Vol. 11; no. 5; pp. 1071 - 1086
• Main Authors: Mengyuan Zhang, Lingyu Wang, Jajodia, Sushil, Singhal, Anoop, Albanese, Massimiliano
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.05.2016; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Biodiversity; Biological system modeling; Case studies; computer security; firewalls; Grippers; information security; intrusion detection; Measurement; Resilience; Security; Servers; Software; information security; computer security; firewalls; intrusion detection; Biodiversity
• ISSN: 1556-6013; 1556-6021
• DOI: 10.1109/TIFS.2016.2516916

Diversity has long been regarded as a security mechanism for improving the resilience of software and networks against various attacks. More recently, diversity has found new applications in cloud computing security, moving target defense, and improving the robustness of network routing. However, most existing efforts rely on intuitive and imprecise notions of diversity, and the few existing models of diversity are mostly designed for a single system running diverse software replicas or variants. At a higher abstraction level, as a global property of the entire network, diversity and its effect on security have received limited attention. In this paper, we take the first step toward formally modeling network diversity as a security metric by designing and evaluating a series of diversity metrics. In particular, we first devise a biodiversity-inspired metric based on the effective number of distinct resources. We then propose two complementary diversity metrics, based on the least and the average attacking efforts, respectively. We provide guidelines for instantiating the proposed metrics and present a case study on estimating software diversity. Finally, we evaluate the proposed metrics through simulation.