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

Mengyuan Zhang, Lingyu Wang, Sushil Jajodia, Anoop Singhal, Massimiliano Albanese

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

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.
Original languageEnglish
Article number7378495
Pages (from-to)1071-1086
JournalIEEE Transactions on Information Forensics and Security
Volume11
Issue number5
DOIs
Publication statusPublished - 1 May 2016
Externally publishedYes

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