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

Published

January 12, 2016

Author(s)

Meng Zhang, Lingyu Wang, Sushil Jajodia, Anoop Singhal, M. Albanese

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 (MTD), 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 towards formally modeling network diversity as a security metric by designing and evaluating a series of diversity metrics. Specifically, 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.

Citation

IEEE Transactions on Information Forensics and Security

Volume

11

Issue

5

Pub Type

Journals

Download Paper

https://doi.org/10.1109/TIFS.2016.2516916

Local Download

Keywords

Security Metrics, Diversity, Network Security, Zero Day Attack, Network Resilience

Citation

Zhang, M. , Wang, L. , Jajodia, S. , Singhal, A. and Albanese, M. (2016), Network Diversity: A Security Metric for Evaluating the Resilience of Networks Against Zero Day Attacks, IEEE Transactions on Information Forensics and Security, [online], https://doi.org/10.1109/TIFS.2016.2516916, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=918869 (Accessed December 3, 2024)