Computer systems are vulnerable to both known and zero-day attacks. Although known attack patterns can be easily modeled, thus enabling the definition of suitable hardening strategies, handling zero-day vulnerabilities is inherently difficult due to their unpredictable nature. Previous research has attempted to assess the risk associated with unknown attack patterns, and a metric to quantify such risk, the k-zero-day safety metric, has been defined. However, existing algorithms for computing this metric are not scalable, and assume that complete zero-day attack graphs have been generated, which may be unfeasible in practice for large networks. In this paper, we propose a framework comprising a suite of polynomial algorithms for estimating the k-zero-day safety of possibly large networks efficiently, without pre-computing the entire attack graph. We validate our approach experimentally, and show that the proposed solution is computationally efficient and accurate.
Proceedings Title: E-Business and Telecommunications (Communications in Computer and Information Science)
Conference Dates: July 29-31, 2013
Conference Location: Reykjavik, -1
Conference Title: 10th International Conference on Security and Cryptography (SECRYPT 2013)
Pub Type: Conferences
attack graphs, vulnerability analysis, zero-day