Scalable Approach to Enhancing ICS Resilience by Network Diversity

Abstract

Network diversity has been widely recognized as an effective defense strategy to mitigate the spread of malware. Optimally diversifying network resources can improve the resilience of a network against malware propagation. This work proposes a scalable method to compute such an optimal deployment, in the context of upgrading a legacy Industrial Control System with modern IT infrastructure. Our approach can tolerate various constraints when searching for optimal diversification, such as outdated products and strict configuration policies. We explicitly measure the vulnerability similarity of products based on the CVE/NVD, to estimate the infection rate of malware between products. A Stuxnet-inspired case demonstrates our optimal diversification in practice, particularly when constrained by various requirements. We then measure the improved resilience of the diversified network in terms of a well-defined diversity metric and Meantime to compromise (MTTC), to verify the effectiveness of our approach. Finally, we show the competitive scalability of our approach in finding optimal solutions within a couple of seconds to minutes for networks of large scales (up to 10,000 hosts) and high densities (up to 240,000 edges).

Redundancy Planning for Cost Efficient Resilience to Cyber Attacks

“…The main contributions of the paper are as follows: 1) We investigate the effectiveness of redundancy to mitigate attack impacts, taking the service capacity analysis angle to redundancy and diversity. This differs from previous works on the use of diversity for security such as [2], [3], [4], which focus on identifying which parts of a system to diversify, but without considering overall performance. On the capacity analysis side, where performance modeling is common, our work differs in our focus on malicious attacks.…”

“…Diversity: Existing studies on the use of diversity to increase robustness to attacks (e.g. [2], [3], [4]) focus on optimizing network service diversity to resist attack propagation. By comparison, we determine the optimal number of (diverse) servers to be used for the services provided by a system in order to limit the impacts from attacks, with diversity arising in the different server types used for a given service.…”

Maximizing Network Reliability to 0-Day Exploits Through a Heterogeneous Node Migration Strategy

“…Common vulnerabilities in neighbor nodes allow an attacker to employ the same tool to gain control of both nodes, easing how the attacker acquires targets in the network by propagation. To avoid the exploitation of 0-day shared vulnerabilities in such fashion, works like [14], [31]- [33] propose to diversify the network resources implemented in neighbor nodes. The models and problem statements presented in the works above improved our vision on network diversity methods.…”

“…However, works like [24], [25], and the vulnerability disclosure databases [9]- [13] reveal that apparently unrelated implementations could share common risks due to code reutilization, third-party software applications, etc. In the literature, other authors have considered shared vulnerabilities, such as [14], [31]- [33], [37], [41]- [43]. Some authors take into account shared vulnerabilities assessing the number of common vulnerabilities disclosed between the available technologies.…”

“…Examples of average metrics are the average pairwise connectivity [35], [37], the average attacking effort [14], [31], and the average normalized size of the largest component [38]. On the other hand, examples of worst-case scenario metrics are the worstcase pairwise connectivity [36], the least attacking effort [14], [31], and the minimum normalized size of the largest component [38]. As observed in [38], each of the metrics taken alone in assessing reliability is incomplete; that is why in our work, we consider a joint metric that incorporates both.…”