Toward Software Diversity in Heterogeneous Networked Systems

Abstract

Abstract. When there are either design or implementation flaws, a homogeneous architecture is likely to be disrupted entirely by a single attack (e.g., a worm) that exploits its vulnerability. Following the survivability through heterogeneity philosophy, we present a novel approach to improving survivability of networked systems by adopting the technique of software diversity. Specifically, we design an efficient algorithm to select and deploy a set of off-the-shelf software to hosts in a networked system, such that the number and types of vulnerabilities presented on one host would be different from that on its neighboring nodes. In this way, we are able to contain a worm in an isolated "island". This algorithm addresses software assignment problem in more complex scenarios by taking into consideration practical constraints, e.g., hosts may have diverse requirements based on different system prerequisites. We evaluate the performance of our algorithm through simulations on both simple and complex system models. The results not only confirm the effectiveness and scalability of our algorithm, but also show its capability in creating moving attack surface. The level of heterogeneity our algorithm can actually create depends on the ratio of the number of installed software to the total number of available software.

Optimal Multiculture Network Design for Maximizing Resilience in the Face of Multiple Correlated Failures

“…Another two different applications of network diversity for increasing network survivability and reliability were introduced in the contexts of cyber-security [34][35][36][37] and virus contention [38][39][40][41]. In [34,35] attack graphs and attack paths are defined as the ways an attacker can get access to a network asset.…”

“…In [39], three random-distributed techniques were developed to sub-optimally solve the NP-hard perfect coloring problem in non-exponential time. Huang et al proposed the graph multicoloring problem to minimize the number of shared software executed on neighboring nodes [40]. Should malware compromises software in one node, this would stay contained in the subgraph containing the node and the neighbors with the common vulnerability.…”

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.…”

Opportunistic Diversity-Based Detection of Injection Attacks in Web Applications

“…By solving this problem, it achieves better isolation between adjacent variants while using only a limited number of diversified applications. Finally, the software assignment problem, i.e., how to optimally assign diverse software to different hosts in a network in order to improve the network's resilience to security threats like worms, is addressed in [45] by considering practical constraints, and a similar issue is formulated and solved as a multi-objective optimization problem in [46].…”