A recurrent problem currently affecting network reliability is the simultaneous exploitation of 0-day vulnerabilities shared between several node implementations across the network. When such 0-day vulnerabilities are exploited, large portions of the network may get compromised as a result. In this work, we propose a network node migration strategy to minimize the impact of 0-day attacks on network reliability. The migration method proposes replacing homogeneous node implementations with diverse alternatives to yield a heterogeneous network. The migration method allocates heterogeneous nodes within the network by minimizing the product between the average and the maximum number of network partitions, which may emerge after the simultaneous exploitation of 0-day risks on shared network resources. As we show, our migration strategy maximizes network connectivity in the event of a simultaneous 0-day attack. Our work's significant findings are the following: First, increasing the heterogeneity in node technologies reduces the attacker's ability to break down the entire network. Second, given a set of available network technologies that partially share risks, a network design implemented using several heterogeneous technologies sharing a small number of 0-day risks is more reliable than one with a small number of technologies whose 0-day risks are disjoint. Third, we observed that in a node-heterogeneous network topology, clustering nodes by technology improves network reliability.INDEX TERMS Network diversity, network reliability, 0-day vulnerabilities, connected components.

No abstract

Current data networks are highly homogeneous because of management, economic, and interoperability reasons. This technological homogeneity introduces shared risks, where correlated failures may entirely disrupt the network operation and impair multiple nodes. In this paper, we tackle the problem of improving the resilience of homogeneous networks, which are affected by correlated node failures, through optimal multiculture network design. Correlated failures regarded here are modeled by SRNG events. We propose three sequential optimization problems for maximizing the network resilience by selecting as different node technologies, which do not share risks, and placing such nodes in a given topology. Results show that in the 75% of real-world network topologies analyzed here, our optimal multiculture design yields networks whose probability that a pair of nodes, chosen at random, are connected is 1, i.e., its ATTR metric is 1. To do so, our method efficiently trades off the network heterogeneity, the number of nodes per technology, and their clustered location in the network. In the remaining 25% of the topologies, whose average node degree was less than 2, such probability was at least 0.7867. This means that both multiculture design and topology connectivity are necessary to achieve network resilience.

No abstract

No abstract