REACT: reactive resilience for critical infrastructures using graph-coloring techniques. (1st November 2019)

• Record Type: Journal Article
• Authors: Marsa-Maestre, Ivan; Gimenez-Guzman, Jose Manuel; Orden, David; de la Hoz, Enrique; Klein, Mark
• Is Part Of: Journal of network and computer applications. Volume 145(2019)
• Publication Date: 2019-11-01
• Subjects: Network security -- Network theory (graphs) -- Optimization -- Simulated annealing; Microcomputers -- Periodicals; Computer networks -- Periodicals; Application software -- Periodicals; Micro-ordinateurs -- Périodiques; Réseaux d'ordinateurs -- Périodiques; Logiciels d'application -- Périodiques; Application software; Computer networks; Microcomputers; Periodicals; 004.05; 004
• DOI: 10.1016/j.jnca.2019.07.003
• Languages: English
• ISSNs: 1084-8045

Abstract

Abstract: Nowadays society is more and more dependent on critical infrastructures. Critical network infrastructures (CNI) are communication networks whose disruption can create a severe impact. In this paper we propose REACT, a distributed framework for reactive network resilience, which allows networks to reconfigure themselves in the event of a security incidents so that the risk of further damage is mitigated. Our framework takes advantage of a risk model based on multilayer networks, as well as a graph-coloring problem conversion, to identify new, more resilient configurations for networks in the event of an attack. We propose two different solution approaches, and evaluate them from two different perspectives, with a number of centralized optimization techniques. Experiments show that our approaches outperform the reference approaches in terms of risk mitigation and performance. Highlights: Risk reduction against zero-day attacks is an important issue in current society. Multi-layer graphs are useful to capture multiple network security related aspects. Reactive network redeployment is related to the graph coloring problem. We propose two techniques to redeploy the network upon a security incident Simulations show significant risk reduction when applying the proposed techniques.