Malware propagation in smart grid networks: metrics, simulation and comparison of three malware types

Abstract

Smart grids utilize communication technologies that make them vulnerable to cyber attacks. The power grid is a critical infrastructure that constitutes a tempting target for sophisticated and well-equipped attackers. In this paper we simulate three malware types capable of attacking smart grid networks in the ns3 simulation environment. First, an aggressive malware type, named the pandemic malware, follows a topological-scan strategy to find and infect all devices on the network in the shortest time possible, via a brute force approach. Next, the more intelligent endemic malware sacrifices speed for stealthiness and operates with a less conspicuous hit-list and permutation-scan strategy. Finally, a highly stealthy malware type called the contagion malware does not scan the network or initiate any connections but rather appends on legitimate communication flows. We define several metrics to express the infection speed, scanning efficiency, stealthiness, and complexity of malware and use those metrics to compare the three malware types. Our simulations provide details on the scanning and propagation behavior of different malware classes. Furthermore, this work allows the assessment of the detectability of different malware types.