Analyzing Cascading Failures in Smart Grids under Random and Targeted Attacks

We model smart grids as complex interdependent networks, and study targeted attacks on smart grids for the first time. A smart grid consists of two networks: the power network and the communication network, interconnected by edges. Occurrence of failures (attacks) in one network triggers failures in the other network, and propagates in cascades across the networks. Such cascading failures can result in disintegration of either (or both) of the networks. Earlier works considered only random failures. In practical situations, an attacker is more likely to compromise nodes selectively. We study cascading failures in smart grids, where an attacker selectively compromises the nodes with probabilities proportional to their degrees; high degree nodes are compromised with higher probability. We mathematically analyze the sizes of the giant components of the networks under targeted attacks, and compare the results with the corresponding sizes under random attacks. We show that networks disintegrate faster for targeted attacks compared to random attacks. A targeted attack on a small fraction of high degree nodes disintegrates one or both of the networks, whereas both the networks contain giant components for random attack on the same fraction of nodes.Comment: Accepted for publication in 28th IEEE International Conference on Advanced Information Networking and Applications (AINA) 201

Strategic Investment in Protection in Networked Systems

We study the incentives that agents have to invest in costly protection against cascading failures in networked systems. Applications include vaccination, computer security and airport security. Agents are connected through a network and can fail either intrinsically or as a result of the failure of a subset of their neighbors. We characterize the equilibrium based on an agent's failure probability and derive conditions under which equilibrium strategies are monotone in degree (i.e. in how connected an agent is on the network). We show that different kinds of applications (e.g. vaccination, malware, airport/EU security) lead to very different equilibrium patterns of investments in protection, with important welfare and risk implications. Our equilibrium concept is flexible enough to allow for comparative statics in terms of network properties and we show that it is also robust to the introduction of global externalities (e.g. price feedback, congestion).Comment: 32 pages, 3 figure