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Title: Realtime Robustification of Interdependent Networks under Cascading Attacks
This paper studies the problem of robustifying an interdependent network by rewiring a small number of links in realtime during a cascading attack. Interdependent networks have been widely used to model interconnected complex systems such as a critical infrastructure network including both the power grid and the Internet. Realtime robustification of interdependent networks, therefore, has significant practical importance. This paper formulates the problem using the Markov decision process (MDP) framework. We first show the problem is NP-hard and then develop an effective and efficient greedy algorithm, named R EAL W IRE , to robustify the network in realtime. R EAL W IRE scores each link (and each node) based on the expected number of links failures resulted from the failure of the link (or the node), and rewires the links greedily according to the scores. Extensive experimental results show that R EAL W IRE outperforms other algorithms on multiple trobustness metrics.
Authors:
; ;
Award ID(s):
1651203 1715385 1947135
Publication Date:
NSF-PAR ID:
10099225
Journal Name:
2018 IEEE International Conference on Big Data (Big Data)
Page Range or eLocation-ID:
1347 to 1356
Sponsoring Org:
National Science Foundation
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