Privacy-Preserving Obfuscation of Critical Infrastructure Networks

Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Main track. Pages 1086-1092.

https://doi.org/10.24963/ijcai.2019/152

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Abstract

The paper studies how to release data about a critical infrastructure network (e.g., a power network or a transportation network) without disclosing sensitive information that can be exploited by malevolent agents, while preserving the realism of the network. It proposes a novel obfuscation mechanism that combines several privacy-preserving building blocks with a bi-level optimization model to significantly improve accuracy. The obfuscation is evaluated for both realism and privacy properties on real energy and transportation networks. Experimental results show the obfuscation mechanism substantially reduces the potential damage of an attack exploiting the released data to harm the real network.

Keywords

  • Constraints and SAT: Constraints: Applications
  • Multidisciplinary Topics and Applications: Security and Privacy
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