papers AI Learner
The Github is limit! Click to go to the new site.

Privacy-Preserving Obfuscation of Critical Infrastructure Networks

2019-05-23
Ferdinando Fioretto, Terrence W.K. Mak, Pascal Van Hentenryck

Abstract

The paper studies how to release data about a critical infrastructure network (e.g., the 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.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1905.09778

PDF

http://arxiv.org/pdf/1905.09778


Similar Posts

Comments