Differential Privacy for Power Grid Obfuscation

January 21, 2019 Β· Declared Dead Β· πŸ› IEEE Transactions on Smart Grid

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Authors Ferdinando Fioretto, Terrence W. K. Mak, Pascal Van Hentenryck arXiv ID 1901.06949 Category cs.AI: Artificial Intelligence Cross-listed cs.CE Citations 73 Venue IEEE Transactions on Smart Grid Last Checked 3 months ago
Abstract
The availability of high-fidelity energy networks brings significant value to academic and commercial research. However, such releases also raise fundamental concerns related to privacy and security as they can reveal sensitive commercial information and expose system vulnerabilities. This paper investigates how to release power networks where the parameters of transmission lines and transformers are obfuscated. It does so by using the framework of Differential Privacy (DP), that provides strong privacy guarantees and has attracted significant attention in recent years. Unfortunately, simple DP mechanisms often result in AC-infeasible networks. To address these concerns, this paper presents a novel differential privacy mechanism that guarantees AC-feasibility and largely preserves the fidelity of the obfuscated network. Experimental results also show that the obfuscation significantly reduces the potential damage of an attacker exploiting the release of the dataset.
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