Differential Privacy for Power Grid Obfuscation
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jan 2019.
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Citing papers per year: 2021: 2; 2022: 2; 2023: 1.
5 papers.
- 2022Differential Privacy and Fairness in Decisions and Learning Tasks: A Surveycited by 47
- 2022Post-processing of Differentially Private Data: A Fairness Perspectivecited by 9
- 2021Complex-valued Federated Learning with Differential Privacy and MRI Applicationscited by 5
- 2023Differentially Private Algorithms for Synthetic Power System Datasetscited by 1
- 2021Realistic Differentially-Private Transmission Power Flow Data Releasecited by 0
- 2023Differentially Private Algorithms for Synthetic Power System Datasets20 Mar 2023
- 2022Differential Privacy and Fairness in Decisions and Learning Tasks: A Survey16 Feb 2022
- 2022Post-processing of Differentially Private Data: A Fairness Perspective24 Jan 2022
- 2021Complex-valued Federated Learning with Differential Privacy and MRI Applications7 Oct 2021
- 2021Realistic Differentially-Private Transmission Power Flow Data Release25 Mar 2021