Privacy-Preserving Data Aggregation for Smart Meters under a Mixed Adversary Model

Konferenz: PESS 2025 - IEEE Power and Energy Student Summit
08.10.2025-10.10.2025 in Munich, Germany

doi:10.30420/566656010

Tagungsband: PESS 2025 – IEEE Power and Energy Student Summit,

Seiten: 6Sprache: EnglischTyp: PDF

Autoren:
Popanda, Jan; Nitz, Lasse; Mandal, Avikarsha; Decker, Stefan

Inhalt:
Smart meters are increasingly deployed in modern power systems to enable fine-grained monitoring, demand response, and efficient grid management. While smart meters benefit both utilities and consumers, the fine-grained insights they provide into household behavior raise significant privacy concerns. To mitigate these risks, we introduce a protocol for privacy-preserving aggregation of high-resolution usage data across multiple smart meters. In particular, we seek to use the smart meters themselves to aggregate data rather than making them available to a central authority. At the same time, our protocol accounts for unresponsive or malicious smart meters, introducing mechanisms for exception handling and detecting anomalous reports while preserving competitive performance.