Privacy-Friendly Peer-to-Peer Energy Trading: A Game Theoretical Approach
This addresses privacy concerns for participants in decentralized energy markets, offering an incremental improvement over existing schemes by integrating encryption with competitive pricing.
The paper tackles the problem of privacy in peer-to-peer energy trading by proposing a decentralized platform (PFET) that uses homomorphic encryption and game theory to protect sensitive user data, achieving efficient privacy preservation as demonstrated through analysis and evaluation.
In this paper, we propose a decentralized, privacy-friendly energy trading platform (PFET) based on game theoretical approach - specifically Stackelberg competition. Unlike existing trading schemes, PFET provides a competitive market in which prices and demands are determined based on competition, and computations are performed in a decentralized manner which does not rely on trusted third parties. It uses homomorphic encryption cryptosystem to encrypt sensitive information of buyers and sellers such as sellers$'$ prices and buyers$'$ demands. Buyers calculate total demand on particular seller using an encrypted data and sensitive buyer profile data is hidden from sellers. Hence, privacy of both sellers and buyers is preserved. Through privacy analysis and performance evaluation, we show that PFET preserves users$'$ privacy in an efficient manner.