Privacy-Friendly Peer-to-Peer Energy Trading: A Game Theoretical Approach
Erdayandi, Kamil, Paudel, Amrit, Cordeiro, Lucas, Mustafa, Mustafa A.
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jan-5-2022
- Country:
- Asia
- China (0.04)
- Middle East > Republic of Türkiye (0.04)
- Europe
- Belgium > Flanders
- Flemish Brabant > Leuven (0.04)
- United Kingdom > England
- Greater Manchester > Manchester (0.04)
- Belgium > Flanders
- North America > Canada
- British Columbia (0.04)
- Asia
- Genre:
- Research Report (0.50)
- Industry:
- Energy > Power Industry (1.00)
- Information Technology > Security & Privacy (1.00)
- Technology: