mlsanityData to 14 Oct 2026

Privacy-Friendly Peer-to-Peer Energy Trading: A Game Theoretical Approach

arXiv 2201.01810 ↗First posted 5 Jan 2022cs.GT cs.AI cs.CRcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 4 of its 19 references that are in the map. First posted on arXiv 5 Jan 2022.

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4 of 19 references.

References · 4

  1. 2018Peer-to-Peer Energy Trading with Sustainable User Participation: A Game Theoretic Approachcited by 5
  2. 2013A Game-Theoretic Approach to Energy Trading in the Smart Gridcited by 2
  3. 2018Secure and Privacy-Friendly Local Electricity Trading and Billing in Smart Gridcited by 2
  4. 2020Privacy Preserving Distributed Energy Tradingcited by 1

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