Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (11): 335-344.doi: 10.11896/jsjkx.220300138

• Information Security • Previous Articles     Next Articles

Privacy-preserving Scheme of Energy Trading Data Based on Consortium Blockchain

SHI Kun1, ZHOU Yong1, ZHANG Qi-liang2, JIANG Shun-rong1   

  1. 1 College of Computer Science and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China
    2 XcmgHanyun Technologies Co.,Ltd.,Xuzhou,Jiangsu 221001,China
  • Received:2022-03-14 Revised:2022-06-07 Online:2022-11-15 Published:2022-11-03
  • About author:SHI Kun,born in 1996,postgraduate,is a member of China Computer Federation.His main research interests include blockchain and data security.
    JIANG Shun-rong,born in 1986,Ph.D,associate professor,is a member of China Computer Federation.His main research interests include Internet of vehicles,cloud computing,blockchain and data security.
  • Supported by:
    Fundamental Research Funds for the Central Universities of Ministry of Education of China(2020ZDPY0306)and Xuzhou Science and Technology Program(KC21044).

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Abstract: Blockchain technology could effectively solve the problems of lack of trust,malicious tampering and false transactions.However,the open and transparent characteristics of the blockchain make the distributed energy trading model based on the blockchain extremely vulnerable to be attacked,leading to the disclosure of user’s privacy.Therefore,a privacy-preserving scheme BLDP-AM based on differential privacy algorithm and account mapping technology is proposed to protect the privacy information of trading data.Our scheme redesigns the data perturbation mechanism of the local differential privacy algorithm to make it applicable to blockchain technology,and constructs the BLDP algorithm based on this perturbation mechanism to protect the privacy of transaction data.At the same time,in order to ensure the correctness of trading and hide the characteristics of the trading curve,our scheme first associates users with multiple accounts through account mapping technology,then uses the exponential smoo-thing prediction algorithm to calculate the trading prediction value of each account,and finally uses the BLDP algorithm to perturb the trading prediction value to obtain the real trading value and conduct trading.Our scheme not only guarantee the correctness of transactions but also achieve the purpose of protecting the privacy of trading data.The privacy analysis proves the feasibility of the scheme in protecting user privacy,and the experimental analysis shows that the scheme has better performance.

Key words: Energy trading systerm, Blockchain, Local differential privacy, Account mapping, Exponential smoothing prediction

CLC Number: 

  • TP399
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