LPPAC: Lightweight privacy-preserving distributed payments with access control

被引:0
|
作者
Zeng, Bo [1 ]
Wu, Tian [2 ]
Yu, Fangchao [1 ]
Yang, Geying [1 ]
Zhao, Kai [1 ]
Wang, Lina [1 ]
机构
[1] Wuhan Univ, Sch Cyber Sci & Engn, Key Lab Aerosp Informat Secur & Trusted Comp, Minist Educ, Wuhan 430072, Peoples R China
[2] Nanchang Univ, Digital Literacy & Skills Enhancement Res Ctr, Jiangxi Prov Philosophy & Social Sci Key Res Base, Nanchang 330031, Peoples R China
基金
中国国家自然科学基金;
关键词
Distributed payments; Blockchain; Privacy preserving; Auditability; Access control;
D O I
10.1016/j.comnet.2024.110936
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The privacy-preserving distributed payment system leverages the advantages of its decentralized form while upholding data privacy. Currently, numerous solutions effectively safeguard users' privacy, encompassing transaction amounts and identities, but in practical deployments, these solutions may impose limitations due to their indiscriminate treatments. Recognizing that real-world transactions involve not only the exchange of funds but also the transfer of assets, we introduce a lightweight privacy-preserving distributed payment scheme called LPPAC, which differentiates its treatment of different levels of private data. The transformation of amounts, which directly involves monetary values, is rigorously protected using appropriate encryption techniques. Additionally, we incorporate transaction pruning techniques to reduce storage overhead and enhance operational efficiency. In the context of asset transfers, there maybe instances where parties other than the transacting entities need to be informed to make adequate preparations. However, the information related to asset transfers is inherently linked to transaction amounts. Therefore, we introduce an access control mechanism to allocate corresponding access rights. Through this approach, we theoretically establish that LPPAC can offer a precise privacy protection solution without compromising privacy. Furthermore, experimental results show the strong performance of LPPAC in practical applications.
引用
收藏
页数:13
相关论文
共 50 条
  • [41] Privacy-Preserving Decentralized Access Control for Cloud Storage Systems
    Chen, Jianwei
    Ma, Huadong
    2014 IEEE 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING (CLOUD), 2014, : 507 - 514
  • [42] Privacy-Preserving Attribute Distribution Mechanism for Access Control in a Grid
    Park, Sang M.
    Chung, Soon M.
    ICTAI: 2009 21ST INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, 2009, : 308 - 313
  • [43] A Lightweight Privacy-Preserving Authentication Protocol for VANETs
    Li, Xiong
    Liu, Tian
    Obaidat, Mohammad S.
    Wu, Fan
    Vijayakumar, Pandi
    Kumar, Neeraj
    IEEE SYSTEMS JOURNAL, 2020, 14 (03): : 3547 - 3557
  • [44] Privacy-preserving distributed collaborative filtering
    Boutet, Antoine
    Frey, Davide
    Guerraoui, Rachid
    Jegou, Arnaud
    Kermarrec, Anne-Marie
    COMPUTING, 2016, 98 (08) : 827 - 846
  • [45] Distributed privacy-preserving policy reconciliation
    Meyer, Ulrike
    Wetzel, Susanne
    Ioannidis, Sotiris
    2007 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, VOLS 1-14, 2007, : 1342 - +
  • [46] Towards Distributed Privacy-Preserving Prediction
    Lyu, Lingjuan
    Law, Yee Wei
    Ng, Kee Siong
    Xue, Shibei
    Zhao, Jun
    Yang, Mengmeng
    Liu, Lei
    2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2020, : 4179 - 4184
  • [47] Privacy-Preserving Distributed Stream Monitoring
    Friedman, Arik
    Sharfman, Izchak
    Keren, Daniel
    Schuster, Assaf
    21ST ANNUAL NETWORK AND DISTRIBUTED SYSTEM SECURITY SYMPOSIUM (NDSS 2014), 2014,
  • [48] Privacy-Preserving Distributed Graph Filtering
    Li, Qiongxiu
    Coutino, Mario
    Leus, Geert
    Christensen, Mads Grxsboll
    28TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO 2020), 2021, : 2155 - 2159
  • [49] Privacy-preserving distributed collaborative filtering
    Antoine Boutet
    Davide Frey
    Rachid Guerraoui
    Arnaud Jégou
    Anne-Marie Kermarrec
    Computing, 2016, 98 : 827 - 846
  • [50] Privacy-Preserving Distributed Kalman Filtering
    Moradi, Ashkan
    Venkategowda, Naveen K. D.
    Talebi, Sayed Pouria
    Werner, Stefan
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2022, 70 : 3074 - 3089