PriChain: Efficient Privacy-Preserving Fine-Grained Redactable Blockchains in Decentralized Settings

被引:0
|
作者
Guo, Hongchen [1 ]
Gan, Weilin [2 ]
Zhao, Mingyang [2 ]
Zhang, Chuan [2 ]
Wu, Tong [3 ]
Zhu, Liehuang [2 ]
Xue, Jingfeng [1 ]
机构
[1] Beijing Inst Technol, Sch Comp Sci Technol, Beijing 100081, Peoples R China
[2] Beijing Inst Technol, Sch Cyberspace Sci & Technol, Beijing 100081, Peoples R China
[3] Univ Sci & Technol Beijing, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
基金
中国博士后科学基金; 国家重点研发计划; 中国国家自然科学基金;
关键词
Resistance; Access control; Data privacy; Dictionaries; Blockchains; Encryption; Complexity theory; Usability; Protection; Blockchain; Fine-grained redaction; Privilege downward compatibility; Privacy preservation;
D O I
10.23919/cje.2023.00.305
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Recently, redactable blockchain has been proposed and leveraged in a wide range of real systems for its unique properties of decentralization, traceability, and transparency while ensuring controllable on-chain data redaction. However, the development of redactable blockchain is now obstructed by three limitations, which are data privacy breaches, high communication overhead, and low searching efficiency, respectively. In this paper, we propose PriChain, the first efficient privacy-preserving fine-grained redactable blockchain in decentralized settings. PriChain provides data owners with rights to control who can read and redact on-chain data while maintaining downward compatibility, ensuring the one who can redact will be able to read. Specifically, inspired by the concept of multi-authority attribute-based encryption, we utilize the isomorphism of the access control tree, realizing fine-grained redaction mechanism, downward compatibility, and collusion resistance. With the newly designed structure, PriChain can realize O(n) communication and storage overhead compared to prior O (n(2)) schemes. Furthermore, we integrate multiple access trees into a tree-based dictionary, optimizing searching efficiency. Theoretical analysis proves that PriChain is secure against the chosen-plaintext attack and has competitive complexity. The experimental evaluations show that PriChain realizes 10 x efficiency improvement of searching and 100 x lower communication and storage overhead on average compared with existing schemes.
引用
收藏
页码:82 / 97
页数:16
相关论文
共 50 条
  • [41] Toward Vehicular Digital Forensics From Decentralized Trust: An Accountable, Privacy-Preserving, and Secure Realization
    Li, Ming
    Weng, Jian
    Liu, Jia-Nan
    Lin, Xiaodong
    Obimbo, Charlie
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (09) : 7009 - 7024
  • [42] Privacy-Preserving Combined Heat and Power Dispatch Based on Information Masking Mechanism: A Decentralized Perspective
    Zhao, Leilei
    Xue, Yixun
    Du, Yuan
    Chang, Xinyue
    Li, Zening
    Su, Jia
    Sun, Hongbin
    IEEE TRANSACTIONS ON SMART GRID, 2024, 15 (05) : 4550 - 4563
  • [43] A fog architecture for privacy-preserving data provenance using blockchains
    Lautert, Filipe
    Pigatto, Daniel F.
    Gomes-Jr, Luiz
    2020 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2020, : 1112 - 1117
  • [44] Privacy-Preserving and Reliable Decentralized Federated Learning
    Gao, Yuanyuan
    Zhang, Lei
    Wang, Lulu
    Choo, Kim-Kwang Raymond
    Zhang, Rui
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2023, 16 (04) : 2879 - 2891
  • [45] Towards trustworthy and privacy-preserving decentralized auctions
    Tiphaine Henry
    Julien Hatin
    Eloi Besnard
    Nassim Laga
    Walid Gaaloul
    Journal of Banking and Financial Technology, 2024, 8 (1): : 45 - 63
  • [46] A Decentralized Privacy-Preserving Healthcare Blockchain for IoT
    Dwivedi, Ashutosh Dhar
    Srivastava, Gautam
    Dhar, Shalini
    Singh, Rajani
    SENSORS, 2019, 19 (02)
  • [47] ADMM Based Privacy-Preserving Decentralized Optimization
    Zhang, Chunlei
    Ahmad, Muaz
    Wang, Yongqiang
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2019, 14 (03) : 565 - 580
  • [48] Privacy-preserving Decentralized Federated Deep Learning
    Zhu, Xudong
    Li, Hui
    PROCEEDINGS OF ACM TURING AWARD CELEBRATION CONFERENCE, ACM TURC 2021, 2021, : 33 - 38
  • [49] GAIN: Decentralized Privacy-Preserving Federated Learning
    Jiang, Changsong
    Xu, Chunxiang
    Cao, Chenchen
    Chen, Kefei
    JOURNAL OF INFORMATION SECURITY AND APPLICATIONS, 2023, 78
  • [50] SPDL: A Blockchain-Enabled Secure and Privacy-Preserving Decentralized Learning System
    Xu, Minghui
    Zou, Zongrui
    Cheng, Ye
    Hu, Qin
    Yu, Dongxiao
    Cheng, Xiuzhen
    IEEE TRANSACTIONS ON COMPUTERS, 2023, 72 (02) : 548 - 558