Dynamic, Privacy-Preserving Decentralized Reputation Systems

被引:23
|
作者
Clark, Michael R. [1 ,2 ]
Stewart, Kyle [1 ]
Hopkinson, Kenneth M. [1 ]
机构
[1] Air Force Inst Technol, Wright Patterson AFB, OH 45433 USA
[2] Tenet 3 LLC, Wright Patterson AFB, OH 45433 USA
关键词
Reputation systems; cryptography; multiparty computation; mobile ad-hoc networks;
D O I
10.1109/TMC.2016.2635645
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reputation systems provide an important basis for judging whether to interact with others in a networked system. Designing such systems is especially interesting in decentralized environments such as mobile ad-hoc networks, as there is no trusted authority to manage reputation feedback information. Such systems also come with significant privacy concerns, further complicating the issue. Researchers have proposed privacy-preserving decentralized reputation systems (PDRS) which ensure individual reputation information is not leaked. Instead, aggregate information is exposed. Unfortunately, in existing PDRS, when a party leaves the network, all of the reputation information they possess about other parties in the network leaves too. This is a significant problem when applying such systems to the kind of dynamic networks we see in mobile computing. In this article, we introduce dynamic, privacy-preserving reputation systems (Dyn-PDRS) to solve the problem. We enumerate the features that a reputation system must support in order to be considered a Dyn-PDRS. Furthermore, we present protocols to enable these features and describe how our protocols are composed to form a Dyn-PDRS. We present simulations of our ideas to understand how a Dyn-PDRS impacts information availability in the network, and report on an implementation of our protocols, including timing experiments.
引用
收藏
页码:2506 / 2517
页数:12
相关论文
共 50 条
  • [41] Privacy-Preserving Decentralized Optimization Using Homomorphic Encryption
    Huo, Xiang
    Liu, Mingxi
    IFAC PAPERSONLINE, 2020, 53 (05): : 630 - 633
  • [42] PriParkRec: Privacy-Preserving Decentralized Parking Recommendation Service
    Li, Zengpeng
    Alazab, Mamoun
    Garg, Sahil
    Hossain, M. Shamim
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2021, 70 (05) : 4037 - 4050
  • [43] Nym Credentials: Privacy-Preserving Decentralized Identity with Blockchains
    Halpin, Harry
    2020 CRYPTO VALLEY CONFERENCE ON BLOCKCHAIN TECHNOLOGY (CVCBT 2020), 2020, : 56 - 67
  • [44] Privacy-preserving Decentralized Learning Framework for Healthcare System
    Kasyap, Harsh
    Tripathy, Somanath
    ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 2021, 17 (02)
  • [45] Flexible and Privacy-preserving Framework for Decentralized Collaborative Learning
    Ma, Zhuoran
    Ma, Jianfeng
    Miao, Yinbin
    Liu, Ximeng
    Zheng, Wei
    Li, Xiang
    2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2020,
  • [46] Privacy-Preserving Personalized Decentralized Learning With Fast Convergence
    Qiao, Jing
    Xie, Zhenzhen
    Zheng, Zhigao
    Zhang, Xiao
    Zhang, Zhenyu
    Zhang, Qun
    Yu, Dongxiao
    IEEE TRANSACTIONS ON CONSUMER ELECTRONICS, 2024, 70 (04) : 6618 - 6629
  • [47] Decentralized Graph Neural Network for Privacy-Preserving Recommendation
    Zheng, Xiaolin
    Wang, Zhongyu
    Chen, Chaochao
    Qian, Jiashu
    Yang, Yao
    PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, 2023, : 3494 - 3504
  • [48] TripleBlind: A Privacy-Preserving Framework for Decentralized Data and Algorithms
    Gharibi, Gharib
    Gilkalaye, Babak Poorebrahim
    Patel, Ravi
    Rademacher, Andrew
    Wagner, David
    Fay, Jack
    Moore, Gary
    Penrod, Steve
    Storm, Greg
    Das, Riddhiman
    NEURIPS 2021 COMPETITIONS AND DEMONSTRATIONS TRACK, VOL 176, 2021, 176 : 343 - 348
  • [49] Privacy-preserving decentralized learning methods for biomedical applications
    Tajabadi, Mohammad
    Martin, Roman
    Heider, Dominik
    COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL, 2024, 23 : 3281 - 3287
  • [50] PRIVACY-PRESERVING DISTRIBUTED PRECODER DESIGN FOR DECENTRALIZED ESTIMATION
    Venkategowda, Naveen K. D.
    Werner, Stefan
    2018 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP 2018), 2018, : 1311 - 1315