A Blockchain-Based Trust Model for Uploading Illegal Data Identification

被引:2
|
作者
Cheng, Jieren [1 ,2 ]
Li, Yuanshen [2 ,3 ]
Yuan, Yuming [4 ]
Zhang, Bo [4 ]
Xu, Xinbin [2 ,3 ]
机构
[1] Hainan Univ, Sch Comp Sci & Technol, Haikou 570228, Hainan, Peoples R China
[2] Hainan Univ, Hainan Blockchain Technol Engn Res Ctr, Haikou 570228, Hainan, Peoples R China
[3] Hainan Univ, Sch Cyberspace Secur Acad, Cryptog Acad, Haikou 570228, Hainan, Peoples R China
[4] Hainan Huochain Tech Co Ltd, Haikou 570100, Hainan, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 19期
基金
中国国家自然科学基金; 海南省自然科学基金;
关键词
blockchain; trust model; smart contract; blockchain security;
D O I
10.3390/app12199657
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Malicious users can upload illegal data to the blockchain to spread it, resulting in serious threats due to the tamper-proof characteristics of the blockchain. However, the existing methods for uploading illegal data identification cannot select trust nodes and ensure the credibility of the identification results, leading to a decrease in the credibility of the methods. To solve the problem, this paper proposes a blockchain-based trust model for uploading illegal data identification. The trust model mainly has the following two core modules: Reputation-based random selection algorithm (RBRSA) and incentive mechanism. By assigning reputation attributes to nodes, the proposed RBRSA will select nodes according to reputation values. RBRSA favors the nodes with high reputation value to ensure the randomness and credibility of the identification nodes. The incentive mechanism is designed to ensure the credibility of the identification results through the credibility analysis of the model based on game theory and Nash equilibrium. Identification nodes that identify illegal data correctly will obtain incentives. In order to obtain a higher income, the identification nodes must identify illegal data correctly. Credibility analysis and comparative experiments show that the probability of selecting credible nodes by RBRSA is up to 23% higher than the random selection algorithm. The probability of selecting the nodes with a reputation value of 20 by RBRSA is 27% lower than the random selection algorithm; that is, the probability that RBRSA selects untrusted nodes is lower. Therefore, the nodes selected by RBRSA have superior credibility compared with other methods. In terms of the effect of the incentive mechanism, the incentive mechanism can encourage nodes to identify data credibly and improve the credibility of identification results. All in all, the trusted model has higher credibility than other methods.
引用
收藏
页数:18
相关论文
共 50 条
  • [1] A Blockchain-Based Trust Model for Supporting Collaborative Healthcare Data Management
    Jeon J.
    Kim J.
    Shin M.
    Kim M.
    [J]. Computer Systems Science and Engineering, 2023, 46 (03): : 3403 - 3421
  • [2] A New Blockchain-Based trust management model
    Masmoudi, Mariam
    Zayani, Corinne Amel
    Amous, Ikram
    Sedes, Florence
    [J]. KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KSE 2021), 2021, 192 : 1081 - 1091
  • [3] A Blockchain-based trust model for crowd environments
    Mo Nguyen
    Yu, Jian
    Tung Nguyen
    [J]. PROCEEDINGS OF THE AUSTRALASIAN COMPUTER SCIENCE WEEK MULTICONFERENCE (ACSW 2020), 2020,
  • [4] Trust Modeling for Blockchain-based Wearable Data Market
    Chowdhury, Mohammad Jabed Morshed
    Ferdous, Md Sadek
    Biswas, Kamanashis
    Chowdhury, Niaz
    Kayes, A. S. M.
    Watters, Paul
    Ng, Alex
    [J]. 11TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE (CLOUDCOM 2019), 2019, : 411 - 417
  • [5] Trust in blockchain-based systems
    Becker, Moritz
    Bodo, Balazs
    [J]. INTERNET POLICY REVIEW, 2021, 10 (02):
  • [6] A Quantifiable Trust Model for Blockchain-based Identity Management
    Gruener, Andreas
    Muehle, Alexander
    Gayvoronskaya, Tatiana
    Meinel, Christoph
    [J]. IEEE 2018 INTERNATIONAL CONGRESS ON CYBERMATICS / 2018 IEEE CONFERENCES ON INTERNET OF THINGS, GREEN COMPUTING AND COMMUNICATIONS, CYBER, PHYSICAL AND SOCIAL COMPUTING, SMART DATA, BLOCKCHAIN, COMPUTER AND INFORMATION TECHNOLOGY, 2018, : 1475 - 1482
  • [7] Blockchain-based service recommendation and trust enhancement model
    Wang, Chao
    Chen, Shizhan
    Xing, Meng
    Wu, Hongyue
    Feng, Zhiyong
    [J]. KNOWLEDGE-BASED SYSTEMS, 2024, 294
  • [8] COBATS: A Novel Consortium Blockchain-Based Trust Model for Data Sharing in Vehicular Networks
    Fan, Qi
    Xin, Yang
    Jia, Bin
    Zhang, Yang
    Wang, Pinxiang
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (11) : 12255 - 12271
  • [9] Blockchain-Based Privacy Preserving Trust Management Model in VANET
    Liang, Ruochen
    Li, Bohan
    Song, Xinyang
    [J]. ADVANCED DATA MINING AND APPLICATIONS, 2020, 12447 : 465 - 479
  • [10] Blockchain-based Zero Trust on the Edge
    Bicer, Cem
    Murturi, Ilir
    Donta, Praveen Kumar
    Dustdar, Schahram
    [J]. 2023 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE, CSCI 2023, 2023, : 1006 - 1013