• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Jin Yu, Gu Zhimin, and Ban Zhijie. A New Reputation Management Mechanism Based on Bi-Ratings in Peer-to-Peer Systems[J]. Journal of Computer Research and Development, 2008, 45(6).
Citation: Jin Yu, Gu Zhimin, and Ban Zhijie. A New Reputation Management Mechanism Based on Bi-Ratings in Peer-to-Peer Systems[J]. Journal of Computer Research and Development, 2008, 45(6).

A New Reputation Management Mechanism Based on Bi-Ratings in Peer-to-Peer Systems

More Information
  • Published Date: June 14, 2008
  • The efficiency of reputation system depends on the quality of feedbacks. However current reputation models in peer-to-peer systems can not process such strategic feedbacks as collusive ratings or no ratings attacks. Also there is unfairness for the blameless peers in these models. Pointing to these problems, a new reputation management mechanism is proposed. In this mechanism there are two metrics used to evaluate peers: feedback and service trust. Service trust shows the service reliability of peers. Feedback trust can reflect credibility of peers when reporting ratings. After a transaction both service consumer and provider submit ratings to report the quality of this transaction. According to these two ratings, service trust of sever and feedback trust of consumer are separately updated, furthermore the former is closely related to the latter. Complementary to the reputation model, a punishment mechanism is proposed to prevent malicious peers from iteratively exerting bad behaviors or not submitting ratings. Although both the partners are punished when two ratings disagree with each other, only the service trust of provider may be decreased but its feedback trust keeps constant. Likewise, feedback trust of reporter will be decreased while its service trust does not change. Simulation shows that the proposed approach can effectively resist aforesaid malicious attacks and mitigate unfairness.
  • Related Articles

    [1]Shi Leyi, Zhu Hongqiang, Liu Yihao, Liu Jia. Intrusion Detection of Industrial Control System Based on Correlation Information Entropy and CNN-BiLSTM[J]. Journal of Computer Research and Development, 2019, 56(11): 2330-2338. DOI: 10.7544/issn1000-1239.2019.20190376
    [2]Yao Sheng, Xu Feng, Zhao Peng, Ji Xia. Intuitionistic Fuzzy Entropy Feature Selection Algorithm Based on Adaptive Neighborhood Space Rough Set Model[J]. Journal of Computer Research and Development, 2018, 55(4): 802-814. DOI: 10.7544/issn1000-1239.2018.20160919
    [3]Dong Hongbin, Teng Xuyang, Yang Xue. Feature Selection Based on the Measurement of Correlation Information Entropy[J]. Journal of Computer Research and Development, 2016, 53(8): 1684-1695. DOI: 10.7544/issn1000-1239.2016.20160172
    [4]Tang Chenghua, Liu Pengcheng, Tang Shensheng, Xie Yi. Anomaly Intrusion Behavior Detection Based on Fuzzy Clustering and Features Selection[J]. Journal of Computer Research and Development, 2015, 52(3): 718-728. DOI: 10.7544/issn1000-1239.2015.20130601
    [5]Zhang Fengbin and Wang Tianbo. Real Value Negative Selection Algorithm with the n-Dimensional Chaotic Map[J]. Journal of Computer Research and Development, 2013, 50(7): 1387-1398.
    [6]Zhang Zhenhai, Li Shining, Li Zhigang, and Chen Hao. Multi-Label Feature Selection Algorithm Based on Information Entropy[J]. Journal of Computer Research and Development, 2013, 50(6): 1177-1184.
    [7]Zheng Liming, Zou Peng, Han Weihong, Li Aiping, Jia Yan. Traffic Anomaly Detection Using Multi-Dimensional Entropy Classification in Backbone Network[J]. Journal of Computer Research and Development, 2012, 49(9): 1972-1981.
    [8]Zhang Xiang, Deng Zhaohong, Wang Shitong, Choi Kupsze. Maximum Entropy Relief Feature Weighting[J]. Journal of Computer Research and Development, 2011, 48(6): 1038-1048.
    [9]Chen Shitao, Chen Guolong, Guo Wenzhong, and Liu Yanhua. Feature Selection of the Intrusion Detection Data Based on Particle Swarm Optimization and Neighborhood Reduction[J]. Journal of Computer Research and Development, 2010, 47(7): 1261-1267.
    [10]Hou Jian, Peng Jiayin, Zhang Yuzhuo, Zhang Chengyi. A Reverse Triple I Algorithm for Fuzzy Reasoning Based on Maximum Fuzzy Entropy Principle[J]. Journal of Computer Research and Development, 2006, 43(7): 1180-1185.

Catalog

    Article views (480) PDF downloads (622) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return