增强交易因素影响的P2P网络信任评估模型研究

doi:10.3969/j.issn.1000-0801.2013.10.015

摘要/Abstract

摘要：

在交易评估机制中，信任度由多种因素构成，但由于各个因素自身的特点，其影响和作用大小不一。通过采用适当的关联关系，增强某些重要交易因素的影响和作用，可以有效地提高评估模型的准确率和有效性。由此提出一种增强交易因素影响的P2P网络信任评估模型，给出了新的信任评估计算方法和仿真实验。实验结果表明，该评估模型效果显著。

关键词: 对等网络, 信任度, 增强, 交易因素

Abstract:

In the transaction evaluation mechanism,trust is formed by many kinds of factors,but due to the characteristics of its own,its effects and influences are different.By using the relationship between appropriate,it enhances the effects of some important factors and the role of trade.That can effectively improve the accuracy and validity of the evaluation model.A model of enhancing the factors' effects based on the trust evaluation for P2P network was proposed,a new calculation method of the trust evaluation,and the model's simulation results were given.The experimental results show that the evaluation model has significant effect.

Key words: peer-to-peer network, trust,enhancing, trading factor

张祖昶,王诚. 增强交易因素影响的P2P网络信任评估模型研究[J]. 电信科学, 2013, 29(10): 88-91.

Zuchang Zhang,Cheng Wang. Research on a Model of Enhancing Factors' Effects Based on Trust Evaluation for P2P Network[J]. Telecommunications Science, 2013, 29(10): 88-91.

图/表 2

参考文献 15

1	Lua E K , Crowcroft J . A survey and comparison of peer-to-peer overlay network schemes. IEEE Communications Survey and Tutorial, 2004（3）: 1～22
2	Asnar Y , Zannone N . Perceived risk assessment. Proceedings of the 4th ACM Workshop on Quality of Protection（QoP'08）, New York,USA, 2008: 59～63
3	Singh A , Lilja D . Improving risk assessment methodology:a statistical design of experiments approach. Proceedings of the 2nd International Conference on Security of Information and Networks（SIN'09）, New York,USA, 2009: 21～29
4	Costa C , Soares V , Almeida J ,et al. Fighting pollution dissemination in peer-to-peer networks. Proceedings of ACM Symposium on Applied Computing, Seoul, ACM Press, 2007: 1586～1590
5	Wang X F . On the policy description and quantification model for trust management. National University of Defense Technology 2009
6	Xiong L , Liu L . Peer trust:supporting reputation-based trust for peer-to-peer electronic communities. IEEE Transactions on Knowledge and Data Engineering, 2004,16（7）: 843～857
7	Beth T , Borcherding M , Klein B . Valuation of trust in open network. Proceedings of European Symposium on Research in Security, Springer-Verlag, Brighton, 1994
8	Wang Y , Vassileva J . Bayesian network trust model in peer-to-peer networks. Proceedings of the 2nd Int'l Workshop on Agents and Peer-to-Peer Computing, Springer-Verlag, Berlin, 2004:23～34
9	常俊胜，王怀民，尹刚 . 一种P2P系统中基于时间帧的动态信任模型. 计算机学报， 2006,8（29）: 1301～1307
10	Huang C L , Hu H P , Wang Z Y . Modeling time-related trust. Proceedings of the 3rd International Conference on Grid and Cooperative Computing, Wuhan,China, 2004:382～389
11	Wang Y , Lin F . Trust and risk evaluation of transactions with different amounts in peer-to-peer e-commerce environments. Proceedings of IEEE International Conference on eBusiness Engineering（ICEBE'06）, Shanghai,China, 2006:102～109
12	王勇，云晓春，李奕飞 . 对等网络拓扑测量与特征分析实例. 软件学报， 2008,19（4）: 981～992
13	韩正平，蔡凤娟 . 网络安全信息关联分析技术研究与应用. 计算机应用研究， 2006,23（10）: 93～100
14	李景涛，荆一楠 . 基于相似度加权推荐的P2P 环境下的信任模型. 软件学报， 2007,18（1）: 157～167
15	孟宪福，张磊，王旭 . P2P 电子商务信任模型研究. 计算机应用研究， 2009,26（8）: 3067～3069

权值			次数
权值	G=300	G=600	G=900G=1 200	G=1 500	G=1 800
μ=0.9 λ=0.1	7.73%	78.33%	78.23%78.03%	78.13%	8.33%
λ=0.3,μ=0.7	79.33%	80.13%	80.63%81.13%	81.53%	81.43%
λ=0.5,μ=0.5	79.63%	80.53%	80.73%81.23%	81.83%	81.93%
λ=0.7,μ=0.3	78.43%	79.73%	79.47%79.93%	80.33%	80.43%
λ=0.9,μ=0.1	77.23%	78.43%	78.53%78.33%	78.73%	78.93%

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