基于社会网络和证据理论的信任计算模型

Jie Jiang, Junhui Xiang, Hua Zhou, Xiaolin Zheng, Tianyang Dong
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引用次数: 4

摘要

为了解决电子商务中恶意用户带来的信任问题,提出了一种基于社交网络的信任计算模型。通过对信任特征的分析,将社会网络引入到信任模型中,根据信任的主观性和组合性特征,从最可信的来源获取信息,以改善电子交易中买方信息不对称的状况。鉴于证据理论可以很好地整合相互冲突的证据的优势,我们解决了各推荐第三方的信息冲突。我们还介绍了其他各种信任影响因素,如交易评级字典、交易背景重要因素、交易金额因素和交易时间因素等。最后,通过仿真实验,根据不同的交易环境设置不同的置信度因子,验证了结合社会网络和证据理论获得合理推荐信任值的方法是可行的。结果表明,基于社交网络的信任计算模型具有较好的抗攻击能力。
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Trust Calculation Model Based on Social Network and Evidence Theory
To solve the trust issue caused by malicious users in e-commerce, we propose a trust calculation model based on social network. Through analysing the trust features, social network is introduced into this trust model to get information from the most trusted source according to the subjectivity and the compositionality feature of trust to improve the buyers' situation of asymmetric information in electronic trading. In view of the advantage that conflicted evidences can be well combined by evidence theory, we resolve the conflict of information from each recommended third-party. We also introduce other various trust influence factors, such as transaction rating dictionary, transaction background important factor, transaction amount factor and trading time factor, etc. Finally, through simulation experiments, we set different confidence factors depending on different trading environment, and verify that the method to combine social network and evidence theory for obtaining a reasonable recommendation trust value is feasible. It proves that our proposed trust calculation model based on social network has a better anti-attack ability.
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