网络在线交易动态信任计算模型与信誉管理机制

当前,在C2C网上拍卖交易领域,各种各样的恶意行为层出不穷,信任缺失信誉欺诈现象非常突出,因此,如何建立有效的信任机制已成为亟待解决的问题.在分析现有网络信任交易机制局限性的基础上,针对网络交易信任问题的动态性、匿名性、虚拟性等特点,提出一种基于多Agent系统的网络交易动态信任计算模型与信誉系统.模型包括3部分:第一部分为用户时域的信任度,旨在着重近期历史信誉状况对现期信任度的影响,激励用户采取一致的合作策略;第二部分是对信誉反馈评分的加权平均计算,权重部分主要引入了信誉反馈评分人的信任度(反馈评分的可信性)、交易价值(防止"信誉榨取")、时间折现("防范信誉波动")等因素;第三部分为社区贡献加权,旨在根据某一时域内,一用户对社区其他成员所采取的行为情况,增加或减少此时该用户的信任值,达到孤立信誉反馈提交、惩治欺诈行为的目的.建立了事前开展防范、事中进行协调、事后给予惩罚三位一体的欺诈约束机制,保障网络在线交易的安全性.理论分析和实验验证表明该机制能有效解决三方面问题:解决难以防范投机用户小额积誉、大宗榨取的问题;有效防止会员通过虚假交易或伪造身份进行欺诈;降低网络交易平台仲裁的工作量.

Dynamic trust calculation model and credit management mechanism of online trading

At present, all kinds of malicious acts appear in C2C online auctions, particularly the phenomenon of trust lack and credit fraud is very outstanding. Therefore, how to build all effective trust model has becolne a burning problem. Based oil analyzing limitations of the existing online trust transaction mechanism, and according to characteristics （such as dynamic, innominate and suppositional） of online transaction trust problem, the article proposes a dynamic trust calculation model and reputation management mechanism of online trading based on multi-Agent system. The model consists of three parts. The frst part is the trust of user domain, to put importance on the influence on current trust by recent credibility status, to motivate users to adopt a agreed cooperative strategy. The second part is the weighted average of reputation feedback score. The weighted part mainly considers the trust from the reputation feedback score person （tile credibility of the feedback score）, the value of the transaction （to prevent the ＂credit squeeze＂）, temporal discounted （＂guard against the fluctuations of the credibility＂ ） and other factors. Tile third part is to give a weighting on the community contribution, according to the action taken by a user to the other members of the cormnunity in a time domain, to increase or decrease the user＇s trust to isolate the feedback submission of the credibility and punish the fraud. The paper builds the fraud limiting mechanism which combine the prevention beforehand, coordination in the event and punishment afterwards. The mechanism makes the online transaction safe. Theoretic proof and experimental verification indicate the following three problems can be solved effectively： 1） solving the problem which is difficult to prevent and is that speculative user accumulates the little trusts and squeeze on the large trading; 2） preventing members from cheating by false trading or personation; 3） reducing the arbitration workload of the online business platfor