DS证据理论下融合隐式与显式特征的共谋攻击识别推理模型

Collusion Attack Identification Reasoning Model Fusing Implicit and Explicit Features Under DS Evidence Theory

现有的攻击识别模型大多未能较好地解决共谋攻击对电子商务信任评价机制产生的威胁。为此,结合国内C2C电子商务的特点,以共谋攻击中的商品为识别对象,融合隐式和显式用户行为特征以及与交易和买家相关的复合特征,并根据DS证据理论处理不确定问题的优点,提出一种DS证据理论下的共谋攻击识别推理模型。在某电商平台真实共谋攻击数据上的实验结果表明,该推理模型能够识别共谋攻击,提取的攻击识别特征可反映用户真实行为,有效区分攻击和合法交易所涉及的商品。

Collusion attack produced a serious threat to e-commerce trust evaluation mechanism and the existing attack detection model is not able to solve the problem well, combined with the characteristics of domestic C2 C e-commerce,this paper uses the goods in collusion attack as the object of detection,f uses explicit and implicit user behavior feature and summary feature of related transactions and buyers,combining the advantages of DS evidence theory in dealing with uncertain problems,puts forward the collusion attack detection model under DS evidence theory. Experimental results based on the real collusion attacks data in e-commerce show that the proposed reasoning model can effectively identify the collusion attack,the extracted attacks can effectively reflect the user＇s real behavior, effectively distinguish between the goods involved in attacks and legitimate transactions.