基于BP神经网络的信誉欺骗检测模型  

A Cheating Detection Model for Reputation System Based on BP Neural Network

作　　者：金福生[1] 牛振东[2] 吴璠[1] 张全新[2] 

机构地区：[1]北京理工大学软件学院,北京100081 [2]北京理工大学计算机学院,北京100081

出　　处：《北京理工大学学报》2012年第1期62-66,94,共6页Transactions of Beijing Institute of Technology

基　　金：国家自然科学基金资助项目(60705022)

摘　　要：在分析信誉系统评价的目标系统的行为特征的基础上,提出了一种集成的BP神经网络模型.该模型使用训练集对构造好的BP神经网络进行训练,将测试集输入到训练好的BP神经网络中,进行欺骗检测,并在行为维度上进行欺骗检测效果验证.实验结果验证了基于BP神经网络的信誉欺骗检测模型的可行性.基于BP神经网络的欺骗检测模型能够快速、准确地实现欺骗行为的检测.Based on the analysis of behavioral characteristics of the target system,which is used to evaluate reputation system,an integrated BP neural network is proposed as the model to detect cheating characteristics for reputation system.The designed training set was used to train BP neural network,the cheating behavior could be detected by inputting test set to the trained BP neural network and the detected effect was verified on behavioral dimensions.Experiment results indicate that the proposed model is feasible and it could achieve the aim of reputation cheating detection with high speed and accuracy.

关 键 词：信誉欺骗 BP神经网络 欺骗分类 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]