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P2P环境下的文件污染问题威胁着系统的安全性和可用性,甚至可能导致系统消亡.当前的信誉机制和基于文件特征等防污染方案存在未考虑多种用户共享行为、难以获得大量原始数据和版本发布初期恶意欺骗等问题.本文首次发现用户共享习惯差异性、用户特别长时间保留个别文件等多种用户共享行为,并分析其对防污染方案的影响.提出了基于多种用户共享行为的防污染模型,减弱了多种用户共享行为干扰和版本发布初期恶意欺骗等问题.设计了结构化P2P网络下低开销的实现机制,自动收集大量用户共享文件信息,解决了难以获取大量原始数据的问题.文中还给出了系统参数配置方案.基于真实系统运行日志的模拟实验证明该方案能够准确、快速地区分出虚假文件,降低虚假文件下载次数,保证接近100%的真实文件下载比例,有效抵抗文件污染的攻击.
The file pollution in P2P environment threatens the security and usability of the system and may even cause the system to die.The current reputation mechanism and file-based anti-pollution schemes do not take into account a variety of user-sharing behavior, it is difficult to obtain a large amount of original data and versions Publishing the first malicious fraud and other issues.This paper first found that the user sharing habits differences, the user especially for a long time to retain individual files and other user-sharing behavior and analysis of its impact on anti-pollution program.A variety of user sharing based on the proposed anti- Pollution model to reduce the variety of user-sharing behavior interference and malicious version of the initial version of the issue of fraud.Designed to implement a structured P2P network low overhead mechanism to automatically collect a large number of users to share file information to solve the problem of difficult access to large amounts of raw data The system parameters configuration is also given in this paper.A simulation experiment based on the real system running log shows that this scheme can distinguish the fake files accurately and quickly, reduce the number of fake files to download, guarantee the real file download ratio close to 100%, effectively resist File pollution attack.