Smart-blacklisting:P2P文件共享系统假块污染攻击对抗方法

在当前十分流行的P2P文件共享网络中,假块污染攻击严重地干扰了正常的文件下载过程。提出了基于概率统计及多轮筛选的对抗假块污染攻击策略——Smart-blacklisting,从理论上证明了该策略的有效性。仿真实验结果表明,该策略可以保证目标文件成功下载并降低假块污染攻击对下载时间及带宽消耗的影响。当攻击强度为0.2时,下载时间仅为eMule系统黑名单方法的13%,在带宽消耗方面也仅为其50%。

Smart-blacklisting: an efficient methodology for mitigating fake block attack in P2P file-sharing systems

Fake block attack intends to prolong the downloading time by providing fake data to make the file block fail in the hash check.P2P file-sharing systems are susceptible to fake block attacks,whereby malicious clients are able to make a big impact on users’ downloading experience.An efficient methodology named Smart-blacklisting,which aims to lessen the downloading time and bandwidth wastes interfered by the attack was proposed through using a mathematic model,and the efficiency of this method was analyzed during a simulation experiment.The ovel approach presents 87% downloading time and 50% bandwidth wastes compare less than those of eMule blacklisting method.