CCN中基于节点状态模型的缓存污染攻击检测算法

Detection algorithm for cache pollution attacks based on node state model in content centric networking

针对内容中心网络中的缓存污染攻击问题,以污染内容数量、分布状态和攻击强度3个参数对缓存污染攻击进行定量描述和分析,建立了攻击下的节点缓存状态模型。通过分析节点关键参数的变化,提出了基于节点状态模型的攻击检测原则,并分别以单位时间缓存替换率和请求达到率为观测参数进行算法实例化设计。仿真结果与性能分析表明,所提检测算法在应对分散式攻击与集中式攻击时,可以取得良好的检测性能。

Aiming at cache pollution attacks in content centric networking, the attacks were quantitatively described by three parameters, namely number of pollution contents, distribution of attack requests and attack intensity, then the cache state model of node under attack was built. Benefited from the analysis of key parameters of cache node, the attack detection principle based on node state model was put forward, correspondingly, two attack detection algorithms were instantiated with the observation parameters of cache replacement ratio and request arrival rate. The simulation results show that proposed algorithm can obtain good detection performance under each decentralized attack and centralized attack.