网络节点攻击路径检测方法研究与仿真

Research and Simulation Network Node Attack Path Detection Method

对网络的节点攻击路径进行检测,可以提高网络的安全性能。由于节点攻击在选择路径时,具有较强的随机性,前后攻击无法形成关联,传统的攻击检测方法,主要是根据前一入侵路径特征对后一入侵路径进行预测检测,无法克服这种攻击特有的路径无关干扰,导致出现路径检测不准确的问题。提出采用叶贝斯推理的网络节点攻击路径检测方法。先建立网络节点攻击的操作成本与风险成本的模型,并对生成的子攻击路径进行评估,将对节点攻击路径的识别检测问题转换为对节点攻击路径选取可行性值的计算,在利用节点攻击路径图对节点攻击者的攻击意图可达性、意图实现概率、及意图可以实现最短路径进行衡量,完成对网络节点攻击路径的检测。仿真证明,改进的检测方法对网络节点攻击中的路径检测准确性较高。

Detecting the network node attack path can improve the safety performance of the network. In the paper,a network node attack path detection method Bayesian reasoning was proposed. A model of operation cost and risk cost of network node attack was established firstly,and the generated sub- attack path was evaluated. The recognition and detection problem of node attack path can be converted to the calculation of the selection feasibility value of node attack path. Then the node attack path graph was used to achieve the shortest path measurement for the attack intention,accessibility intention,and the achieving probability intention of node attacker,to complete network node attack path detection. Simulation shows that the improved detection method for path detection in network node attack has higher accuracy.