网络攻击方案评估系统设计与仿真

从攻击者角度出发提出一个基于RBF神经网络的网络攻击方案评估系统用于网络安全态势分析.提出涵盖了攻击方案中所涉及的攻防双方特性的评估指标体系,利用模糊层次分析法对指标数据进行模糊综合处理,采用RBF神经网络对攻击方案的效能进行推理,使系统具备自学习的能力,实现对整体攻击方案对受攻击的网络的影响程度的预测.仿真实验结果表明,系统能较客观地反映网络攻击方案针对不同防护能力目标所产生的危害,为推理分析出攻击者可能采取的攻击思路和手段提供参考.

Network attack scenarios evaluation system design and simulation

To analyze network security situation,a network attack scenarios evaluation system based on RBF neural network is proposed from the perspective of an attacker.The system is based on a set of valuation index system which involves both offensive and defensive characteristics.Using fuzzy algorithm to integrate the index data,the input parameters of RBF neural network are generated.Ultimately the result of the overall attack scenario can be predicted.Simulation results show that the system can reflect the network attack protection capabilities for different objectives of the program,and a useful reference is provided for targeted network security defense.