网络群体对抗综合评判模型定性化研究

Comprehensive evaluation model of network group countermeasure qualitative research

通过对网络群体攻击和防御的分析,定义了网络群体对抗的指标权重,同时提出了疫苗的克隆攻击评判策略和抗体的剪枝防御评判策略,指出对亲和力高于1的网元进行克隆攻击具有很高的攻击成功率,应将其赋予高优先级的网络攻击体系计算范围;而当网元的抗体浓度低于零时,应将其剪枝隔离,不再将其纳入评判网络防御效果的防御体系计算范围内。在此基础上建立了网络群体攻防对抗的免疫和神经网络综合评判模型,对其进行了定性化研究,为网络的群体攻防对抗仿真研究奠定了基础,并根据该模型设计了网络群体对抗评判系统,对其进行了相关分析。

Through the analysis of the network attacks and defense, this paper gave the target-weights definition of the network group countermeasure, and modeled the simulation model of network countermeasure based on the theories of neural networks and immunity. Proposed the evaluation tactics of the vaccine＇ cloning attack and the antibody＇ pruning defense from the mod- el. pointed out the phenomenon that the network element, whose affinity was higher than one, would have high success rate of cloning attacks. It should be taken into evaluation scope of network attack effects. When antibody concentration was lower than zero, the network elements should be pruned isolation avoids being incorporated into evaluation of network defense effect. Comprehensive evaluation and qualitative research of network group countermeasure were been given by using immunity and neural networks. These had been laid the foundation for the evaluation research of network group countermeasure. According to the mode, designed the network group countermeasure evaluation system and gave its related analysis.