基于攻防混沌度边界预警机制的网络安全存储算法研究

考虑到当前网络安全存储算法普遍存在的防御策略集收敛性不足,抗攻击性能差的难题,提出了一种基于攻防混沌度边界预警机制的网络安全存储算法。根据网络供给侧进行混沌度边界建模(网络供给侧-需求侧边界预警模型),提高安全边界对攻击集合的匹配程度,增强防御资源的合理利用;随后,基于防御资源需要动态攻击集合的问题,引入马尔科夫边界攻击者集合收敛机制,实现对最高强度-次高强度攻击行为的两次预警,有效提升网络安全防御的纳什均衡解,进一步降低了防御成本,从而提高了网络的安全存储性能。仿真实验表明,相比于当前网络安全存储领域使用较广的峰值强度映射过滤算法(Peak Intensity Mapping Filtering Algorithm,PIMF算法)、超线性纳什维度均衡策略算法(Superlinear Nash-Dimension Equilibrium Strategy Algorithm,ND-SES算法),本文算法在资源受限条件下能够实现混沌度高级别预警,降低防御成本,改善了误比特率及丢包率性能,具有更高的抗攻击峰值带宽及二次冗余带宽性能。

THE RESEARCH NETWORK SECURITY STORAGE ALGORITHM BASED ON BORDER WARNING MECHANISM OF ATTACK & DEFENSE CHAOS DEGREE

In order to solve the problems of insufficient convergence of defense strategy set, poor degree of chaos effect, a network security storage algorithm based on early warning mechanism of attack-defense chaos boundary is proposed. In order to improve the matching degree of security boundaries to attack sets and enhance the rational utilization of defense resources, chaos degree boundary modeling (network supply-demand side boundary early warning model) is carried out on the network supply side. Then, based on the problem that defense resources need dynamic attacking sets, the convergence of Markov amplitude boundaries attacker sets is introduced. The mechanism realizes two early warnings of the highest intensity-sub-high intensity attacks, greatly improves the Nash equilibrium solution of network security defense, further reduces the defense cost, and improves the network security storage performance. Compared with Peak Intensity Mapping Filtering Algorithm and Superlinear Nash-Dimension Equilibrium Strategy Algorithm, simulation results show that this algorithm can achieve high-level early warning of chaos under resource constraints, reduce defense costs, and improve the effectiveness of anti-attack.The performance of BER and packet loss rate is improved, and the performance of anti-attack peak bandwidth and quadratic redundancy bandwidth is significantly higher than that of the control group.