基于多核构架的高速实时网络风险评估模型

High-speed model of real-time risk evaluation based on multi-processor

针对复杂高速网络环境风险评估面临的性能瓶颈以及实时准确性低的问题,提出了多核构架的网络风险评估模型。该模型利用多核网络处理平台资源,提出了高速并行处理网络流量构架和实时入侵检测均衡算法。同时以人工免疫为基础,模拟了人体记忆细胞对外部抗原的免疫过程,采用克隆选择算法增扩抗体浓度,为实时风险评估提供理论依据。理论分析和仿真实验结果表明,该模型能够定量实时评估高速网络环境风险,能够保证处理性能和评估准确性。

To solve an emerging need for improving the performance of risk evaluation for network security at high-speed network, ahigh-speed model of real-time risk evaluation based on multi-processor is proposed, and a load-balancing algorithm for intrusion detection is proposed to improve detection ability of intrusion detection. The model makes use of multi-processor network platform resources, and establishes a high-speed parallel processing of network traffic structure. This model is also based on immune theory as the theoretical basis, by simulating the immune cells of the external antigen recognition, clone selection, changes of antibody concentration to carry out risk assessment. Theoretical analysis and simulation results prove the model can evaluate the risk assessment for high-speed network and ensure the efficiency and the accuracy.