摘要： 提出一种网格计算环境下基于免疫进化计算的分布式入侵检测方法，应用免疫进化计算、定义生成检测器方法和基因库进化学习方法提高分布式入侵检测的主动性和自适应性。利用网格安全环境实现系统的负载均衡，提高系统的并行处理能力。仿真实验结果证明了该方法的有效性，与基于人工免疫的入侵检测方法相比，误检率降低了0.37%，在确保检测率的同时提高了并行处理能力，降低了处理 时延。

关键词: 网格计算, 免疫进化计算, 入侵检测, 人工免疫系统

Abstract: This paper proposes a distributed intrusion detection method based on immune evolution computing in grid computing environments. Immune evolution computing and method of generating detector and gene base are used to improve initiative and self-adaptive of distributed intrusion detection system. Grid security environment is used to realize load balancing and improve parallel processing ability. The effectiveness is proved by experiments. Comparing with intrusion detection method based on artificial immune, false detection rate is reduced by 0.37%, parallel processing ability is improved and processing delay is reduced while assuring detection rate.

Key words: grid computing, immune evolution computing, intrusion detection, artificial immune system

中图分类号: 

• TP309.2