摘要
针对传统入侵检测系统检测速度慢和误检率高的问题,将免疫原理、移动Agent技术和量子粒子群优化算法相结合,提出了基于免疫Agent和粒子群优化算法的入侵检测模型。介绍了系统模型与体系结构,并对系统性能进行仿真实验。实验结果对比表明,系统能提高传统入侵检测系统的检测速度和降低误检率。
Aiming at low detecting speed and high false positive rate of traditional intrusion detection system, immune principle, mobile Agent and quantum-behaved particle swarm optimization are combined. An intrusion detection model based on immune Agent and particle swarm optimization is proposed. System model and systematic construction are introduced, and system performance is tested. The experiment results indicate that the system can improve the low detecting speed and high false positive rate of traditional intrusion detection system.
出处
《计算机工程与应用》
CSCD
2012年第1期102-104,124,共4页
Computer Engineering and Applications
基金
江苏省高校自然科学基金(No.05KJD52006)
江苏科技大学科研资助项目(No.2005DX006J)
江苏科技大学研究生科技创新计划项目
关键词
免疫原理
移动AGENT
量子粒子群
入侵检测
immune principle mobile Agent quantum-behaved particle swarm optimization intrusion detection
