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一种基于人工免疫理论的蠕虫检测模型

发表时间:2009-10-31  浏览量:1595  下载量:710
全部作者: 陈文,李涛,梁刚,赵奎
作者单位: 四川大学计算机学院
摘 要: 指出了传统蠕虫检测技术在检测未知蠕虫和系统健壮性方面的不足,介绍了利用人工免疫系统进行蠕虫检测在自适应和资源整合方面的优势。基于人工免疫理论,将计算机网络映射为免疫网络,利用免疫机制提高蠕虫检测的自适应能力。网络中的检测节点基于抗体对抗原的识别原理,进行蠕虫特征码扫描、进程行为监测以及进程状态监测。蠕虫检测过程分为检测器抗体初始训练和动态检测两个阶段。动态检测过程中,各检测节点既独立执行动态蠕虫检测,又相互配合,有机地协同防范蠕虫入侵,以此建立了基于人工免疫机制的蠕虫检测模型,该模型具有自适应性、健壮性、自治性等特点。
关 键 词: 计算机应用;蠕虫检测;人工免疫;网络安全
Title: A worm detection model based on artificial immune theory
Author: CHEN Wen, LI Tao, LIANG Gang, ZHAO Kui
Organization: College of Computer Science, Sichuan University
Abstract: This paper points out the deficiency in detecting the unknown worms and system robustness of the traditional worm detection technologies, and then introduces the advantages of using artificial immune system in self-adaptability aspect and resource integrating. Based on artificial immune theory, the paper maps the computer network into immune network, and improves the self-adaptive capacity of worm detection with its immune mechanism. The detection nodes in the immune network carry out worm signature scanning, process activity monitors and process state inspection based on the principle of antibody recognize antigen. The detection process includes two phases, namely the initial training of antibody and the dynamic immune detection of worms, and in the dynamic immune detection phase, each node is independent while all the nodes cooperate with each other to defense the intrusion of worms. Based on these, a worm detection model based on artificial immunity mechanism is set up with adaptability, robustness and autonomy.
Key words: computer application; worm detection; artificial immune; network security
发表期数: 2009年10月第20期
引用格式: 陈文,李涛,梁刚,等. 一种基于人工免疫理论的蠕虫检测模型[J]. 中国科技论文在线精品论文,2009,2(20):2114-2119.
 
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