云环境中基于遗传算法的入侵检测系统设计

发布时间：2018-05-01 00:13

本文选题：遗传算法 + 云环境　；参考：《北京邮电大学》2014年硕士论文

【摘要】：由于防火墙防护功能的局限性,入侵检测系统(IDS)作为防火墙之后的第二道安全保障措施,能够处理防火墙不能及时处理的安全问题(DDOS攻击、SYN泛洪等)。但是入侵检测技术仍然有很多缺点,例如误报率、漏报率过高,检测效率过低等。为了解决这个问题,入侵检测系统被融合了新技术和新方法,尤其是引入了其他领域的一些概念和方法,最典型的就是将人工智能算法应用于入侵检测系统中。另一方面随着云的广泛应用,云中的安全问题愈发的引人注目,云中的入侵检测系统的设计和实现也备受关注。在本文中,我们提出了云环境中基于遗传算法的入侵检测模型,将一种协同进化遗传算法(Co-evolutionary Genetic Algorithm)应用于入侵检测系统中。本文首先对该算法的主要流程进行了改进,添加了一些组件(分代收集、碰撞等),提高了算法的性能；同时将改进后的算法应用到入侵检测系统中,完成了算法重点步骤的研究和设计,主要包括编码表、适应度函数和遗传算子的设计。在此基础上,提出了一种适用于云环境中的基于协同进化遗传算法的入侵检测系统模型和架构,该体系结构分为三层：第一层是终端服务器；第二层是子服务器；第三层是节点嗅探器。三层架构协同合作改进云环境中入侵检测系统的性能。实验证明,遗传算法可以提高入侵检测系统的检测率。
[Abstract]:Because of the limitation of firewall protection function, intrusion Detection system (IDS), as the second security measure behind firewall, can deal with the security problems which cannot be dealt with in time by DDOS attacks, such as SYN flooding. However, intrusion detection technology still has many shortcomings, such as false alarm rate, high false alarm rate, low detection efficiency and so on. In order to solve this problem, intrusion detection system (IDS) is integrated with new technologies and methods, especially some concepts and methods in other fields are introduced. The most typical one is to apply artificial intelligence algorithm to intrusion detection system (IDS). On the other hand, with the wide application of cloud, the security problem in cloud becomes more and more attractive, and the design and implementation of intrusion detection system in cloud is paid more and more attention. In this paper, we propose a genetic algorithm-based intrusion detection model in cloud environments, and apply a co-evolutionary genetic algorithm, Co-Evolutionary Genetic algorithm, to intrusion detection systems. In this paper, the main process of the algorithm is improved, and some components (generation collection, collision, etc.) are added to improve the performance of the algorithm, meanwhile, the improved algorithm is applied to the intrusion detection system. The key steps of the algorithm are studied and designed, including coding table, fitness function and genetic operator. On this basis, an intrusion detection system model and architecture based on co-evolution genetic algorithm in cloud environment is proposed. The architecture is divided into three layers: the first layer is terminal server, the second layer is sub-server; The third layer is the node sniffer. The three-tier architecture collaborates to improve the performance of intrusion detection systems in cloud environments. Experiments show that genetic algorithm can improve the detection rate of intrusion detection system.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TP393.08

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