基于智能化自学习方式的入侵检测防护系统设计与实现

摘要

随着网络结构日益复杂，网络攻击手段多样化，传统的防火墙已无法阻止多种类型的网络攻击。基于智能化自学习方式的入侵检测防护系统将防火墙与入侵检测系统集成为一体，符合NDIS接口规范。系统采用智能化自学习的方式来维护“黑名单”特征库，使防火墙具有自适应的特点，能够阻断未知入侵行为。系统具有快速稳定的防护效果，能够实时响应入侵行为，并提供危机预警的反馈机制。%With the growth of network structure complexity and the diversity of network attack methods, traditional ifrewalls have been unable to prevent many types of network attack. According to NDIS interface standard, intrusion detection protection system based on intelligent self learning method(IDPS-ISM) is developed, which has the advantages of ifrewall and intrusion detection system(IDS) combined. In order to realize a self-adaptive ifrewall to block unpredictable attack behaviors, method of intelligent self learning is used to maintain the"blacklist"of IDPS-ISM. The actual facts show that IDPS-ISM is fast and stable, and promises great real-time response. Besides, the system also has warning mechanism to against crisis.