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网络安全类产品的入侵检测方法主流的特征检测和异常检测均存在着如序列数据处理能力缺乏、规则库及时更新等问题,而智能算法由于运行效率问题无法在高速网络中实时检测。本文提出了一种基于免疫检测器集的高速网络自适应入侵检测系统设计方法,人工免疫算法的自我与非自我识别机制可检测新型变种的入侵行为与网络异常,针对该算法的执行效率提出自体集规模约束方法产生检测器,可以实时检测网络数据,适用于高速网络中发现未知入侵行为。
In the intrusion detection method of network security products, the mainstream feature detection and anomaly detection all have problems such as the lack of sequence data processing ability and the rule base updating in time, and the intelligent algorithm can not be detected in real time in the high speed network due to the operation efficiency problem. This paper presents a design method of high speed network adaptive intrusion detection system based on immune detector set. The self-identification and non-self-identification mechanism of artificial immune algorithm can detect the intrusion behavior and network anomaly of the new variant. According to the implementation efficiency of the algorithm, Set size constraints method to generate detectors, real-time detection of network data for high-speed network to find unknown intrusion.