Immune Based Intrusion Detector Generating Algorithm

Immune-based intrusion detection approaches are studied. The methods ofconstructing self set and generating mature detectors are researched and improved. A binary encodingbased self set construction method is applied. First, the traditional mature detector generatingalgorithm is improved to generate mature detectors and detect intrusions faster. Then, a novelmature detector generating algorithm is proposed based on the negative selection mechanism.According to the algorithm, less mature detectors are needed to detect the abnormal activities inthe network. Therefore, the speed of generating mature detecotrs and intrusion detection isimproved. By comparing with those based on existing algorithms, the intrusion detection system basedon the algorithm has higher speed and accuracy.

基于免疫的入侵检测方法研究

生物的免疫系统和计算机安全系统所面临及需要解决的问题十分类似,采用生物免疫思想的入侵检测技术可以结合 异常检测和误用检测的优点．研究了基于免疫的入侵检测方法,对Self集的确定和有效检测器的生成方法进行了研宛和改进, 基于反向选择机制提出了一种新的有效检测器生成算法,可以使用较少的有效检测器检测网络中的异常行为,从而提高了有效 检测器生成和入侵检测的速度．通过与基于已有的有效检测器生成算法的系统进行比较,使用本文的方法构造的入侵检测系统 速度更快,且有较高的准确性．

基于免疫机制的入侵检测器生成的研究

为了提高基于人工免疫入侵检测系统中有效检测器的生成和检测效率,通过对传统检测器生成算法的研究,结合传统阴性选择算法和缩小检测器长度的方法,提出了一种新的检测器生成算法。实验证明该算法生成的检测器在保证了检测准确性的同时减少了检测所需的时间。