改进的检测器大小可变的免疫异常检测算法

Improved Immune-Based Anomaly Algorithm with Variable-Size Detector

在传统的免疫异常检测算法中,通常存在检测器对非我空间的覆盖漏洞,以及检测器数量过大且相互覆盖等问题,这是导致免疫异常检测算法效率较低的主要原因。提出了一种能够处理混合型数据的免疫异常检测算法,它能够生成不同大小的检测器,提高对非我空间覆盖的效率。通过模拟实验和对比实验表明,该算法能够较好地完成对混合型数据的处理,并有效提高生成检测器的效率。

Previous research has indicated there are some defects in the traditional immune-based algorithm of detecting abnormity.Two common defects of this are as follows：the detectors created by the algorithm cannot cover all Nonself-space, and the number of the detectors in the algorithm is too big to keep the detectors from covering each other.These defects are the main reasons why the algorithm is not efficient.In this paper, an algorithm, which can deal with mixed-type data and produce detectors in different sizes to improve the capacity of covering Nonself-space is proposed.The simulated and compared experiments show that this algorithm can preferably process mixed-type data and effectively improve the efficiency of generating detectors .