面向入侵检测系统的EBP算法研究

The Research of EBP Algorithm for Intrusion Detection System

BP算法是入侵检测系统(IDS)的一种重要检测方法,但是该算法存在检测时间长、效率低下等局限性.为了解决以上问题,通过对BP算法的深入剖析,提出了一种面向入侵检测系统的新算法——EBP(Enhanced BP)算法.EBP算法通过改进误差函数、增加可自适应放大的误差信号等方法,较好地解决了IDS的检测速度慢、检测效率低下等问题.实验结果表明,EBP算法相比经典的BP算法和MBP算法,不仅在网络训练的收敛速度上有了明显改善,而且在IDS的检测效率上分别提高了14.0%和8.1%,在误报率上分别降低了4.45%和1.5%.

Although BP algorithm is a very important method in the intrusion detection systems（IDS）,it can cause the system problems of long time detection and low detection rate.To solve these problems,through analyzing the BP algorithm,a novel EBP algorithm（Enhanced BP algorithm）for IDS is constructed.An improved error function is designed in EBP algorithm to solve some disadvantages of the IDS,such as the slower detection speed and detection efficiency.Moreover,a self-adaptive method of magnifying error signal is also proposed.The results show that the EBP algorithm is an efficient algorithm.Compared with the classical BP algorithm and the MBP algorithm,the EBP algorithm can not only increases the convergence speed of network training obviously,but also improves the detection rate of IDS to 14.0% and 8.1%respectively.Besides,the decrease in false positive rate of EBP algorithm is 4.45% and 1.5%than other two algorithms respectively.