Intrusion detection system based on improved abc algorithm with tabu search
Intrusion detection system based on improved abc algorithm with tabu search
复制标题
基于禁忌搜索的改进abc算法的入侵检测系统
DOI：
10.1002/tee.22987
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发表时间：
2019
影响因子：
1
通讯作者：
Long Li
中科院分区：
文献类型：
--
作者：
Tianlong Gu;Hanyi Chen;Liang Chang;Long Li
入侵检测系统(入侵检测系统)对网络攻击的检测在网络安全中起着重要作用。为了提高入侵检测系统的有效性，提出了一种基于支持向量机和改进的禁忌搜索人工蜂群算法的入侵检测方法。在新方法中，针对网络数据冗余和模型参数不足的问题，提出了特征选择和参数计算的同步优化策略。同时，TS的思想替代了ABC算法的贪婪选择特性，并在ABC算法的前期和后期演化中给出了两种不同的选择概率公式。实验结果表明，该方法在检测准确率和漏检率方面均优于已有的方法。此外，探测攻击和DoS攻击的检测率分别达到99.987和99.687%。2019日本电气工程师学会。作者：John Wiley&Sons，Inc.
An intrusion detection system (IDS) plays an important role in cyber security to detect network attacks. To improve the effectiveness of IDS, a new intrusion detection approach based on the support vector machine and improved Artificial Bee Colony algorithm (ABC) with Tabu Search (TS) is proposed. In the new method, to solve the problem of redundant network data and insufficient model parameters, a synchronous optimization strategy for feature selection and parameter calculation is proposed. At the same time, the idea of TS is a substitute for the greedy selection property of ABC, and two different selection probability formulas are provided in the early and later evolution of the ABC algorithm. The experimental results show that the newly proposed method performs better than other existing methods, especially in terms of detection accuracy and false negative rate. Besides, the detection rate of Probe attack and DoS attack reached 99.987 and 99.687%, respectively. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.