文章基本信息

标题：Improving Intrusion Detection System by Developing Feature Selection Model Based on Firefly Algorithm and Support Vector Machine
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作者：Wathiq Laftah Al-Yaseen
期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2019
卷号：46
期号：4
页码：534-540
出版社：IAENG - International Association of Engineers
摘要：The nowadays growing of threads and intrusionson networks make the need for developing efficient and effectiveintrusion detection systems a necessity. Powerful solutions ofintrusion detection systems should be capable of dealing withcentral network issues such as huge data, high-speed traffic, andwide variety in threat types. This paper proposes a wrapperfeature selection method that is based on firefly algorithm andsupport vector machine. The firefly optimization algorithm hasbeen effectively employed in diverse combinatorial problems.The proposed method improves the performance of intrusiondetection by removing the irrelevant features and reduces thetime of classification by reducing the dimension of data. TheSVM model was employed to evaluate each of the featuresubsets produced from firefly technique. The main merit ofthe proposed method is its ability in modifying the fireflyalgorithm to become suitable for selection of features. Tovalidate the proposed approach, the popular NSL-KDD datasetwas used in addition to the common measures of intrusiondetection systems such as overall accuracy, detection rate, andfalse alarm rate. The proposed method achieved an overallaccuracy of 78.89% compared with 75.81% for all the 41features. The analysis results approved the effectiveness ofthe proposed feature selection method in enhancing networkintrusion detection system.
关键词：intrusion detection system; support vector;machine; firefly algorithm; wrapper feature selection method