FCM–SVM based intrusion detection system for cloud computing environment

被引:0
|
作者
Aws Naser Jaber
Shafiq Ul Rehman
机构
[1] Universiti Malaysia,Faculty of Computer Systems and Software Engineering (FSKKP)
[2] Singapore University of Technology and Design (SUTD),ST Engineering Electronics
来源
Cluster Computing | 2020年 / 23卷
关键词
Intrusion detection system; Cloud computing; DDoS attacks; Machine learning classifiers; Cyber security; FCM; SVM;
D O I
暂无
中图分类号
学科分类号
摘要
Cloud computing offer various services over the Internet based on pay-per-use concept. Therefore, many organizations have already adopted this system to attract the users with its desirable features. However, due to its design, makes it vulnerable to malicious attacks. This demands an Intrusion Detection System that can detect such attacks with high detection accuracy in cloud environment. This paper proposes a novel intrusion detection system that combines a fuzzy c means clustering (FCM) algorithm with support vector machine (SVM) to improve the accuracy of the detection system in cloud computing environment. The proposed system is implemented and compared with existing mechanisms. The NSL-KDD dataset is used for experiments. Based on performance evaluation and comparative analysis, the results obtained using this new hybrid mechanism (FCM–SVM) show that the proposed system can detect the anomalies with high detection accuracy and low false alarm rates over the existing techniques.
引用
收藏
页码:3221 / 3231
页数:10
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