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FCM–SVM based intrusion detection system for cloud computing environment

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Abstract

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.

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Acknowledgements

This work was supported by the Faculty of Computer Systems and Software Engineering (FSKKP), Univer-siti Malaysia Pahang (UMP), Malaysia. In collaboration with ST Engineering Electronics-SUTD Cyber Security Laboratory, Singapore University of Technology and Design (SUTD), Singapore.

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Authors and Affiliations

  1. Faculty of Computer Systems and Software Engineering (FSKKP), Universiti Malaysia, Pahang, Malaysia

    Aws Naser Jaber

  2. ST Engineering Electronics - SUTD Cyber Security Laboratory, Singapore University of Technology and Design (SUTD), 8 Somapah Road, 487372, Singapore, Singapore

    Shafiq Ul Rehman

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  1. Aws Naser Jaber
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  2. Shafiq Ul Rehman
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Correspondence to Shafiq Ul Rehman.

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Jaber, A.N., Rehman, S.U. FCM–SVM based intrusion detection system for cloud computing environment. Cluster Comput 23, 3221–3231 (2020). https://doi.org/10.1007/s10586-020-03082-6

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