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Ca-NIDS: A network intrusion detection system using combinatorial algorithm approach

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  • Olusegun Folorunso
  • Femi Emmanuel Ayo
  • Y. E. Babalola

Abstract

A signature-based system (SBS) is a common approach for intrusion detection and the most preferable by researchers. In spite of the popularity of SBS, it cannot detect new attacks on the network compared to anomaly-based systems (ABS). The most challenging problem of SBS is keeping an up-to-date database of known attack signatures and the setting of a suitable threshold level for intrusion detection. In this article, a network intrusion detection system based on combinatorial algorithm (CA-NIDS) is proposed. The CA-NIDS uses additional databases to enable the SBS to act as an ABS for the purpose of detecting new attacks and to speed up network traffic during traffic analysis by the combinatorial algorithm. A suitable threshold of 12 was also set based on the study of past works to lower the false positive rate. The CA-NIDS was evaluated with similar online schemes and result shows a small false-positive rate of 3% and a better accuracy of 96.5% compared with related online algorithms.

Suggested Citation

  • Olusegun Folorunso & Femi Emmanuel Ayo & Y. E. Babalola, 2016. "Ca-NIDS: A network intrusion detection system using combinatorial algorithm approach," Journal of Information Privacy and Security, Taylor & Francis Journals, vol. 12(4), pages 181-196, October.
    • Handle: RePEc:taf:uipsxx:v:12:y:2016:i:4:p:181-196
    DOI: 10.1080/15536548.2016.1257680
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    Cited by:

    1. Femi Emmanuel Ayo & Joseph Bamidele Awotunde & Olasupo Ahmed Olalekan & Agbotiname Lucky Imoize & Chun-Ta Li & Cheng-Chi Lee, 2023. "CBFISKD: A Combinatorial-Based Fuzzy Inference System for Keylogger Detection," Mathematics, MDPI, vol. 11(8), pages 1-24, April.

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