Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Membrane Computing (MC) with its variants has proved to be a versatile class of distributed parallel computing model. This is because despite its infancy, it has enjoyed significant application in various fields. However, much is yet to be accomplished in the area of information and network security. So, to further explore the efficacy of MC, this paper presents a new attempt in the application of SN P system and as well provides a novel idea and method for attack detection. The extension of SN P system called trapezoidal Fuzzy Reasoning Spiking Neural P (tFRSN P) system is adopted in the network intrusion prediction model. SN P system is a neural-like computing model inspired from the way spiking neurons communicate using spikes. It has a graphical modeling advantage which makes it well suited for fuzzy reasoning as well as fuzzy knowledge representation. In order to evaluate the performance of tFRSN P system in intrusion detection, the publicly available KDD Cup benchmark dataset was employed. After the experiments, our results yielded very high detection rate of 99.78% and very low false alarm rate of 0.16% for Brute Force Attack (BFA).

Original languageEnglish
Title of host publicationProceedings - Asian Conference on Membrane Computing, ACMC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781479980123
DOIs
Publication statusPublished - 23 Mar 2015
Event2014 Asian Conference on Membrane Computing, ACMC 2014 - Coimbatore, Tamil Nadu, India
Duration: 18 Sep 201419 Sep 2014

Other

Other2014 Asian Conference on Membrane Computing, ACMC 2014
CountryIndia
CityCoimbatore, Tamil Nadu
Period18/9/1419/9/14

Fingerprint

Intrusion detection
Membranes
Network security
Knowledge representation
Security of data
Parallel processing systems
Neurons
Experiments

Keywords

  • Cyber-security
  • Fuzzy reasoning
  • Intrusion Detection
  • P System
  • Rule-based System

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications

Cite this

Idowu, R., Chandren, R., & Othman, Z. (2015). Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection. In Proceedings - Asian Conference on Membrane Computing, ACMC 2014 [7065804] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACMC.2014.7065804

Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection. / Idowu, Rufai; Chandren, Ravie; Othman, Zulaiha.

Proceedings - Asian Conference on Membrane Computing, ACMC 2014. Institute of Electrical and Electronics Engineers Inc., 2015. 7065804.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Idowu, R, Chandren, R & Othman, Z 2015, Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection. in Proceedings - Asian Conference on Membrane Computing, ACMC 2014., 7065804, Institute of Electrical and Electronics Engineers Inc., 2014 Asian Conference on Membrane Computing, ACMC 2014, Coimbatore, Tamil Nadu, India, 18/9/14. https://doi.org/10.1109/ACMC.2014.7065804
Idowu R, Chandren R, Othman Z. Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection. In Proceedings - Asian Conference on Membrane Computing, ACMC 2014. Institute of Electrical and Electronics Engineers Inc. 2015. 7065804 https://doi.org/10.1109/ACMC.2014.7065804
Idowu, Rufai ; Chandren, Ravie ; Othman, Zulaiha. / Advocating the use of fuzzy reasoning spiking neural P system in intrusion detection. Proceedings - Asian Conference on Membrane Computing, ACMC 2014. Institute of Electrical and Electronics Engineers Inc., 2015.
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