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Review of Machine Learning-Based Intrusion Detection Techniques for MANETs

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Computing and Network Sustainability

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 75))

Abstract

Mobile ad hoc network is a widely developing technology that has been used in various areas such as in health care, military, virtual classrooms and conferences. However, mobile ad hoc networks are installed in critical situations security in this network is an important issue. Many susceptible characteristics of mobile ad hoc networks make an attacker breach the system easily. So, it is important to have an intrusion detection system which can monitor mobile ad hoc networks constantly to identify any suspicious behaviour. Anomaly and misuse detection are the two widely used intrusion detection mechanisms used to analyse the attacks in mobile ad hoc networks. Anomaly intrusion detectors were proven to be more effective against unknown attacks. A number of anomaly-based intrusion detectors based on machine learning techniques were developed and tested against various attacks. In this paper, several intrusion detection techniques which used machine learning approaches for detection are reviewed and a hybrid IDS technique which combines with genetic algorithm and Bayesian game theory is proposed.

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Author information

Authors and Affiliations

  1. Noorul Islam Centre for Higher Education, Kumaracoil, Kanyakumari, India

    Fouziah Hamza & S. Maria Celestin Vigila

Authors
  1. Fouziah Hamza
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  2. S. Maria Celestin Vigila
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Corresponding author

Correspondence to Fouziah Hamza .

Editor information

Editors and Affiliations

  1. Department of Computer Science , National Dong Hwa University, Hualien, Taiwan

    Sheng-Lung Peng

  2. Techno India College of Technology, Kolkata, West Bengal, India

    Nilanjan Dey

  3. Poornima University, Jaipur, Rajasthan, India

    Mahesh Bundele

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Hamza, F., Maria Celestin Vigila, S. (2019). Review of Machine Learning-Based Intrusion Detection Techniques for MANETs. In: Peng, SL., Dey, N., Bundele, M. (eds) Computing and Network Sustainability. Lecture Notes in Networks and Systems, vol 75. Springer, Singapore. https://doi.org/10.1007/978-981-13-7150-9_39

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  • DOI: https://doi.org/10.1007/978-981-13-7150-9_39

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-7149-3

  • Online ISBN: 978-981-13-7150-9

  • eBook Packages: EngineeringEngineering (R0)

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