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Anomaly-based framework for detecting dynamic spectrum access attacks in cognitive radio networks

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Abstract

Several new attacks have been identified in CRNs such as primary user emulation, dynamic spectrum access (DSA), and jamming attacks. Such types of attacks can severely impact network performance, specially in terms of the over all achieved network throughput. In response to that, intrusion detection system (IDS) based on anomaly and signature detection is recognized as an effective candidate solution to handle and mitigate these types of attacks. In this paper, we present an intrusion detection system for CRNs (CR-IDS) using the anomaly-based detection (ABD) approach. The proposed ABD algorithm provides the ability to effectively detect the different types of CRNs security attacks. CR-IDS contains different cooperative components to accomplish its desired functionalities which are monitoring, feature generation and selection, rule generation, rule based system, detection module, action module, impact analysis and learning module. Our simulation results show that CR-IDS can detect DSA attacks with high detection rate and very low false negative and false positive probabilities.

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Authors and Affiliations

  1. Jordan University of Science and Technology, Irbid, Jordan

    Yaser Jararweh, Abdallah Alturani & Loai Tawalbeh

  2. Yarmouk University, Irbid, Jordan

    Haythem A. Bany Salameh

  3. West Virginia University, Morgantown, WV, USA

    Houbing Song

Authors
  1. Yaser Jararweh
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  2. Haythem A. Bany Salameh
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  3. Abdallah Alturani
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  4. Loai Tawalbeh
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  5. Houbing Song
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Correspondence to Yaser Jararweh.

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Jararweh, Y., Bany Salameh, H.A., Alturani, A. et al. Anomaly-based framework for detecting dynamic spectrum access attacks in cognitive radio networks. Telecommun Syst 67, 217–229 (2018). https://doi.org/10.1007/s11235-017-0329-9

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