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Overview of Adversary Detection in CR Networks

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Book cover Adversary Detection For Cognitive Radio Networks

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

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Abstract

As discussed in Chap. 1, the PUE attack and the Byzantine attack are two severe security threats unique to the CR networks, and if not properly addressed, the functionality of the entire CR network will be demolished. With this consideration, advocators of the CR technology have devoted substantial research efforts to address these two security problems in the past decade. Most of them focus on how to detect and identify the adversaries; after all, detection and identification is usually the very first step to remove a security threat. The objective of this chapter is to provide an overview of the recent advancements in detecting these two disrupting attacks. Particularly, in the first part of this chapter, we intend to provide a systematic review of the existing PUE attack detection methods, and in the second part of this chapter, we will switch gear towards the Byzantine attack detection schemes.

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Notes

  1. 1.

    In [5], it is assumed that multiple PUE attackers are uniformly distributed in the CR networks. Interested readers may refer to [5] for the details of estimating these two parameters in practice.

  2. 2.

    This mechanism does require some modifications in the PU transmitter but the PU receiver can be kept unchanged.

  3. 3.

    As the removal of the malicious SU will change the set \(\mathcal {F}_t\), the suspicious levels of the rest SUs have to be re-evaluated.

  4. 4.

    This is feasible since the reputation update formula is publicly known and the attacker knows its own reported sensing results.

  5. 5.

    One of the fundamental differences between the DS theory and probability theory is that the basic assignment admits \(\sum _{A\in 2^{\varOmega }} m(A)=1\) whereas a probability measurement admits p(Ω) = 1.

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Authors and Affiliations

  1. Department of Electrical Engineering, Lamar University, Beaumont, TX, USA

    Xiaofan He

  2. Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USA

    Huaiyu Dai

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  1. Xiaofan He
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He, X., Dai, H. (2018). Overview of Adversary Detection in CR Networks. In: Adversary Detection For Cognitive Radio Networks. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-75868-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-75868-8_3

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