© 2018

Adversary Detection For Cognitive Radio Networks


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

Table of contents

  1. Front Matter
    Pages i-x
  2. Xiaofan He, Huaiyu Dai
    Pages 1-6
  3. Xiaofan He, Huaiyu Dai
    Pages 7-17
  4. Xiaofan He, Huaiyu Dai
    Pages 19-44
  5. Xiaofan He, Huaiyu Dai
    Pages 51-62
  6. Xiaofan He, Huaiyu Dai
    Pages 63-72
  7. Xiaofan He, Huaiyu Dai
    Pages 73-74

About this book


This SpringerBrief provides a comprehensive study of the unique security threats to cognitive radio (CR) networks and a systematic investigation of the state-of-the-art in the corresponding adversary detection problems. In addition, detailed discussions of the underlying fundamental analytical tools and engineering methodologies of these adversary detection techniques are provided, considering that many of them are quite general and have been widely employed in many other related fields.

 The exposition of this book starts from a brief introduction of the CR technology and spectrum sensing in Chapter 1. This is followed by an overview of the relevant security vulnerabilities and a detailed discussion of two security threats unique to CR networks, namely, the primary user emulation (PUE) attack and the Byzantine attack.

 To better prepare the reader for the discussions in later chapters, preliminaries of analytic tools related to adversary detection are introduced in Chapter 2. In Chapter 3, a suite of cutting-edge adversary detection techniques tailor-designed against the PUE and the Byzantine attacks are reviewed to provide a clear overview of existing research in this field.

 More detailed case studies are presented in Chapters 4 – 6. Specifically, a physical-layer based PUE attack detection scheme is presented in Chapter 4, while Chapters 5 and 6 are devoted to the illustration of two novel detection techniques against the Byzantine attack. Concluding remarks and outlooks for future research are provided in Chapter 7.

 The  primary audience for this SpringerBrief include network engineers interested in addressing adversary detection issues in cognitive radio networks, researchers interested in the state-of-the-art on unique security threats to cognitive radio networks and the corresponding detection mechanisms. Also, graduate and undergraduate students interested in obtaining comprehensive information on adversary detection in cognitive radio networks and applying the underlying techniques to address relevant research problems can use this SpringerBrief as a study guide. 


Cognitive radio Spectrum sensing Security Adversary detection Primary user emulation attack Byzantine attack wireless security spectrum sensing data falsification physical-layer hidden Markov model conditional frequency check

Authors and affiliations

  1. 1.Department of Electrical EngineeringLamar UniversityBeaumontUSA
  2. 2.Department of Electrical and Computer EngineeringNorth Carolina State UniversityRaleighUSA

Bibliographic information

  • Book Title Adversary Detection For Cognitive Radio Networks
  • Authors Xiaofan He
    Huaiyu Dai
  • Series Title SpringerBriefs in Electrical and Computer Engineering
  • Series Abbreviated Title SpringerBriefs in Electrical
  • DOI
  • Copyright Information The Author(s) 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Softcover ISBN 978-3-319-75867-1
  • eBook ISBN 978-3-319-75868-8
  • Series ISSN 2191-8112
  • Series E-ISSN 2191-8120
  • Edition Number 1
  • Number of Pages X, 74
  • Number of Illustrations 0 b/w illustrations, 0 illustrations in colour
  • Topics Communications Engineering, Networks
  • Buy this book on publisher's site
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