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Adversary Detection For Cognitive Radio Networks

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

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-x
  2. Introduction

    • Xiaofan He, Huaiyu Dai
    Pages 1-6
  3. Preliminaries of Analytical Tools

    • Xiaofan He, Huaiyu Dai
    Pages 7-17
  4. Overview of Adversary Detection in CR Networks

    • Xiaofan He, Huaiyu Dai
    Pages 19-44
  5. Case Study II: HMM-Based Byzantine Attack Detection

    • Xiaofan He, Huaiyu Dai
    Pages 51-62
  6. Case Study III: CFC-Based Byzantine Attack Detection

    • Xiaofan He, Huaiyu Dai
    Pages 63-72
  7. Conclusion and Future Work

    • 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. 

Authors and Affiliations

  • Department of Electrical Engineering, Lamar University, Beaumont, USA

    Xiaofan He

  • Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, USA

    Huaiyu Dai

Bibliographic Information

Buy it now

Buying options

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access