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Enhance Physical Layer Security via Channel Randomization with Reconfigurable Antennas

  • Yanjun Pan
  • Ming LiEmail author
  • Yantian Hou
  • Ryan M. Gerdes
  • Bedri A. Cetiner
Chapter
Part of the Advances in Information Security book series (ADIS, volume 74)

Abstract

Secure wireless communication techniques based on physical (PHY) layer properties are promising alternatives or complements to traditional upper-layer cryptography-based solutions, due to the capability of achieving message confidentiality or integrity and authentication protection without pre-shared secrets. While many theoretical results are available, there are few practical PHY-layer security schemes, mainly because the requirement of channel advantage between the legitimate users versus the attacker’s is hard to satisfy in all cases. Recent research shows that channel randomization, which proactively and dynamically perturbs the physical channel so as to create an artificial channel advantage, is helpful to enhance certain PHY-layer security goals such as secrecy. However, a systematic study of the foundations of such an approach and its applicability is needed. In this chapter, we first survey the state-of-the-art in PHY-layer security and identify their main limitations as well as challenges. Then we examine the principles of channel randomization and explore its application to achieve in-band message integrity and authentication. Especially, we focus on preventing active signal manipulation attacks and use reconfigurable antennas to systematically randomize the channel such that it is unpredictable to the active attacker. Both theoretical and experimental results show that it is a feasible and effective approach. Other applications and future directions are discussed in the end.

Notes

Acknowledgements

This work was partly supported by NSF grants CNS-1410000, CNS-1619728, CAREER Award CNS-1564477, ONR YIP Award N00014-16-1-2650. The multifunctional reconfigurable antenna design aspect of this work performed at Utah State University is supported in part by AFOSR Grant No FA 9550-15-1-0040 DEF.

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Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019

Authors and Affiliations

  • Yanjun Pan
    • 1
  • Ming Li
    • 1
    Email author
  • Yantian Hou
    • 2
  • Ryan M. Gerdes
    • 3
  • Bedri A. Cetiner
    • 4
  1. 1.The University of ArizonaTucsonUSA
  2. 2.Boise State UniversityBoiseUSA
  3. 3.Virginia TechArlingtonUSA
  4. 4.Utah State UniversityLoganUSA

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