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Related Work

  • Jie Yang
  • Yingying ChenEmail author
  • Wade Trappe
  • Jerry Cheng
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

The traditional approach to prevent spoofing attacks is to use cryptographic-based authentication (B. Wu, J. Wu, E. Fernandez, and S. Magliveras, “Secure and efficient key management in mobile ad hoc networks,” in Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2005., Wool, ACM/Springer Wirel Networks 11(6): pp. 677–686, 2005, M. bohge and W. Trappe, “An authentication framework for hierarchical ad hoc sensor networks,” in Proceedings of the ACM Workshop on Wireless Security (WiSe), 2003, pp. 79–87. B. Wu, J. Wu, E. Fernandez, and S. Magliveras (“Secure and efficient key management in mobile ad hoc networks,” in Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2005). has introduced a secure and efficient key management framework (SEKM). SEKM builds a Public Key Infrastructure (PKI) by applying a secret sharing scheme and an underlying multicast server group. A. Wool, “Lightweight key management for ieee 802.11 wireless lans with key refresh and host revocation,” ACM/Springer Wireless Networks, vol. 11, no. 6, pp. 677–686, 2005. implemented a key management mechanism with periodic key refresh and host revocation. to prevent the compromise of authentication keys. An authentication framework for hierarchical, ad hoc sensor networks is proposed in M. bohge and W. Trappe, (“An authentication framework for hierarchical ad hoc sensor networks,” in Proceedings of the ACM Workshop on Wireless Security (WiSe), 2003, pp. 79–87). However, the cryptographic authentication may not be always applicable because of the limited resources on wireless devices, and lacking of a fixed key management infrastructure in the wireless network.

Keywords

Gaussian Mixture Model Receive Signal Strength Indicator Secret Share Scheme Link Quality Indicator Authentication Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Jie Yang
    • 1
  • Yingying Chen
    • 2
    Email author
  • Wade Trappe
    • 3
  • Jerry Cheng
    • 4
  1. 1.Department of Computer Science and EngineeringOakland UniversityRochesterUSA
  2. 2.Department of Electrical & Computer EngineeringStevens Institute of TechnologyHobokenUSA
  3. 3.Wireless Information Network LabRutgers, The State University of New JerseyNorth BrunswickUSA
  4. 4.Rutgers, The State University of New JerseyNew BrunswickUSA

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