A Passive Approach to Unauthorized Sensor Node Identification

  • Cherita Corbett
  • John Copeland
  • Raheem Beyah
Part of the Signals and Communication Technology book series (SCT)

As access to power becomes less of a concern (solar powered devices, wind powered devices, longer battery life, AC), the desire for higher bandwidth com- munication, and a desire for easy deployment, sensor networks are increasingly using the 802.11 medium access control (MAC) protocol. Further, some sensor deployment schemes are heterogeneous, using smaller low-powered sensors for traffic routing, but use higher-powered devices that use 802.11 to improve overall performance of the network. Accordingly, in this chapter we discuss security concerns that apply to sensor networks, but extend to any network using the 802.11 MAC, including wireless local area networks (WLANs) and ad hoc networks.


Sensor Network Sensor Node Medium Access Control Power Spectral Density Relay Node 
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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  1. 1.
    Sunwoong Choi, Kihong Park and Chong-kwon Kim, On the Performance Char-acteristics of WLANs: Revisited, ACM Sigmetrics, Banff, Alberta, Canada, 2005.Google Scholar
  2. 2.
    The 802.11i Standard, getieee802/download/802.11i-2004.pdf.
  3. 3.
  4. 4.
    Chulsung Park, Qiang Xie and Pai H. Chou, DuraNode: Wi-Fi-based Sensor Node for Real-Time Structural Safety Monitoring, The Fourth International Conference on Information Processing in Sensor Networks (IPSN 2005), 2005.Google Scholar
  5. 5.
    Alefiya Hussain, John Heidemann and Christos Papadopoulos, Identification of repeated attacks using network traffic forensics, USC/Information Sciences Insti-tute, ISI-TR-2003-577b, 2003.Google Scholar
  6. 6.
    W. Richard Stevens, Unix Network Programming, Prentice Hall, 1998.Google Scholar
  7. 7.
    A.V. Oppenheim and R.W. Schafer, Discrete-Time Signal Processing, Prentice-Hall, 1989.Google Scholar
  8. 8.
    C. Partridge, D. Cousins, A.W. Jackson, R. Krishan T. Saxena and T. Strayer, Using Signal Processing to Analyze Wireless Data Traffic, ACM Workshop on Wireless Security (WiSe), Atlanta, GA, 2002.Google Scholar
  9. 9.
    Chen-Mou Cheng, H.T. Kung and Koan-Sin Ta, Use of spectral analysis in de-fense against DoS attacks, IEEE GLOBECOM, 2002.Google Scholar
  10. 10.
    M. Lacage, M. Manshaei and T. Turletti, IEEE 802.11 Rate Adaption: A Prac-tical Approach, ACM/IEEE MSWIM, Venice, Italy, 2004.Google Scholar
  11. 11.
    Tadayoshi Kohno, Andre Briodo and KC Claffy, Remote physical device finger-printing, IEEE Transactions on Dependable and Secure Computing, vol.2 pp.93-108,2005.CrossRefGoogle Scholar
  12. 12.
    Jeyanthi Hall, Michel Barbeau and Evangelos Kranakis, Detection of Transient in Radio Frequency Fingerprinting using Signal Phase, Internet and Information Technology (CIIT), 2004.Google Scholar
  13. 13.
  14. 14.
    iPass, deviceid.html.
  15. 15.
  16. 16.
    Joshua Wright, Detecting Wireless LAN MAC Address Spoofing, Scholar
  17. 17.
  18. 18.
    Slayer,TheDefinitiveGuideToWirelessWarX’ing, Scholar
  19. 19.
    William A. Arbaugh, Narendar Shankar and Y.C. Justin Wan, Your 802.11 wireless network has no clothes, waa/wireless.pdf.
  20. 20.
    Nikita Borisov, Ian Golberg and David Wagner, Intercepting mobile communi-cations: The insecurity of 802.11, MOBICOM, 2001.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Cherita Corbett
    • 1
  • John Copeland
    • 1
  • Raheem Beyah
    • 2
  1. 1.School of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaUSA
  2. 2.Department of Computer ScienceGeorgia State UniversityAtlantaUSA

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