Time Synchronization Attacks in Sensor Networks

  • Tanya Roosta
  • Mike Manzo
  • Shankar Sastry
Part of the Advances in Information Security book series (ADIS, volume 30)

Abstract

In this chapter, we review time synchronization attacks in wireless sensor networks. We will first consider three of the main time synchronization protocols in sensor network in sections. In section we discuss applications of time synchronization in sensor networks. In section we analyze possible security attacks on the existing time synchronization protocols. In section we examine how different sensor network applications are affected by time synchronization attacks. Finally in section we propose possible countermeasures to secure the time synchronization protocols.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Balogh, G., Ledeczi, A., Maroti, M., Simon, G. Time of Arrival Data Fusion for Source Localization.Google Scholar
  2. 2.
    Coleri, S. PEDAMACS: Power Efficient and Delay Aware Medium Access Protocol for Sensor Networks. M.S. Thesis, UC. Berkeley, December 2002.Google Scholar
  3. 3.
    Elson, J., Estrin, D. Fine-Grained Network Time Synchronization using Reference Broadcast. The fifth symposium on Operating Systems Design and Implementation (OSDI), p. 147–163, December 2002.Google Scholar
  4. 4.
    Fischler, M. A., Bolles, R. C. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM, Vol 24, pp 381–395, 1981.CrossRefMathSciNetGoogle Scholar
  5. 5.
    Ganeriwawal, S., Kumar, R., Srivastava, M. Timing-Sync Protocol for Sensor Networks. The first ACM Conference on Embedded Networked Sensor Systems (SenSys), p. 138–149, November 2003.Google Scholar
  6. 6.
    Hohlt, B., Doherty, L., Brewer, E. Flexible Power Scheduling for Sensor Networks. Information Processing in Sensor Networks (IPSN), April 2004, Berkeley, CA.Google Scholar
  7. 7.
    Karlof, C, Sastry, N., Wagner, D. TinySec: A Link Layer Security Architecture for Wireless Sensor Networks. Proceedings of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys), pages 162–175, November 2004.Google Scholar
  8. 8.
    Ledeczi A., Volgyesi P., Martoi M., et al. Multiple Simultaneous Acoustic Source Localization in Urban Terrain.Google Scholar
  9. 9.
    Maroti, M., Kusy, B., Simon, G., Ledeczi, A. The Flooding Synchronization Protocol. Proc. Of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys), November 2004.Google Scholar
  10. 10.
    Oh, S., Russell, S., Sastry, S. Markov Chain Monte Carlo Data Association for General Multiple-Target Tracking Problems.Google Scholar
  11. 11.
    Perrig, A., Szewczyk, R., Wen, V., Culler, D., Tygar, J. D. SPINS: Security Protocols for Sensor Networks. Mobile Computing and Networking. Rome, Italy, 2001.Google Scholar
  12. 12.
    Simon, G., Maroti, M., Ledeczi, A.. Sensor Network-Based Countersniper System. Proc. Of the Second ACM Conference on Embedded Networked Sensor Systems (SenSys), November 2004.Google Scholar
  13. 13.
    Welch, G., Bishop, G. An Introduction to the Kalman Filter. University of North Carolina at Chapel Hill, Department of Computer Science, Chapel Hill, NC, USA. TR95-041. Available online at: http://www.cs.unc.edu/welch/publications.htmlGoogle Scholar
  14. 14.
    Available on the web: www.xbow.com/Products/productsdetails.aspx?sid=62Google Scholar
  15. 15.
    Available on the web: http://www.cs.unc.edu/ tracker/media/pdf/ SIG-GRAPH2001-CoursePack-08.pdfGoogle Scholar
  16. 16.
    Available on the web: www.wabash.edu/econexcel/LMSOrigin/LMSIntro.docGoogle Scholar
  17. 17.
    Rmer, Kay. Time Synchronization in Ad Hoc Networks. Proceedings of MobiHoc 2001, ACM, October 2001.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Tanya Roosta
    • 1
  • Mike Manzo
    • 1
  • Shankar Sastry
    • 1
  1. 1.University of California at BerkeleyBerkeley

Personalised recommendations