Improving Sensor Network Security with Information Quality

  • Qiang Qiu
  • Tieyan Li
  • Jit Biswas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3813)


With extremely limited resources, it is hard to protect sensor networks well with conventional security mechanisms. We study a class of passive fingerprinting techniques and propose an innovative information quality based approach to improve the security of sensor network. For each sensor, we create a quality profile QP of profiling its normal/standard sensing behaviour. After deployment, new sensor readings are verified using this QP. If significant deviation is found, we either regard the readings as an abnormal behaviour or declare the sensor to be a fake sensor. The methods can be used as an assistant sensor authentication mechanism, but with a potential drawback. Furthermore, we also demonstrate a secure data fusion protocol, applying the proposed methods together with conventional security mechanisms. Through security analysis, we point out several countermeasures that can explicitly or implicitly defend against these attacks.


Sensor Network Sensor Node Wireless Sensor Network Cluster Head Information Quality 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Perrig, A., Stankovic, J., Wagner, D.: Security in wireless sensor networks. Communications of the ACM 47(6), 53–57 (2004); Special Issue on Wireless sensor networksCrossRefGoogle Scholar
  2. 2.
    Wood, A.D., Stankovic, J.A.: Denial of Service in Sensor Networks. IEEE Computer 35(10), 54–62 (2002)Google Scholar
  3. 3.
    Karlof, C., Wagner, D.: Secure Routing in Wireless Sensor Networks: Attacks and Countermeasures. In: First IEEE International Workshop on Sensor Network Protocols and Applications (May 2003)Google Scholar
  4. 4.
    Newsome, J., Shi, E., Song, D., Perrig, A.: The Sybil Attack in Sensor Networks: Analysis and Defenses. In: Third International Symposium on Information Processing in Sensor Networks, IPSN 2004 (2004)Google Scholar
  5. 5.
    Martin, T., Hsiao, M., Ha, D., Krishnaswami, J.: Denial-of-Service Attacks on Battery-powered Mobile Computers. In: Second IEEE International Conference on Pervasive Computing and Communications (PerCom 2004), Orlando, Florida, March 14-17, 2004, pp. 309–318 (2004)Google Scholar
  6. 6.
    Wang, W., Bhargava, B.: Visualization of Wormholes in Sensor Networks. In: ACM WiSe 2004, October 1 (2004)Google Scholar
  7. 7.
    Smith, D., Mahon, R., Koundinya, S., Panicker, S.: SNTS: Sensor Node Traceback Scheme. In: ACM WiSe 2004, October 1 (2004)Google Scholar
  8. 8.
    Hu, L., Evans, D.: Secure aggregation for wireless networks. In: Workshop on Security and Assurance in Ad hoc Networks (January 2003)Google Scholar
  9. 9.
    Du, W., Deng, J., Han, Y.S., Varshney, P.: A Witness-Based Approach For Data Fusion Assurance In Wireless Sensor Networks. In: IEEE 2003 Global Communications Conference (GLOBECOM), San Francisco, CA, USA, December 1-5 (2003)Google Scholar
  10. 10.
    Przydatek, B., Song, D., Perrig, A.: SIA: Secure Information Aggregation in Sensor Networks. In: Proc. of ACM SenSys 2003 (2003)Google Scholar
  11. 11.
    Wagner, D.: Resilient Aggregation in Sensor Networks. In: ACM Workshop on Security of Ad Hoc and Sensor Networks (SASN 2004), October 25 (2004)Google Scholar
  12. 12.
    Girao, J., Westhoff, D., Schneider, M.: CDA: Concealed Data Aggregation in Wireless Sensor Networks. In: ACM WiSe 2004, October 1 (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Qiang Qiu
    • 1
  • Tieyan Li
    • 1
  • Jit Biswas
    • 1
  1. 1.Institute for Infocomm Research (I2R)Singapore

Personalised recommendations