Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Transmission Power Range based Sybil Attack Detection Method over Wireless Sensor Networks

  • Seo, Hwa-Jeong (Department of Computer Engineering, Pusan National University) ;
  • Kim, Ho-Won (Department of Computer Engineering, Pusan National University)
  • Received : 2011.09.09
  • Accepted : 2011.11.15
  • Published : 2011.12.31
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Abstract

Sybil attack can disrupt proper operations of wireless sensor network by forging its sensor node to multiple identities. To protect the sensor network from such an attack, a number of countermeasure methods based on RSSI (Received Signal Strength Indicator) and LQI (Link Quality Indicator) have been proposed. However, previous works on the Sybil attack detection do not consider the fact that Sybil nodes can change their RSSI and LQI strength for their malicious purposes. In this paper, we present a Sybil attack detection method based on a transmission power range. Our proposed method initially measures range of RSSI and LQI from sensor nodes, and then set the minimum, maximum and average RSSI and LQI strength value. After initialization, monitoring nodes request that each sensor node transmits data with different transmission power strengths. If the value measured by monitoring node is out of the range in transmission power strengths, the node is considered as a malicious node.

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References

  1. T. Karalar and J. Rabaey., An rf tof based ranging implementation for sensor networks, in Communications, 2006. ICC '06. IEEE International Conference on, (2006), 3347-3352
  2. S. Gezici, Z. Tian, G. Giannakis, H. Kobayashi, A. Molisch, H. Poor, and Z. Sahinoglu, Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks, Signal Processing Magazine, IEEE, (2005), 70-84.
  3. A. Nasipuri and K. Li, A directionality based location discovery scheme for wireless sensor networks, in WSNA '02: Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications. (2002), 105-111
  4. R.-H. Wu, Y.-H. Lee, H.-W. Tseng, Y.-G. Jan, and M.-H. Chuang, Study of characteristics of rssi signal, in Industrial Technology, 2008. ICIT 2008. IEEE International Conference on, (2008), 1-3.
  5. J. R. Douceur., The sybil attack, In IPTPS '01:Revised Papers from the First International Workshop on peer-to-peer systems, (2002), 251-260.
  6. Fereshteh Amini, Jelena Mišic, and Hossein Pourreza., Detection of Sybil attack in beacon enabled IEEE 802.15.4 Networks., Wireless Communications and Mobile Computing Conference, 2008. IWCMC'08. International, (2008), 1058-1063.
  7. M. Demirbas and Y. Song., An RSSI-based Scheme for Sybil Attack Detection in Wireless Sensor Networks., International Symposium on a World of Wireless, Mobile and Multimedia Networks, (2006), 564-570.
  8. L. Shaohe, W. Xiaodong, Z. Xin, Z. Xingming, Detecting the Sybil Attack Cooperatively in Wireless Sensor Networks, Computational Intelligence and Security, 2008. CIS '08. International Conference on, (2008), 442-446.
  9. ChipCon Inc. http://www.chipcon.com
  10. J.L. Hill, D.E. Culler, Mica: A wireless platform for deeply embedded networks,IEEE Micro 22 (6) (2002) 12-24. https://doi.org/10.1109/MM.2002.1134340
  11. M. Corporation, Tmote sky:Ultra low power IEEE 802.15.4 compliant wireless sensor module data sheet, (2006).
  12. G.Zhou, T.He, S. Krishnamurthy, and J. A. Stankovic. Impact of radio irregularity on wireless sensor networks., In MobiSys '04: Proceedings of the 2nd international conference on Mobile systems, applications, and services, (2004), 125-138
  13. TinyOS, http://www.tinyos.net/