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Proceedings Paper

Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence
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Paper Abstract

Security in wireless sensor networks is typically sacrificed or kept minimal due to limited resources such as memory and battery power. Hence, the sensor nodes are prone to Denial-of-service attacks and detecting the threats is crucial in any application. In this paper, the Sybil attack is analyzed and a novel prediction method, combining Bayesian algorithm and Swarm Intelligence (SI) is proposed. Bayesian Networks (BN) is used in representing and reasoning problems, by modeling the elements of uncertainty. The decision from the BN is applied to SI forming an Hybrid Intelligence Scheme (HIS) to re-route the information and disconnecting the malicious nodes in future routes. A performance comparison based on the prediction using HIS vs. Ant System (AS) helps in prioritizing applications where decisions are time-critical.

Paper Details

Date Published: 3 April 2008
PDF: 10 pages
Proc. SPIE 6980, Wireless Sensing and Processing III, 69800F (3 April 2008); doi: 10.1117/12.778219
Show Author Affiliations
Rajani Muraleedharan, Syracuse Univ. (United States)
Xiang Ye, Syracuse Univ. (United States)
Lisa Ann Osadciw, Syracuse Univ. (United States)


Published in SPIE Proceedings Vol. 6980:
Wireless Sensing and Processing III
Sohail A. Dianat; Michael D. Zoltowski, Editor(s)

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