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

Rajani Muraleedharan; Xiang Ye; Lisa Ann Osadciw

doi:10.1117/12.778219

3 April 2008 Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence

Rajani Muraleedharan, Xiang Ye, Lisa Ann Osadciw

Proceedings Volume 6980, Wireless Sensing and Processing III; 69800F (2008) https://doi.org/10.1117/12.778219
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

Citation Download Citation

Rajani Muraleedharan, Xiang Ye, and Lisa Ann Osadciw "Prediction of Sybil attack on WSN using Bayesian network and swarm intelligence", Proc. SPIE 6980, Wireless Sensing and Processing III, 69800F (3 April 2008); https://doi.org/10.1117/12.778219

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