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CLC number: TP393

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Received: 2008-03-13

Revision Accepted: 2008-06-06

Crosschecked: 2008-12-26

Cited: 5

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.2 P.279-289


WAPN: a distributed wormhole attack detection approach for wireless sensor networks

Author(s):  Fan-rui KONG, Chun-wen LI, Qing-qing DING, Guang-zhao CUI, Bing-yi CUI

Affiliation(s):  Department of Automation, Tsinghua University, Beijing 100084, China; more

Corresponding email(s):   kongfr@mails.tsinghua.edu.cn

Key Words:  Wireless sensor networks (WSNs), Security, Wormhole detection

Fan-rui KONG, Chun-wen LI, Qing-qing DING, Guang-zhao CUI, Bing-yi CUI. WAPN: a distributed wormhole attack detection approach for wireless sensor networks[J]. Journal of Zhejiang University Science A, 2009, 10(2): 279-289.

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%A Fan-rui KONG
%A Chun-wen LI
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%A Guang-zhao CUI
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%D 2009
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820178

T1 - WAPN: a distributed wormhole attack detection approach for wireless sensor networks
A1 - Fan-rui KONG
A1 - Chun-wen LI
A1 - Qing-qing DING
A1 - Guang-zhao CUI
A1 - Bing-yi CUI
J0 - Journal of Zhejiang University Science A
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SP - 279
EP - 289
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Y1 - 2009
PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.A0820178

As the applications of wireless sensor networks (WSNs) diversify, providing secure communication is emerging as a critical requirement. In this paper, we investigate the detection of wormhole attack, a serious security issue for WSNs. Wormhole attack is difficult to detect and prevent, as it can work without compromising sensor nodes or breaching the encryption key. We present a wormhole attack detection approach based on the probability distribution of the neighboring-node-number, WAPN, which helps the sensor nodes to judge distributively whether a wormhole attack is taking place and whether they are in the influencing area of the attack. WAPN can be easily implemented in resource-constrained WSNs without any additional requirements, such as node localization, tight synchronization, or directional antennas. WAPN uses the neighboring-node-number as the judging criterion, since a wormhole usually results in a significant increase of the neighboring-node-number due to the extra attacking link. Firstly, we model the distribution of the neighboring-node-number in the form of a Bernoulli distribution. Then the model is simplified to meet the sensor nodes’ constraints in computing and memory capacity. Finally, we propose a simple method to obtain the threshold number, which is used to detect the existence of a wormhole. Simulation results show that WAPN is effective under the conditions of different network topologies and wormhole parameters.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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