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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 5 Issue 7 ijcatr05071003

IJCATR Volume 5 Issue 7

A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes

Abdolreza Andalib Mojtaba Jamshidi Farahnaz Andalib Davod Momeni
10.7753/IJCATR0507.1003
keywords : Wireless Sensor Networks, Sybil attack, Lightweight algorithm, Sink nodes

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Considering the application of wireless sensor networks in critical area, such as battlefields, establishing security in these networks is of utmost importance. One of the most serious and dangerous attack against these networks is Sybil attack. In this attack, a malicious hostile node creates multiple fake identities simultaneously. This misleads legitimate nodes and, by mistake, they assume each of these identifiers as real separate nodes. In this attack, malicious hostile node attracts so heavy traffic that can dramatically disrupt routing protocols which has devastating effects on the network functions such as data integration, voting, and resource allocation. The current research proposes a new lightweight algorithm for detecting Sybil attack in Mobile Wireless Sensor Networks using sink nodes. The proposed algorithm is implemented to be assessed in terms of detection and error rates efficiency in a series of experiments. Comparison of the experiment results with the results of other available algorithms revealed optimal performance of the proposed algorithm.
@artical{ 572016ijcatr05071003,
Title = "A Lightweight Algorithm for Detecting Sybil Attack in Mobile Wireless Sensor Networks using Sink Nodes",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="7",
Pages ="433 - 438",
Year = "2016",
Authors =" Abdolreza Andalib Mojtaba Jamshidi Farahnaz Andalib Davod Momeni "}
  • This paper proposes a new algorithm for detecting Sybil attack in Mobile Wireless Sensor Networks.
  • The proposed algorithm uses sink nodes to detect Sybil nodes.
  • The proposed algorithm is implemented to be assessed in terms of detection and error rates.
  • The experiment results show the high performance of the proposed algorithm.
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