A lightweight algorithm for detecting mobile Sybil nodes in mobile wireless sensor networks. (November 2017)

• Record Type: Journal Article
• Authors: Jamshidi, Mojtaba; Zangeneh, Ehsan; Esnaashari, Mehdi; Meybodi, Mohammad Reza
• Is Part Of: Computers & electrical engineering. Volume 64(2017)
• Page Start: 220
• Page End: 232
• Publication Date: 2017-11
• Subjects: Wireless sensor network -- Malicious node -- Sybil node -- Watchdog Node; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.12.011
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: Utilizing a few Watchdog Nodes which monitor the network traffic and nodes' mobility passively to detect Sybil nodes. Assigning bitwise tags to mobile sensor nodes, using Watchdog Nodes, considering their movement behaviors. Eliminating memory, computation, and communication overheads of sensor nodes for detecting Sybil nodes. Abstract: Sybil attack is a well-known attack against wireless sensor networks (WSNs) in which a malicious node attempts to propagate multiple identities. This attack is able to affect routing protocols negatively as well as many other operations such as voting, data aggregation, resource allocation, misbehavior detection, etc. In this paper, a light weight, dynamic algorithm is proposed for detecting Sybil nodes in mobile wireless sensor networks. The proposed algorithm uses Watchdog Nodes first to label ( bit_label ) mobile nodes based on their movement behaviors, and then detects Sybil nodes according to the labels, during detection phase. As all Sybil nodes belong to a single device (malicious node), they move together, hence, they would have identical bit_label . This fact is used to detect Sybil nodes in the detection phase. The proposed algorithm is simulated using JSIM simulator and simulation results are compared with existing algorithms in terms of true detection and false detection rates. The results show that the proposed algorithm is able to identify more than 94% of Sybil nodes, while false detection rate is 0%. Graphical abstract: