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D. I. Curiac, O. Banias, F. Dragan, C. Volosencu and O. Dranga, “Malicious Node Detection in Wireless Sensor Networks Using an Autoregression Technique,” 3rd International Conference on Networking and Services, 19-25 June 2007. doi:10.1109/ICNS.2007.79

has been cited by the following article:

• TITLE: Malicious Node Detection Using Confidence Level Evaluation in a Grid-Based Wireless Sensor Network

  AUTHORS: Min-Cheol Shin, Yoon-Hwa Choi

  KEYWORDS: Sensor Networks; Malicious Node Detection; Grid-Based WSN; Faults; Confidence Levels

  JOURNAL NAME: Wireless Sensor Network, Vol.5 No.3, March 29, 2013

  ABSTRACT: In this paper, we present a malicious node detection scheme using confidence-level evaluation in a grid-based wireless sensor network. The sensor field is divided into square grids, where sensor nodes in each grid form a cluster with a cluster head. Each cluster head maintains the confidence levels of its member nodes based on their readings and reflects them in decision-making. Two thresholds are used to distinguish between false alarms due to malicious nodes and events. In addition, the center of an event region is estimated, if necessary, to enhance the event and malicious node detection accuracy. Experimental results show that the scheme can achieve high malicious node detection accuracy without sacrificing normal sensor nodes.