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Wireless Communications and Mobile Computing
Volume 2018, Article ID 8961239, 11 pages
https://doi.org/10.1155/2018/8961239
Research Article

A Security Framework for Cluster-Based Wireless Sensor Networks against the Selfishness Problem

Department of Electrical and Computer Engineering, Pusan National University, Busan, Republic of Korea

Correspondence should be addressed to Younghwan Yoo; rk.ca.nasup@omomy

Received 3 March 2018; Revised 30 May 2018; Accepted 26 June 2018; Published 10 July 2018

Academic Editor: Houbing Song

Copyright © 2018 Zeba Ishaq et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Over the last few decades, Cluster-Based Wireless Sensor Networks (CBWSNs) have played a crucial role in handling various challenges (load balancing, routing, network lifetime, etc.) of large scale Wireless Sensor Networks (WSNs). However, the security becomes a big problem for CBWSNs, especially when nodes in the cluster selfishly behave, e.g., not forwarding other nodes’ data, to save their limited resources. This may make the cluster obsolete, even destroying the network. Thus, a way to guarantee the secure and consistent clusters is needed for proper working of CBWSNs. We showed that the selfishness attack, i.e., passive attack or insider attack, in CBWSNs can cause severe performance disaster, when particularly a cluster head node becomes selfish. In order to prevent this situation, this paper proposes a security framework that involves a novel clustering technique as well as a reputation system at nodes for controlling selfishness, making them cooperative and honest. The novelty of the clustering comes from the existence of inspector node (IN) to monitor the cluster head (CH) and its special working style. The experimental results showed that the proposed security framework can control the selfishness and improve the security of the clusters.