Volume 11, Number 2

An Enhancement of Cluster-Based False Data Filtering Scheme Through Dynamic Security Selection in Wireless Sensor Networks

  Authors

Jungsub Ahn and Taeho Cho, Sungkyunkwan University, Republic of Korea

  Abstract

Today, wireless sensor networks (WSNs) are applied to various industries such as building automation, medical, security, intelligent agriculture, and disaster monitoring. A WSN consists of hundreds to thousands of tiny sensor nodes that perform monitoring tasks. A small sensor node has a limited amount of internal memory and energy resources. Sensor nodes are used to detect a variety of data in specific environmental areas. As a result, WSN should be energy efficient. Sensor nodes are vulnerable to false report injection attacks because they are deployed in an open environment. A false report injection attack consumes the limited energy of a node more quickly and confuses the user. CFFS has been proposed to prevent such an attack using a method of en-route filtering false reports by dividing nodes into clusters. However, the CFFS scheme is vulnerable for repeated false report injection attacks. In this paper, we propose an approach to prolong the WSN lifetime by adjusting the dynamic security threshold value and using a fuzzy logic-based key redistribution selection of cluster head nodes. The proposed method increases the detection rate for repeated false report injection attacks by adding the additional key distribution phase in the existing method. The experimental results show that the energy efficiency of the proposed method was increased by 40.278%.

  Keywords

False Report Injection Attack, Cluster-based False Data Filtering, Network Lifetime Extension, FuzzyLogic System