Adaptive False Data Filtering Method for Sensor Networks Based on Fuzzy Logic and Commutative Cipher

Abstract

Wireless sensor networks are vulnerable to false data injection attacks in which attackers inject false reports into the networks through compromised nodes with the goal of deceiving sinks or depleting the resources of the relaying nodes. This paper presents an adaptive false data filtering method, which is based on the commutative cipher-based probabilistic filtering scheme. A security parameter, which determines the required number of participating nodes in each report generation, is controlled by a fuzzy rule-based system with the consideration of the factors that reflect the network status. The proposed method can be more energy-efficient than the base scheme in both legitimate and false traffic. The effectiveness of the proposed method is shown at the end of the paper with simulation results.