Anomaly Detection in Electronic Shelf Label Systems

Abstract

This paper proposes a lightweight, fast and efficient method for the detection of jamming attacks, interference, and other anomalies in electronic shelf label (ESL) systems and wireless sensor networks (WSNs) with periodic data transmission. The proposed method is based on the thresholding technique, which is applied to selected parameters of traffic and allows discrimination of random failures from anomalies and intrusions. It does not require the installation of additional hardware and does not create extra communication costs; its computational requirements are negligible, since it is based on statistical methods. Herein recommendations are provided for choosing a thresholds type. Extensive simulations, made by Castalia simulator for WSNs, show that the proposed method has superior accuracy compared to existing algorithms.