A Survey of Applications for Anomaly Detection in the IoT: Methods, New Perspectives, and Future
Yingxiang Wang, Rongzuo Guo, Peng Min · 2024
In recent years, with the rapid increase the popularity of cellular Internet of Things (IoT) devices and the sharp increase in the number of end users, ensuring the stability and reliability of IoT systems has become an important challenge. In this context, anomaly detection techniques provide solutions for IoT applications. This paper reviews anomaly detection research applied in the field of the IoT in recent years (mainly from 2018 to 2023) from a technical perspective. First, the causes and basic types of IoT anomalies are introduced to provide a better understanding of the importance of anomaly detection. Second, we focus on research progress in machine learning and edge computing, and propose a general workflow for anomaly detection in the IoT based on edge computing, which we call ECADW. Furthermore, the challenges of anomaly detection in the IoT are proposed, and future research per-spectives are prospected. It is hoped that this review can help researchers to better understand the research direction of this topic and choose interesting anomaly detection techniques.