Anomaly Detection Based on Deep Learning: Insights and Opportunities

Abstract

With the advent of the 5G/6G and Big Data, the network has become indispensable in people’s lives, and Cyber security has turned a relevant topic that people pay attention to. For Cyber security, anomaly detection, a.k.a. outlier detection or novelty detection, is one of the key points widely used in financial fraud detection, medical diagnosis, network security, and other aspects. As a hot topic, deep learning-based anomaly detection has been studied by more and more researchers. For such an objective, this article aims to classify anomaly detection based on deep learning, pointing out the problem and the principle, advantages, disadvantages, and application scenarios of each method, and describe possible future opportunities to address challenges.