On the Trend and Problems of IoT Data Anomaly Detection

With the rapid development of Internet technology, the Internet of Things is also constantly developing and progressing. More and more areas are starting to see connected devices, and more and more data is being generated by them. Effective data analysis and detection can prevent network intrusions and predict future trends. In recent years, with the breakthrough of computer technology, machine learning has shown good results in anomaly detection. Therefore, the research on anomaly detection of Internet of Things data has gradually increased and deepened. This work analyzes and summarizes the research trends in this field. First, we use keyword search to export articles in this field. Then we use the tool bibliometrix to generate statistical charts and trend charts for exported articles. At last, we analyze and summarize the generated two graphs. In the process of analysis, we have a detailed description of the phenomenon and a cause analysis. Finally, the future research direction in this field is derived.