Design of Anomaly Detection Algorithm for Intelligent Data Acquisition Terminal of Internet of Things Based on Deep Learning
Liyou Fang · 2023
Anomaly detection is the identification of items, events, or observed values that do not meet the expected situation or other conditions in the data set. In this paper, an anomaly detection algorithm of IoT (Internet of Things) intelligent data acquisition terminal based on deep learning is proposed. In the case design, the Text-CNN (Text-convolutional Neural Network) is adopted as the algorithm of supervised detection scheme. Split the collected IoT data set to obtain network traffic data of a plurality of different devices, and label these data in categories; Input the data into the established Text-CNN algorithm model through NLP; In the sample category output module, train the model, save the trained model, test it, and output the sample category. The test results show that the algorithm proposed in this chapter is superior to other literature algorithms in anomaly detection, and it is suitable for anomaly detection of complex data, especially high-dimensional data.