Research on Vulnerability Mining Method Based on Artificial Intelligence in Internet of Things

In recent years, with the continuous development of computer technology, Internet of Things (IoT) technology has been widely used in various fields and has played an important role in various industries. The Internet of Things is responsible for information transmission and storage, and once there are network security issues, it will bring huge disasters to various industries. Detecting vulnerabilities in the Internet of Things is an urgent problem that needs to be addressed. In order to improve the efficiency of IoT vulnerability detection, this paper designs an IoT vulnerability mining solution based on the LSTM algorithm. The designed artificial intelligence IoT vulnerability mining algorithm uses deep learning for identification, and this framework includes steps such as data collection, data learning, and data detection. The results show that after comparing three models: LSTM, SeqGAN, and WGAN, the LSTM algorithm exhibits the highest accuracy.