Security Computer Database Updating System Based on Deep Learning Algorithm

With the advent of the network era, more and more sensitive information is stored in database systems. As the basic software for information storage and processing, the security of databases is crucial to the safety protection of sensitive information, and once such sensitive information is leaked or obtained by unscrupulous elements, it is likely to lead to very serious consequences. Therefore, this paper is based on deep learning algorithms to study the security computer database update system. The paper begins with a brief description of the secure computer data classification and data hybrid authorisation management, followed by the system design of the algorithm, the security model testing system and the data processing module, and concludes with a systematic analysis of the algorithm comparison, the model management module and the prediction results.