Deep Learning-Based Information Security

Abstract

Abstract. With the rapid development of network technology, information security is facing increasingly complex challenges. Deep learning technology, due to its strong capabilities in data processing and pattern recognition, has become a key technology to improve the detection efficiency and accuracy in the field of information security. This paper delves into the application of deep learning in various aspects such as malware detection, network intrusion identification, User and Entity Behavior Analytics (UEBA), privacy protection technology, model explainability, and network security vulnerability detection, and proposes deep learning-based information security methods. Through experimental validation, our methods have outperformed traditional machine learning models in multiple evaluation metrics, providing new solutions for the field of information security. In the future, we will continue to explore new applications of deep learning in the field of information security to cope with the ever-changing network security threats.