PROJECT

Overview: Computer network system administrators need to inspect and analyze network traffic to detect malicious communications, monitor system performance, and provide operational services. However, identifying threats contained within encrypted network traffic, which has become increasingly prevalent, poses a unique set of challenges. Thus, it is imperative to monitor this traffic for threats and malware but do so in a way that maintains privacy. This project aims to develop a machine learning-based system that can accurately detect malware communication in this setting.