An Overview of Applications of Machine Learning in Encrypted Traffic Analysis for Cyber Security
Course Description
Only a decade ago, encrypted traffic was primarily utilised by financial institutions and specific organisations, such as public sector agencies, for the login pages of security-conscious websites and services. However, in recent years, the adoption of encrypted traffic has expanded significantly to encompass almost all web-based services. Unfortunately, this growth has also facilitated the rise of unlawful activities, making encrypted traffic the default protocol for communication. Consequently, traditional approaches to Network Visibility and Network Forensics have encountered substantial challenges in isolating or detecting suspicious network activities. Machine learning-based approaches have emerged as crucial methods for detecting and containing encrypted malicious traffic to address suspicious network activities. This tutorial provides a comprehensive overview of the applications of Machine Learning in Encrypted Traffic Analysis (ETA) for Cyber Security.
