The role of streaming machine learning in encrypted traffic analysis - Help Net Security

Organizations now create and move more data than at any time ever before in human history. Network traffic continues to increase, and global internet bandwidth grew by 29% in 2021, reaching 786 Tbps. In addition to record traffic volumes, 95% of traffic is now encrypted according to Google. As threat actors continue to evolve their tactics and techniques (for example, hiding attacks in encrypted traffic), securing organizations is becoming more challenging. To help address these problems, many network security and operations teams are relying more heavily on machine learning (ML) technologies to identify faults, anomalies, and threats in network traffic.