Security News > 2022 > May > The role of streaming machine learning in encrypted traffic analysis

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.

To help address these problems, many network security and operations teams are relying more heavily on machine learning technologies to identify faults, anomalies, and threats in network traffic.

Later, it's deployed on data that's been saved for analysis.

As network traffic has grown there's a newer alternative called streaming ML. It utilizes a much smaller resource footprint while exceeding the performance requirements of the highest bandwidth networks.

Historically looking into network traffic was done using Deep Packet Inspection, but as more of that traffic is now encrypted, it's becoming less and less useful.

As encryption grows, organizations must rely more heavily on streaming ML and encrypted traffic analysis to gain the necessary visibility into anomalous traffic.

News URL

https://www.helpnetsecurity.com/2022/05/09/ml-encrypted-traffic-analysis/