Overview

Encryption of network traffic plays a vital role ensuring data security and communications privacy, but encryption also limits the visibility IT professionals rely on to both manage networks and detect cyber threats. The Enea Qosmos ML Categorizer helps cybersecurity solution vendors address this challenge.

The Enea Qosmos ML Categorizer is a machine learning-based module for categorizing encrypted traffic. It preserves critical flow classification functions in fully encrypted environments. With full encryption, the limited data that normally remains clear in encrypted flows is no longer visible (TLS Encrypted Client Hello (ECH) or Encrypted Server Name Indication (eSNI), and DNS-over-HTTPS (DoH), for example). As a result, encrypted traffic classification tools who rely on this remaining clear data to function, go blind.

The Enea Qosmos ML Categorizer overcomes this challenge by using supervised and unsupervised machine learning to categorize traffic flows into application and service categories (for example, video call, streaming video, audio call, etc.). This ensures that essential networking and security functions can continue to operate.

The Enea Qosmos ML Categorizer is available as a standard module with the Enea Qosmos ixEngine® – the most widely deployed traffic classification engine in cybersecurity and networking. It delivers crucial intelligence about traffic flowing across a network, including unique insights into encrypted and evasive traffic. The integration of the Enea Qosmos ML Categorizer means that the Enea Qosmos ixEngine retains network visibility in all circumstances, including fully encrypted traffic, allowing cybersecurity solution vendors to maintain their threat detection capabilities and ensure the security of their customers’ networks.