Blog

  • Detecting Changes in Encrypted Traffic with AI: Introducing MFWDD

    In the rapidly evolving world of network traffic monitoring, machine learning (ML) has become a cornerstone for classification tasks. But as network protocols evolve and data patterns shift, maintaining the reliability of ML models is a constant challenge. Our research team at the Czech Technical University in Prague, together with CESNET, developed a solution to tackle these challenges head-on: Model-based Feature Weight Drift Detection (MFWDD).