AI on Network data
Within the AI for network track, ML techniques are applied on network data with the goal to secure or optimise wired and wireless network communication. IDLab covers following topics:
- The characterization of RF environments to identify the presence of interference (sub-GHz, Wi-Fi bands, satellite), optimize the wireless performance (Wi-Fi, Satellite, UWB, …) and identify and recognize human activities (via UWB radar).
- Twin-based wireless network management,to manage, configure and gain insights into wireless-wired networks and real-time network behaviour.
- Cybersecurity, building AI-driven network intrusion detection systems, classifying network traffic into regular and anomalous, potentially dangerous network flows.
AI on network data mainly translates to use cases within the domains of:
Telecommunication
e.g., zero-touch management of wireless-wired networks, optimise wireless networks (e.g., MAC/PHY parameters configuration)
Cybersecurity
e.g., building a distributed network intrusion detection system that can operate in near real-time.
