Radiflow, a provider of cybersecurity solutions for industrial automation networks, and the Fraunhofer Institute of Optronics, System Technologies, and Image Exploitation (IOSB) launched a joint research project for applying advanced machine learning and artificial intelligence to cybersecurity for industrial automation networks.
This applied research will involve evaluating graph-based and semantic approaches for event correlation and context awareness in order to develop these new machine learning and artificial intelligence capabilities. The outcome of this research will be the development of a prototype for an Autonomous Industrial Cybersecurity Assistance System (AICAS) that expands on existing approaches for detecting deviations and anomalies to a baseline of network behaviors on OT networks.
This prototype will be designed to self learn the underlying behaviors an of industrial automation networks and the functions of the connected assets in order to dynamically detect new and unknown cyberthreats. The funding for this research project, which is scheduled to last two years, was granted by the Innovation Authority in Israel and the Federal Ministry of Education and Research in Germany.