The CYLCOMED project addresses the overall ambitious goal of strengthening the cybersecurity of connected, in vitro diagnostic and software as medical devices (CMDs, IVDs, SaMD), maintaining their performance and safety for patients and preserving or enhancing the confidentiality, integrity and availability of private data. CYLCOMED will deliver a comprehensive set of tools covering, among others, AI-based CMD behavioral analysis (covering network traffic analysis with unsupervised Deep Learning capable of detecting a wide range of cybersecurity incidents), and AI-powered log monitoring solution that uses unsupervised NLP (natural language processing)-based methods for the detection of different kinds of anomalies in logs (e.g., those indicating attacks like DoS or spoofing, or failures due to misconfigurations).

Martel will participate in CYLCOMED by leading the dissemination, communication, and community building activities.