CONTINGENT: Advanced Solution to Enhance Cyber Resilience Through Machine Learning Techniques

The CONTINGENT project, developed under the CYRENE H2020 (Horizon 2020) project [1], is a pioneering initiative by FAVIT [2] to bolster cybersecurity in evolving Information and Communication Technologies (ICT) systems. The project’s focus is on enhancing cyber resilience through advanced Machine Learning (ML) techniques, addressing the increasing need for robust cybersecurity solutions in various sectors like transport, healthcare, and energy. CONTINGENT aims to develop and deploy a suite of cybersecurity services/products for Supply Chain Services, utilizing HoneyPots (HPs) and Digital Twins (DTs) [3] to gather rich, actionable data [4]. These tools simulate vulnerable services, attracting and analyzing potential cyber threats. The collected data feeds into ML algorithms, enabling real-time analysis and identification of unknown attack patterns, ensuring proactive defense against cyber threats. The proposed solution includes a set of docker containers with configurable HP services and ML models, integrated within the CYRENE platform. This integration will facilitate seamless data sharing and visualization through CYRENE’s dashboard, enhancing overall cybersecurity measures. Through CONTINGENT, FAVIT addresses significant technical challenges, including managing vast log data, ensuring easy integration across environments, and adhering to CYRENE’s guidelines. This project represents a significant step forward in securing ICT systems against evolving cyber threats, ensuring the resilience and safety of critical infrastructures and data.