Launched IDUNN, the European research project for cybersecurity

This is a cutting-edge research project with a budget of more than five million euros and a duration of three years, in which Spanish, Finnish and German partners participate. The objective of the project is to create a cognitive detection solution so that the operational technologies present in the industrial sector are resistant to cyber attacks.
The industrial sector faces specific security challenges in a context in which data is becoming the main engine of companies and in which, in terms of threats and cyber-attacks, progress is increasing. Faced with this reality, the European IDUNN project started, with a duration of three years and a budget of €5,159,000, with the objective of researching and developing a cognitive detection system (an artificial intelligence application that ‘learns’ by itself to interpret new attacks), to analyze and deal with new cyber threats . This project has been funded under the Horizon 2020 program of the European Commission, the most competitive funding program in Europe for the development of new knowledge.
Ten European partners participate in the project: Ikerlan -leading-, Grupo S21 Sec , Clúster GAIA and Fagor Arrasate (Basque Country), Mondragon Assembly , which will participate from its plant in France in the use tests; oulun Yliopisto and Bittium Oy (Finland); and the German organizations Offis EV, Din Deutsches Institute Fuernormun and Cosynth . Mondragon Goy School Politeknikoa and Bittium Safemove will also participate as linked third parties.
The main objective of IDUNN is focused on providing a reliable solution to any industry, making its ICT systems resistant to cyber attacks, developing solutions that respond to their specific needs. To achieve this, the project will create a security shield in the form of initial tools, methodologies, microservices and standards compatible with any ICT supply chain. Thus, in the event of a possible incident, the IDUNN system will know how to act quickly to alleviate it and, in turn, will generate a cognitive learning process, which reduces human intervention and provides forecasting capabilities.
The IDUNN project will develop a complete and integrated solution, modular and adaptable to different scenarios. To this end, over the next few years, work will be carried out on 3 specific use cases: automotive manufacturing, gas valve manufacturing and industrial IOT controllers (application of the internet of things in industry).