DETECTION OF CYBER THREATS IN THE MONITORING AND CONTROL SYSTEMS OF RENEWABLE GENERATION FACILITIES
The main objective of the RENSHIELD project is the development and validation of an Intrusion Detection System (IDS) software solution for the identification of cyber threats in the monitoring and control systems of renewable generation facilities, through Artificial Intelligence Machine learning techniques capable of detecting anomalous patterns in the control traffic of the plant, the control centres and the elements of the own plant.
This solution identifies vulnerabilities, manages risks and detects cyberattacks in the real-time control systems of renewable generation through artificial intelligence techniques that make it possible to detect unknown attacks through the analysis of normal operation, significantly increasing security levels in the energy monitoring and control systems, both at Scadas and energy facility control centres levels, in addition to determining the risk map of the farms and the securitization of their protocols.
The project main challenges are:
- Implementation of an IDS for real-time traffic and packet analysis at the application layer. Tests of packets in control protocols (Modbus, IEC-104, DNP3, …).
- Application of artificial intelligence techniques to the detection of anomalous patterns in cybersecurity.
- Development of a SIEM (Security Information and Event Management) for event correlation, minimising operator interaction.
- Implementation of the system in a probe in the park network with low computational requirements.
These objectives are part of a larger challenge: providing ISOTROL’s clients a sufficient level of proactive safety and meeting the requirements of the most advanced safety standards demanded by international markets.
Implementation period: 2021 – 2023
Technological Corporation of Andalusia (CTA): 1st call 2021 for R&D&I Projects Funding