The course aims to explore cybersecurity vulnerabilities in the control systems of electric infrastructures. Given the nature of electric power and the typically high speed of electrical processes, managing the operation of such systems is a complex task from both organizational and technical perspectives. For this reason, devices designed for the emergency protection of electrical equipment and automation are of crucial importance to ensure service continuity. The course will analyze the requirements for these devices, their design, and their functionality in order to protect power supply systems while responding to increasing consumer demand and operational needs.
The convergence of information technologies and electric protection systems has triggered a radical transformation, reshaping the fundamental principles of power grid design and management. Enhancing and monitoring control quality is one of the main challenges in the future development of electrical energy and the transition toward Smart Grid systems. The course will therefore examine monitoring techniques and the protection of control systems, which play a key role in the generation, transmission, and distribution of electricity.
The course will cover methodologies for safeguarding control systems, endpoint protection, and monitoring of industrial network traffic, providing implementation examples in a modern electrical substation and defining key terms. This will include monitoring the network as a whole and showing how predictive techniques and online monitoring can help mitigate system criticalities. Tools for modeling networks as graphs will also be explored, along with how Artificial Intelligence enhances control through the use of Graph Neural Networks (GNNs).
The convergence of information technologies and electric protection systems has triggered a radical transformation, reshaping the fundamental principles of power grid design and management. Enhancing and monitoring control quality is one of the main challenges in the future development of electrical energy and the transition toward Smart Grid systems. The course will therefore examine monitoring techniques and the protection of control systems, which play a key role in the generation, transmission, and distribution of electricity.
The course will cover methodologies for safeguarding control systems, endpoint protection, and monitoring of industrial network traffic, providing implementation examples in a modern electrical substation and defining key terms. This will include monitoring the network as a whole and showing how predictive techniques and online monitoring can help mitigate system criticalities. Tools for modeling networks as graphs will also be explored, along with how Artificial Intelligence enhances control through the use of Graph Neural Networks (GNNs).
scheda docente
materiale didattico
a. Identification and analysis of vulnerabilities in Industrial Control Systems (ICS) and SCADA systems used in electrical infrastructures.
b. Study of energy sector-specific communication protocols (e.g. IEC 60870, IEC 61850 and IEC 61970) and their weaknesses.
▪ Endpoint Security and Network Monitoring:
a. Implementation of endpoint security solutions to protect control and automation devices.
b. Monitoring industrial network traffic using traffic analysis tools and intrusion detection systems (IDS).
c. Use of SIEM (Security Information and Event Management) for security event correlation.
▪ Network Modeling and Analysis:
a. Modeling of electrical networks as graphs for interdependencies and vulnerability analysis.
b. Application of Graph Neural Networks (GNN) algorithms for anomaly detection and attack prediction.
▪ Artificial Intelligence and Machine Learning:
a. Use of machine learning techniques for log analysis and detection of anomalous behavior.
b. Implementation of artificial intelligence systems for incident response automation.
c. Use of Meta-Learning algorithms for threat detection.
▪ Predictive Monitoring Techniques:
a. Implementation of predictive monitoring systems to anticipate potential failures and attacks.
b. Use of data analysis techniques to identify suspicious behavior patterns.
▪ Standards and Regulations:
a. In-depth study of cybersecurity regulations and standards specific to the energy sector (e.g. NIST, IEC 62443).
b. Risk management and regulatory compliance.
Springer Nature Switzerland AG
Programma
▪ Vulnerability Analysis:a. Identification and analysis of vulnerabilities in Industrial Control Systems (ICS) and SCADA systems used in electrical infrastructures.
b. Study of energy sector-specific communication protocols (e.g. IEC 60870, IEC 61850 and IEC 61970) and their weaknesses.
▪ Endpoint Security and Network Monitoring:
a. Implementation of endpoint security solutions to protect control and automation devices.
b. Monitoring industrial network traffic using traffic analysis tools and intrusion detection systems (IDS).
c. Use of SIEM (Security Information and Event Management) for security event correlation.
▪ Network Modeling and Analysis:
a. Modeling of electrical networks as graphs for interdependencies and vulnerability analysis.
b. Application of Graph Neural Networks (GNN) algorithms for anomaly detection and attack prediction.
▪ Artificial Intelligence and Machine Learning:
a. Use of machine learning techniques for log analysis and detection of anomalous behavior.
b. Implementation of artificial intelligence systems for incident response automation.
c. Use of Meta-Learning algorithms for threat detection.
▪ Predictive Monitoring Techniques:
a. Implementation of predictive monitoring systems to anticipate potential failures and attacks.
b. Use of data analysis techniques to identify suspicious behavior patterns.
▪ Standards and Regulations:
a. In-depth study of cybersecurity regulations and standards specific to the energy sector (e.g. NIST, IEC 62443).
b. Risk management and regulatory compliance.
Testi Adottati
Cybersecurity in the Electricity Sector: Managing Critical Infrastructure 1st ed. 2019 Edition,Springer Nature Switzerland AG
Modalità Frequenza
Attendance is strongly recommended.Modalità Valutazione
Discussion of course topics with open questions.