The course covers safety and security aspects in cyber-physical systems. Particularly, time-critical systems in critical infrastructure and autonomous systems are studied, where cyberattacks and errors can have physical consequences. A large part of the course is devoted to the presentation of basic principles and methods for modeling, analysis and detection of errors and cyberattacks in dynamic systems. In particular, the following is studied
- Documented attacks against cyber-physical systems, system architectures, safety and accessibility, risk management and attack-space in cyber-physical systems.
- Model-based quantification of physical consequences of errors and cyberattacks, discrete-time dynamic systems (linear state models), observers, strong observability and detectability.
- Model and data-based error detection, fault identification and redundancy, parity space methods, observer based methods, setting of threshold.
- Statistical anomaly detection, hypothesis testing, Neyman-Pearson's lemma, generalised likelihood ratio (GLR), Bayes' theorem, principal component analysis (PCA), detection of abrupt process changes, cumulative sum test (CUSUM), machine-learning based methods.