On specification-based cyber-attack detection in smart grids
Ömer Sen, Dennis van der Velde, Maik Lühman, Florian Sprünken, Immanuel Hacker, Andreas Ulbig, Michael Andres, Martin Henze
Abstract
Abstract The transformation of power grids into intelligent cyber-physical systems brings numerous benefits, but also significantly increases the surface for cyber-attacks, demanding appropriate countermeasures. However, the development, validation, and testing of data-driven countermeasures against cyber-attacks, such as machine learning-based detection approaches, lack important data from real-world cyber incidents. Unlike attack data from real-world cyber incidents, infrastructure knowledge and standards are accessible through expert and domain knowledge. Our proposed approach uses domain knowledge to define the behavior of a smart grid under non-attack conditions and detect attack patterns and anomalies. Using a graph-based specification formalism, we combine cross-domain knowledge that enables the generation of whitelisting rules not only for statically defined protocol fields but also for communication flows and technical operation boundaries. Finally, we evaluate our specification-based intrusion detection system against various attack scenarios and assess detection quality and performance. In particular, we investigate a data manipulation attack in a future-orientated use case of an IEC 60870-based SCADA system that controls distributed energy resources in the distribution grid. Our approach can detect severe data manipulation attacks with high accuracy in a timely and reliable manner.