The growing pervasiveness of computerised systems makes our society vulnerable to faults or attacks on such systems. Rigorous software engineering methods and supporting efficient verification tools are crucial to counter this threat.
The objectives are:
The research within Verification and Software Engineering complements and exploits techniques from other research themes. In particular, verification may be applied establish security properties of Secure Multiparty Computations of Blockchains as found in the Cybersecurity and Blockchain theme as already demonstrated by the Center for Program Verification. The dependability and robustness of several CPS and IoT-based systems may be established by Verification and Software Engineering methods.
Artificial Intelligence is increasingly exploited to accelerate and scale current verification techniques. Dually, machine-learned components, such as Deep Neural Networks, are challenging existing algorithmic techniques for verification with exciting research emerging these days towards verifiable and explainable AI.
The rapidly growing application of machine learning techniques in cyber-physical systems leads to better solutions and products in terms of adaptability, performance, efficiency, functionality and usability. However, cyber-physical systems are often safety critical, e.g., self-driving cars or medical devices, and the need for verification against potentially fatal accidents is of key importance.
IoT devices are blending into the infrastructure of both society and our personal lives. However, many of these devices run in uncontrolled, potentially hostile environments, which makes them vulnerable to security attacks. Moreover, with the increasing number of safety critical IoT devices, such as medical and industrial IoT devices, IoT security is a public safety issue.
Building an internet voting system is not easy: The design of new cryptographic protocols is error-prone, and public trust in the elected body is easily threatened. Together with an industrial partner, this project aims to improve the security and quality of the internet voting system and influence regulation on minimum quality requirements for blockchains.
Professor
Aalborg University
Department of Computer Science
E: kgl@cs.aau.dk
T: +45 99 40 88 93
Associate Professor
Technical University of Denmark
DTU Compute
Professor
IT University of Copenhagen
Department of Computer Science
Professor
University of Copenhagen
Department of Computer Science
Professor
University of Southern Denmark
Department of Mathematics and Computer Science
Associate Professor
Copenhagen Business School
Department of Digitalization
Professor
Aarhus University
Department of Computer Science
Associate Professor
Technical University of Denmark
DTU Compute
Assistant Professor
Tecnical University of Denmark
DTU Compute
