SBA-K1: FP2 AREA 4
The aim of this project is to focus developing mathematically guar- anteed foundations and related primitives for exploring and adapting solutions for vulnerability research in software security and privacy, computation optimization, and assured quality of software.
Therefore, within this project, we concentrate on three interconnected topics: (i) a mathematical framework for the science of security, including discrete mathematical models for software security, privacy, and anonymity (ii) combinatorial arrays, algorithms, and optimization techniques that can be used as an ad-hoc methodology to provide the necessary constructions for the problem of information security addressed in the area and (iii) expand the horizons of combinatorial security testing.
Area 4 of the SBA-K1: FP2 project is funded as part of the COMET K1: FP2 Program Line: Competence Centers for Excellent Technologies by the Austrian Research Promotion Agency (FFG)
In this joint project, we aim to achieve trustable architectures with acceptable residual risk for electric, connected, and automated (ECA) cars with our numerous partners, such as AVL, TU Graz, IFAT, and many more.
As driverless transportation via automated vehicles becomes more relevant and significant, MATRIS Research Group focuses on active safety systems of automated vehicles through functional safety should be evaluated during the development and runtime by providing methods and tools such as a Monitoring Device. Therefore, the H2020 EU project Architect ECA2030 aims to offer solutions to safety issues through methods and models. In this project, we start from TRL (Technology Readiness Level) 1 by creating a concept with the help of basic and applied research and continue until TRL 4 in which we and our partners design and develop models, components, processes, and conduct lab testing in a simulated environment. Thus, we can determine if our project might be able to provide applicable solutions in real life based on modeled systems within this project.
ArchitectECA2030 is funded as part of the H2020 EU project.
DYNAMO – COMBINATORIAL INTERACTION MATCHING WITH APPLICATIONS TO SECURITY AND DATA ANALYSIS
Our partnership with NIST on the DYNAMO project aims to design and develop new combinatorial methods from discrete mathematics and apply the explored novel analysis techniques in the domain of cybersecurity to improve current major societal issues connected to technological innovations: such as user privacy, identifying risk factors in medical and financial data through data analysis.
On the one hand, our goal is to advance the underlying combinatorial methods towards a more generic reasoning framework in terms of pattern matching within the theoretical scope of the project. On the other hand, we focus on pattern recognition and identification techniques for data sets arising in the medical or financial domain.
DYNAMO is funded as part of the Measurement Science and Engineering (MSE) Research Grant Programs of the US Department of Commerce, National Institute of Standards and Technology (NIST).