Research

AMfoRS

Architectures and Methods for Resilient Systems
since 2015


Research topics

photo AMfoRS

The AMfoRS team targets crucial challenges regarding resilient integrated systems. Our goal is twofold: guarantee that systems will not behave unexpectedly and ensure a substantial level of robustness and security. Our work aims at increasing the synergies between verification technologies and activities on the design and validation of reliable, safe and secure integrated systems, with a focus on digital parts.
The expected outcomes of our research include methods, tools and hardware blocks necessary to justify trust in increasingly complex integrated systems and even cyber-physical systems.
The team takes part in several scientific challenges identified not only at the laboratory level, but also in the Research "poles" of University Grenoble-Alpes (especially the MSTIC pole) and more generally at the national level (French strategic directions) and international level (in particular European H2020 priorities).


Last publications

Skaf A., Ezzadeen M., Benabdenbi M., Fesquet L., Adjustable Precision Computing Using Redundant Arithmetic, Workshop on Approximate Computing (AxC'2019), Florence, ITALY, 2019
 
Kooli M., Di Natale G., Bosio A., Memory-Aware Design Space Exploration for Reliability Evaluation in Computing Systems, Journal of Electronic Testing: Theory and Applications, Ed. Springer , Vol. , DOI: 10.1007/s10836-019-05785-0, 2019
 
Plassan G., Morin-Allory K., Borrione D., Mining Missing Assumptions from Counter-Examples, Transactions on Embedded Computing Systems (TECS), Ed. ACM, NY, USA, Vol. 18, No. 1, DOI: 10.1145/3288759, 2019
 
Martin H., Peris-Lopez P., Di Natale G., Taouil M., Hamdioui S., Enhancing PUF Based Challenge-Response Sets by Exploiting Various Background Noise Configurations, MDPI Electronics, Ed. MDPI, Vol. 8, No. 2, DOI: 10.3390/electronics8020145, 2019
 
Vatajelu I., Di Natale G., High-Entropy STT-MTJ-based TRNG, IEEE Transactions on Very Large Scale Integration (VLSI) Systems , Ed. IEEE, Vol. , DOI: 10.1109/TVLSI.2018.2879439, 2019
 
Annual activity report