D!ARC Network veröffentlicht vom Universitätszentrum D!ARC – Digital Age Research Center

Increasing Safety in Pyhsical Human-Robot Interaction (pHRI) with Capacitive Proximity and Tactile Sensors

12. Dezember  2023     12:30- 14:00Uhr       HS V.1.34

Dipl.-Ing. Serkan Ergun, BSc

(Department of Smart System Technologies (SST) – Sensors, Actuators & Modular Robotics (SmArT) Group)

Manufacturing sustainability: A critique of the socio-technical construction of marketing insights

07. November 2023    14:00 – 15:30 Uhr     S.0.05

Laura Bruschi
PhD Candidate in Sociology and Methodology of Social Research (SOMET)
NASP – University of Milan, University of Turin
Department of Social and Political Sciences

„Game Theory and Cybersecurity- Applications, Challenges, Limits“

Dipl.-Ing. Jasmin Wachter, BSc, BA 
Institut Artificial Intelligence and Cybersecurity im Forschungsprojekt ‚Responsible Safe and Secure Robotic Systems Engineering (SEEROSE)‘
1.30 – 3:00 pm 
Inspire Lab / B12a

„Statistical Tools and Techniques in Side-channel Cryptanalysis“

13. Juni  2023   13:00 – 14:30 Uhr   Outdoor HS Kosuta (in case of rain: N.2.57)

Aakash Chowdhury, MSc (Cybersecurity Research Group)


Side-channel cryptanalysis (SCA) is a critical research area in cybersecurity that aids in the development of countermeasures against attackers who are permitted to extract secret information from cryptographic devices such as smart cards and mobile phones. Evaluating such countermeasures necessitates determining the amount of information leaked by the device. To serve this purpose, information extraction approaches that have been published to date effectively combine a „leakage model“ with a „distinguisher“. In the scope of statistical analysis against cryptographic devices, Mutual Information (MI) has been employed as a generic distinguisher by the side channel community for numerous years to measure the probabilistic dependency. My earlier focus was to find a nonparametric estimation approach to MI that allow us to capture the susceptibility of a cryptographic implementation in an embedded device. Presently, I have been working on developing efficient-statistical tools for multivariate leakage detection testing.