piwik-script

Intern
Secure Software Systems Group

Torsten Krauß

Chair of Software Engineering (Informatik II)
Department of Computer Science
University of Würzburg


Am Hubland, 97074 Würzburg

Informatikgebäude, 1.OG, Room A117
E-Mail: torsten.krauss@uni-wuerzburg.de
Phone: +49 931 31-81983

Occupation

 Since Oct 2021
 		 PhD student in the Secure Software Systems Group at the Chair of Computer Science II - Software-Engineering, University of Würzburg

Research interests

  • AI for Security and Security for AI
  • Security in Large Scale Machine Learning
  • Targeted poisoning attacks & detection in Federated Learning Systems

Projects

Teaching

SS 23

  • Security of Software Systems
  • Seminar IT Security

WS 22/23

  • Introduction to IT Security

SS 22

  • Seminar IT Security

WS 21/22

  • Introduction to IT Security
  • Seminar IT Security

Publications

2024[ to top ]
  • Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated Learning Krauß, Torsten; König, Jan; Dmitrienko, Alexandra; Kanzow, Christian; in To appear soon at the Network and Distributed System Security Symposium (NDSS) (2024).
  • CrowdGuard: Federated Backdoor Detection in Federated Learning Rieger, Phillip; Krauß, Torsten; Miettinen, Markus; Dmitrienko, Alexandra; Sadeghi, Ahmad-Reza; in To appear soon at the Network and Distributed System Security Symposium (NDSS) (2024).
2023[ to top ]
  • MESAS: Poisoning Defense for Federated Learning Resilient against Adaptive Attackers Torsten, Krauß; Alexandra, Dmitrienko; in To appear soon at the ACM Conference on Computer and Communications Security (CCS) (2023).
  • Security of NVMe Offloaded Data in Large-Scale Machine Learning Krauß, Torsten; Raphael, Götz; Dmitrienko, Alexandra; in To appear soon at the European Symposium on Research in Computer Security (ESORICS) (2023).
  • Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations Krauß, Torsten; Dmitrienko, Alexandra; in ArXiv | arXiv.2306.03600 (2023).
2022[ to top ]
  • Close the Gate: Detecting Backdoored Models in Federated Learning based on Client-Side Deep Layer Output Analysis Rieger, Phillip; Krauß, Torsten; Miettinen, Markus; Dmitrienko, Alexandra; Sadeghi, Ahmad-Reza; in ArXiv | arXiv:2210.07714 (2022).