Samuel Weiser

Dipl.-Ing. BSc

Secure Systems, PhD Candidate

Samuel Weiser is doing his PhD studies on computer science since 2016. He started his Bachelor studies on Information and Computer Engineering at Graz University of Technology back in 2010, and graduated to Dipl.Ing. (MSc) in 2016. He visited the Systems Security Lab at TU Darmstadt in 2018 for researching security architectures.
Samuel Weiser

Research

My research interests are two-fold. On the one hand, I am interested in software-based side-channels. Although we also demonstrate real attacks, my passion is more on the defensive side. In particular, I co-developed a practical tool for analyzing programs with respect to address-based side-channel leakage (e.g., used in cache attacks). Our tool helped uncover several issues in OpenSSL, and is open-source. On the other hand, I research security architectures such as Intel SGX, which allow secure code execution even in the presence of powerful kernel-level attackers.

Teaching

I give practical classes on Security Aspects in Software Development, with a focus on security against runtime attacks.

Publications

TIMBER-V: Tag-Isolated Memory Bringing Fine-grained Enclaves to RISC-V

Weiser, S., Werner, M. & Mangard, S.
Network and Distributed System Security Symposium (NDSS) 2019

DATA - Differential Address Trace Analysis: Finding Address-based Side-Channels in Binaries

Weiser, S. & Mangard, S.
Proceedings of the 27th USENIX Security Symposium , USENIX Association, 603-620

KeyDrown: Eliminating Software-Based Keystroke Timing Side-Channel Attacks

Schwarz, M., Lipp, M., Weiser, S. & Mangard, S.
Network and Distributed System Security Symposium 2018, 15

Dependable Internet of Things for Networked Cars

Weiser, S. & Mangard, S.
, 226-237

Malware guard extension

Schwarz, M., Weiser, S. & Mangard, S.
Detection of Intrusions and Malware, and Vulnerability Assessment - 14th International Conference, DIMVA 2017, 2017, Springer-Verlag Italia, 3-24, (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10327 LNCS)

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