Abstract
Over the last two decades, cache attacks have emerged as a significant threat to shared computing. At their core, cache attacks exploit minute timing variation to query the state of a cache in the computer. From this cache state, the attacker can infer secret data processed by victim software that uses the shared cache. As these attacks often measure minute variations, at the order of few nanoseconds, multiple proposed defences aim at depriving attackers of high-resolution clocks.
In this talk we show the futility of such attempts. We first show that coarse-grained cache attack can retrieve sensitive information even in the absence of high-resolution timers. We then delve deeper into the nature of cache attacks, demonstrating that they allow arbitrary computation on cache state. Finally, we show how attackers can exploit this observation to implement high-frequency, high-resolution cache attacks without using high-resolution timers.

Bio
Yuval Yarom is a professor at Ruhr University Bochum, where he leads the Chair for Computer Security. He earned his Ph.D. in Computer Science from the University of Adelaide in 2014, and an M.Sc. in Computer Science and a B.Sc. in Mathematics and Computer Science from the Hebrew University of Jerusalem in 1993 and 1990, respectively. In between he has been the Vice President of Research in Memco Software and a co-founder and Chief Technology Officer of Girafa.com.
Yuval’s research explores the security of the interface between the software and the hardware. In particular, he is interested in the discrepancy between the way that programmers think about software execution and the concrete execution in modern processors. He works on identifying micro-architectural vulnerabilities, and on exploitation and mitigation techniques.

Photo © Hilary Brooks

Short bio:
Dr. Sebastian Tschiatschek is assistant professor at the University of Vienna.

He is part of the research group for Data Mining and Machine Learning, leading the work group for Probabilistic and Interactive Machine Learning.

He is also an alumni of TU Graz.

Abstract:

Reinforcement learning has been successfully used for training AI agents when given clearly defined reward signals. However, reinforcement learning can suffer from high sample complexity and is challenging to use in settings in which the reward signal is hard to specify, e.g., for training personal agents that should maximize a human-defined reward function. We investigate imitation learning and reinforcement learning from human feedback which allows us to avoid the specification of a reward function and can drastically reduce sample complexity. Inspired by real-world applications, we particularly study settings in which there is a mismatch between the human providing demonstrations or feedback and the learning AI agent, e.g., in terms of observations, capabilities, or constraints. Our insights emphasize the need for adaptation of the human and the AI agent to achieve the best alignment regarding the human’s goals. Furthermore, we propose practical algorithms to perform this adaptation and sample efficient approaches for learning about rewards and constraints.

Photo: ©University of Vienna

Abstract:
Secure two-party computation allows two parties to securely compute a function on their respective private inputs. It allows to preserve privacy in applications that involve a client and a single server, and in settings where private data is outsourced to two non-colluding servers. In this talk, I will give an overview on recent advances in the area of secure two-party computation. In particular, I will focus on the setting with semi-honest parties, which allows to construct the most efficient protocols. I will summarize three recent research results from the ENCRYPTO group: First, circuit synthesis and secure evaluation of circuits should be considered together to not leak private information when evaluating malformed circuits with popular instantiations of Yao’s garbled circuits protocol (JoC’23). In the area of secret-sharing based protocols, ABY2.0 (USENIX Security’21) allows highly efficient secure evaluation of Boolean circuits with multi-input AND gates and vector products, and FLUTE (IEEE S&P’23) extends these results to multi-input lookup tables. Among many other applications, these protocols substantially improve efficiency of privacy-preserving machine learning.

Short Bio:
Thomas Schneider is full professor for Cryptography and Privacy Engineering in the Department of Computer Science at Technical University of Darmstadt, Germany. Before, he was independent research group leader at TU Darmstadt (2012-2018), did a PhD in IT Security at Ruhr-University Bochum (2008- 2011), and wrote his Master thesis during a research internship at Nokia Bell Labs, NJ, USA (2007). His research focuses on privacy, cryptographic protocols, applied cryptography, and computer security. He heads the Cryptography and Privacy Engineering Group (ENCRYPTO), whose mission is to demonstrate that privacy can be efficiently protected in real-world applications. For this, his group combines applied cryptography and algorithm engineering to develop cryptographic protocols and tools for protecting sensitive data and algorithms. For his research on cryptography and privacy engineering, he was awarded with an ERC Starting Grant 2019 and an ERC Consolidator Grant 2023. See https://encrypto.de/tschneider for more details.

Photo copyright: TU Darmstadt

We present our new open bachelor’s thesis topics and award prizes to excellent students who contributed to scientific publications this past year.

If you’re interested in joining us for your bachelor’s thesis in security, this is the best way to get an impression of our topics as well as how a bachelor’s thesis at IAIK works: You’ll hear about our research areas and current hot topics, our Bachelor@IAIK program where you can work on your thesis together with your fellow students in one of our offices if you like, and maybe you’ll get to know your supervisor while chatting along.

The event will also be the kick-off lecture in Introduction to Scientific Working (ISW) where you will be able to choose your preferred topic!   

We are looking forward to meeting you!

Short abstract
The emergence of open hardware initiatives, for instance, based on the RISC-V ISA, exposes more easily the exact behavior of hardware designs. They can then be analyzed and combined with application-level semantics to formally verify complex safety (and security) properties at the system level. In this talk, we first present an overview of the LEAF approach for verifying such timing-related properties. Then, we focus on the required formal model tailored to a specific property: the detection of Timing Anomalies (TA) within pipelines of processors. A TA is a counterintuitive timing behavior that can threaten Worst-Case Execution Time (WCET) analyses. We also report ongoing work to generate such pipeline formal models from RISC-V processors described in Chisel/FIRRTL. Finally, we conclude on current extensions to apply the LEAF approach to safety properties.

Bio
Dr. Mathieu Jan obtained his engineering diploma in 2003 and got a Ph.D. in 2006 on data management for grid architectures from Univ. of Rennes 1 in an INRIA laboratory. He joined CEA LIST in 2007 as a full-time researcher. Since then, his main research interests are embedded systems and real-time systems. Senior expert at CEA LIST since 2014, he obtained a “Habilitation à Diriger des Recherches” (HDR) in 2016, and is a CEA Research Director since 2021. He spent the whole year 2019 as visiting scholar at the University of California, Berkeley (UCB) in the group of Prof. Edward Lee. Since 2020, Mathieu focuses on the hardware/software formal verification of embedded systems and is the Ph.D. director of several Ph.D. students in this area.

Photo: Private