Abstract: With the growing processing power of computing systems and the increased availability of massive datasets, machine learning algorithms have led to major breakthroughs in many different areas. This development has influenced computer security, inspiring many learning-based security systems, such as for malware detection, vulnerability discovery, and binary code analysis. Despite great potential, machine learning
Abstract: Widely used cryptographic protocols like TLS 1.3 (Transport Layer Security) have seen increased adoption recently on the basis of their claims of provable security. These claims refer to the results of rigorous academic proofs in a formal key-exchange model; however, the actual claims and guarantees rarely reach developers or implementors of TLS, let alone
Abstract: TEMPEST attacks are a well-known threat that consists of spying on an electronic device through its unintended physical emissions. Physical emissions are also used by side-channel attacks to break cryptographic implementations. However, while TEMPEST attacks have been demonstrated at large distances (e.g., several meters), side-channel attacks generally work only in the proximity of the target
Abstract: This presentation covers the “FragAttacks” research. This research includes three new design flaws in the 802.11 standard that underpins Wi-Fi. One design flaw is in the frame aggregation functionality, and another two are in the frame fragmentation functionality. These design flaws enable an adversary to forge encrypted frames in various ways, which in turn
Abstract: The talk will cover: – What makes customers trust digital services – How do you engage communities into building strong security – Are vulnerabilities the end of a company’s reputation Join the Zoom meeting at 12:30 on Thursday, May 27th: https://ethz.zoom.us/j/65841148696
Abstract: Quantum computers are expected to provide efficient solutions to problems that are conjectured to be intractable for classical computers (such as the simulation of quantum physical system). This raises the following question: can a classical computer efficiently verify the results of a quantum computation? In 2018, Urmila Mahadev answered this question in the affirmative
Abstract: In this talk, I will first introduce the Cyber-Defence Campus, including its main topics of interest and activities. I will then show with two application examples how machine learning can enable us to analyze and anticipate cybersecurity risks at scale. First, we will see how supervised and unsupervised learning algorithms can help detect intrusions
Abstract: A multitude of wireless technologies are used by an aircraft during flight. From a conceptual perspective, all of them are insecure as security was never part of their design and the evolution of legacy systems in aviation did not keep up with the state of the art. Recent contributions from academic and hacking communities
Abstract: This talk reports on the latest computational records in integer factoring and finite field discrete logarithms. These hard computational problems underpin the security of the public-key cryptographic primitives known as RSA and finite field Diffie-Hellman, which are still the most used public-key cryptographic primitives in many contexts. This work required a quite formidable amount of computing power, from various
Abstract: Probabilistic data structures use space-efficient representations of data in order to (approximately) respond to queries about the data. Traditionally, these structures are accompanied by probabilistic bounds on query-response errors. These bounds implicitly assume benign attack models, in which the data and the queries are chosen non-adaptively, and independent of the randomness used to construct