Radboud Digital Security group Lunch Talk homepage

Welcome to the site of the talks organised by Radboud Digital Security group. We organize a talk every Wednesday at 12:30.

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Upcoming talks

  • Wednesday, 4th of February 2026 at 12:30 in the big lecture room in Mercator 1 (MERC1_00.28, ground floor)
    DiS Lunch by Seyed Benham Andarzian

    Fuzzing wireless IoT protocols in industry

    This talk explores the practical realities of fuzzing wireless IoT protocols—specifically BLE, Thread, and 5G—within an industrial context. We’ll move beyond theoretical models to share our firsthand experiences with the challenges of testing complex wireless stacks and the "non-standard" implementation flaws we’ve uncovered. The session concludes with a look at our future roadmap, focusing on how we are scaling our testing frameworks and integrating advanced techniques to secure the next generation of hyper-connected infrastructure.

  • Wednesday, 11th of February 2026 at 12:30 in the big lecture room in Mercator 1 (MERC1_00.28, ground floor)
    DiS Lunch by Håvard Raddum

    The Zodiac Killer Ciphers

    The Zodiac killer was a serial killer who was active in the San Francisco area in the late 60´s and early 70´s. In addition to killing he made ciphers that he sent to the police and newspapers. Could his ciphers be cracked? If so, what was his message? The talk is not very technical, the only cryptanalysis in there is of the substitution cipher kind (&=L, ?=I, §=L, %=K decrypts %?§& into…). There is also quite a bit of story telling and the talk will be very accessible to anyone.

  • Wednesday, 18th of February 2026 at 12:30 in the big lecture room in Mercator 1 (MERC1_00.28, ground floor)
    DiS Lunch by Julius Hermelink

    Distribution Hints and Oracles: Soft-Analytic Techniques for Side-Channel Attacks on ML-KEM and ML-DSA


    In response to advances in quantum computing, standardization bodies worldwide have started efforts to identify suitable post-quantum replacements for widely used asymmetric cryptographic schemes. NIST has recently standardized the first post-quantum algorithms, including the key encapsulation mechanism ML-KEM and the signature scheme ML-DSA.
    We introduce soft-analytic techniques for key recovery from side-channel information in these schemes. Our approach relies on the notion of distribution hints, a generalization of existing lattice-based hints; furthermore, our definition captures the information available in a wide range of practical attacks without loss of information. We show how such hints can be exploited using both belief-propagation–based solvers and efficient greedy algorithms.
    We further demonstrate that PC-oracle attacks---one of the most prominent and extensively studied class of attacks against ML-KEM---can be substantially improved using soft-analytic methods. We formalize soft PC-oracles that return probabilistic information and propose several Bayesian inference techniques for exploiting them. One of these methods, based on belief propagation, can be seen as a natural extension of our previous framework.
    Our techniques enable new noise-tolerant attacks and substantially improve upon prior attacks. For example, we require half as many traces in attacks against ML-KEM's noise term. For PC-oracle attacks, we achieve a reduction in the number of traces by a factor of 7 in the previous oracle model; moreover, our new model captures and exploits significantly more information that is available in practice, enabling further reductions. Finally, we show how our framework applies to masked implementations of ML-DSA and provide an information-theoretic analysis.

  • Wednesday, 25th of February 2026 at 12:30 in the big lecture room in Mercator 1 (MERC1_00.28, ground floor)
    DiS Lunch by Rusidy Makarim

    TBA

  • Wednesday, 4th of March 2026 at 12:30 in the big lecture room in Mercator 1 (MERC1_00.28, ground floor)
    DiS Lunch by Yevhen Perehuda

    Attacks and Remedies for Randomness in AI: Cryptanalysis of PHILOX and THREEFRY

    In this work, we address the critical yet understudied question of the security of the most widely deployed pseudorandom number generators (PRNGs) in AI applications. We show that these generators are vulnerable to practical and low-cost attacks. With this in mind, we conduct an extensive survey of randomness usage in current applications to understand the efficiency requirements imposed in practice. Finally, we present a cryptographically secure and well-understood alternative, which has a negligible effect on the overall AI/ML workloads. More generally, we recommend the use of cryptographically strong PRNGs in all contexts where randomness is required, as past experience has repeatedly shown that security requirements may arise unexpectedly even in applications that appear uncritical at first.

  • Past talks