49 results

  • CHERI standardization and software ecosystem

    • September 12, 2025 (11:00 - 12:00)

    • Inria Center of the University of Rennes - Espace de conférences

    Speaker : Carl SHAW - CODASIP

    This talk will describe the current status of the RISC-V International standardization process to add CHERI as an official extension to RISC-V. It will then explore the current state of CHERI-enabled operating systems, toolchains and software tool development, focusing on the CHERI-RISC-V hardware implementations of CHERI. It will then go on to give likely future development roadmaps and how the[…]
    • SoSysec

    • SemSecuElec

    • Compartmentalization

    • Micro-architectural vulnerabilities

  • CHERI: Architectural Support for Memory Protection and Software Compartmentalization

    • September 12, 2025 (10:00 - 11:00)

    • Inria Center of the University of Rennes - Espace de conférences

    Speaker : Robert Watson - University of Cambridge

    CHERI is a processor architecture protection model enabling fine-grained C/C++ memory protection and scalable software compartmentalization. CHERI hybridizes conventional processor, instruction-set, and software designs with an architectural capability model. Originating in DARPA’s CRASH research program in 2010, the work has progressed from FPGA prototypes to the recently released Arm Morello[…]
    • SoSysec

    • SemSecuElec

    • Compartmentalization

    • Micro-architectural vulnerabilities

    • Hardware architecture

  • Side-Channel Based Disassembly on Complex Processors: From Microachitectural Characterization to Probabilistic Models

    • June 27, 2025 (11:00 - 12:00)

    • Inria Center of the University of Rennes - Espace de conférences

    Speaker : Julien Maillard - CEA

    Side-Channel Based Disassembly (SCBD) is a category of Side-Channel Analysis (SCA) that aims at recovering information on the code executed by a processor through the observation of physical side-channels such as power consumption or electromagnetic radiations. While traditional SCA often targets cryptographic keys, SCBD focuses on retrieving assembly code that can hardly be extracted via other[…]
    • SemSecuElec

    • Side-channel

    • Hardware reverse

  • Fine-grained dynamic partitioning against cache-based side channel attacks

    • June 27, 2025 (10:00 - 11:00)

    • Inria Center of the University of Rennes - Espace de conférences

    Speaker : Nicolas Gaudin - Trasna

    The growth of embedded systems takes advantage of architectural advances from modern processors to increase performance while maintaining a low power consumption. Among these advances is the introduction of cache memory into embedded systems. These memories speed up the memory accesses by temporarily storing data close to the execution core. Furthermore, data from different applications share the[…]
    • SemSecuElec

    • Micro-architectural vulnerabilities

    • Hardware architecture

  • Cryptanalytical extraction of complex Neural Networks in black-box settings

    • May 23, 2025 (11:00 - 12:00)

    • Inria Center of the University of Rennes - - IRISA - Salle Aurigny (D165)

    Speaker : Benoit COQUERET - INRIA, Thales CESTI

    With the widespread development of artifical intelligence, Deep Neural Networks (DNN) have become valuable intellectual property (IP). In the past few years, software and hardware-based attacks targetting at the weights of the DNN have been introduced allowing potential attacker to gain access to a near-perfect copy of the victim's model. However, these attacks either fail against more complex[…]
    • SemSecuElec

    • Side-channel

    • Machine learning

  • Anomalies Mitigation for Horizontal Side Channel Attacks with Unsupervised Neural Networks

    • May 23, 2025 (10:00 - 11:00)

    • Inria Center of the University of Rennes - - IRISA - Salle Aurigny (D165)

    Speaker : Gauthier Cler - SERMA Safety & Security

    The success of horizontal side-channel attacks heavily depends on the quality of the traces as well as the correct extraction of interest areas, which are expected to contain relevant leakages. If former is insufficient, this will consequently degrade the identification capability of potential leakage candidates and often render attacks inapplicable. This work assess the relevance of neural[…]
    • SemSecuElec

    • Side-channel

    • Machine learning