Sommaire

Description

  • Orateur

    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 CHERI ecosystem is being grown within organizations such as the CHERI Alliance.

Infos pratiques

Prochains exposés

  • CHERI: Architectural Support for Memory Protection and Software Compartmentalization

    • 12 septembre 2025 (10:00 - 11:00)

    • Inria Center of the University of Rennes - Room Métivier

    Orateur : 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

    • Hardware/software co-design

    • Hardware architecture

  • Towards privacy-preserving and fairness-aware federated learning framework

    • 19 septembre 2025 (11:00 - 12:00)

    • Inria Center of the University of Rennes - Petri/Turing room

    Orateur : Nesrine Kaaniche - Télécom SudParis

    Federated Learning (FL) enables the distributed training of a model across multiple data owners under the orchestration of a central server responsible for aggregating the models generated by the different clients. However, the original approach of FL has significant shortcomings related to privacy and fairness requirements. Specifically, the observation of the model updates may lead to privacy[…]
    • Cryptography

    • SoSysec

    • Privacy

    • Machine learning

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