Description
Controlling the access of data in Database management systems is a classical problem and it has been solved through different mechanisms. One of the most common mechanism implemented in most Database management systems is the mechanism of views, i.e defining the accessible data of a user as the result of a query. This mechanism is also used in principle in other systems such as in social networks. Unfortunately, this approach has some defaults. Even though it does not leak any secret information, the user seeing the data can infer some of these secret data by using different knowledge such as the logical definition of the query used to define the accessible data and various properties of the database. In this talk, I will present a formalism allowing to check when a set of views does not leak any information even through this kind of attacks.
Prochains exposés
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CHERI: Architectural Support for Memory Protection and Software Compartmentalization
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
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SemSecuElec
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Compartmentalization
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Hardware/software co-design
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Hardware architecture
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CHERI standardization and software ecosystem
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[…]-
SoSysec
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SemSecuElec
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Compartmentalization
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Operating system and virtualization
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Hardware/software co-design
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Hardware architecture
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Towards privacy-preserving and fairness-aware federated learning framework
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
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SoSysec
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Privacy
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Machine learning
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