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: understanding how they can be used to reconstruct sensitive client data and designing robust defense mechanisms to protect against such threats. Context Federated Learning (FL) enables multiple clients
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focuses on the analytical synthesis of broadband and dual-band matching networks and power combiners for 6G radar applications. The objective is to develop a component library for integration
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microarchitectural vulnerabilities and/or prove the robustness, for a given fault model, of various RISC-V based processors [3]. For instance, we apply this methodology to the OpenTitan secure element and formally
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plugin. This plugin is based on the open-source Dask framework and allows us to transfer data to dedicated processes to perform in-situ analysis. One of our goals is to establish a feedback mechanism