In this paper, we propose TrustFL, a practical scheme that leverages Trusted Execution Environments (TEEs) to build assurance of participants' training ...
Sep 6, 2024 · ... In [109], differential privacy and homomorphic encryption have been incorporated into FL, aiming to diminish privacy noise and enhance model ...
This paper proposes TrustFL, a practical scheme that leverages Trusted Execution Environments (TEEs) to build assurance of participants' training executions ...
Aug 3, 2020 · In this paper, we aim to build training assurance of untrusted participants in the FL framework. One pragmatic solution is to leverage hardware ...
本项目代码主要依托linux下的Intel SGX SDK，基于Mini-Dnn以及可在SGX下运行的Eigen3开发。代码由Enlave(C++)及Untrusted(Python)两部分构成。
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We propose and implement a Privacy-preserving Federated Learning (PPFL) framework for mobile systems to limit privacy leakages in federated learning.
Jul 22, 2024 · Enabling execution assurance of federated learning at untrusted participants. In Proc. the 2020 IEEE Conference on Computer Communications ...
Enabling Execution Assurance of Federated Learning at Untrusted Participants. DOI PDF 被引用文献1件. Xiaoli Zhang · Fengting Li · Zeyu Zhang · Qi Li · Cong Wang.
Dec 13, 2024 · ExclaveFL provides transparency by enabling participants in an FL job to register signed statements containing attestation reports with a ...
Enabling Execution Assurance of Federated Learning at Untrusted Participants · Computer Science. IEEE Conference on Computer Communications · 2020.