Fengyin Li
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Personalized client-edge-cloud hierarchical federated learning in mobile edge computing - Journal of Cloud Computing
Experiments In this section, we evaluate the performance of ESPerHFL and compare it with the advanced HFL method HierFAVG [19] and the advanced PFL methods APFL [30], HeurFedAMP [31] and FedALA [35]. We also test the effect of the variation of hyperparameters on the performance of the algorithm. In our experiments, we simulate an HFL system consisting of a cloud server, 10 edge servers, 50 clients, and 5 clients connected to each edge server. Figure 4 shows the experimental framework.
Research on Quantum-Attack-Resistant Strong Forward-Secure Signature Schemes
Abstract : The security of digital signatures depends significantly on the signature key. Therefore, to reduce the impact of leaked keys upon existing signatures and subsequent ones, a digital signature scheme with strong forward security could be an effective solution. Most existing strong forward-secure digital signature schemes rely on traditional cryptosystems, which cannot effectively resist quantum attacks.
Post-Quantum Secure Identity-Based Proxy Blind Signature Scheme on a Lattice
Abstract : Blind signatures have been widely applied when privacy preserving is required, and the delegation of blind signature rights and a proxy blind signature (Proxy-BS) become necessary when the signer cannot sign. Existing Proxy-BS schemes are based on traditional cryptographically hard problems, and they cannot resist quantum attacks. Moreover, most current Proxy-BS schemes depend on public key infrastructure (PKI), which leads to high certificate storage and management overhead.
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