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Titlebook: Web and Big Data; 8th International Jo Wenjie Zhang,Anthony Tung,Hongjie Guo Conference proceedings 2024 The Editor(s) (if applicable) and

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樓主: fumble
51#
發(fā)表于 2025-3-30 10:27:56 | 只看該作者
Efficient Updateable Private Set Intersection on?Outsourced Datasetsd data.?We use an Elastic Bloom Filter to store data and compute intersections, which can dramatically improve intersection computation efficiency. Theoretically, we analyze the complexity of the protocol and?prove its security in a semi-honest model. We compare it with related protocols and demonst
52#
發(fā)表于 2025-3-30 15:37:55 | 只看該作者
53#
發(fā)表于 2025-3-30 17:14:32 | 只看該作者
54#
發(fā)表于 2025-3-30 21:49:55 | 只看該作者
55#
發(fā)表于 2025-3-31 01:05:53 | 只看該作者
56#
發(fā)表于 2025-3-31 05:44:26 | 只看該作者
57#
發(fā)表于 2025-3-31 11:15:04 | 只看該作者
58#
發(fā)表于 2025-3-31 13:53:48 | 只看該作者
Parallel Secure Inference for?Multiple Models Based on?CKKSmultaneously to decrease the number of decrypt operations and communication. Subsequently, we apply the two parallel techniques to phenotypic inference from genetic data. Experimental results show that?our method improves the performance by at least 47.8% compared to?the method without parallel tech
59#
發(fā)表于 2025-3-31 20:13:18 | 只看該作者
PrivRBFN: Building Privacy-Preserving Radial Basis Function Networks Based on?Federated Learninggorithm called PrivRBFN to build a privacy-preserving RBF network based on federated learning. PrivRBFN is tailored for RBF networks with Gaussian radial basis functions. It allows the clients involved in federated learning to upload approximate radial bases of their local models to the server for m
60#
發(fā)表于 2025-3-31 21:51:00 | 只看該作者
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