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   Articles with "efficient verifiable" as a keyword



TEVA: Training-Efficient and Verifiable Aggregation for Federated Learning for Consumer Electronics in Industry 5.0

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recommendations! Published in 2025 at "IEEE Transactions on Consumer Electronics"

DOI: 10.1109/tce.2024.3517739

Abstract: Federated learning (FL) has been widely used for privacy-preserving model updates in Industry 5.0, facilitated by 6G networks. Despite FL’s privacy-preserving advantages, it remains vulnerable to attacks where adversaries can infer private data from local… read more here.

Keywords: verifiable aggregation; privacy; training efficient; federated learning ... See more keywords

VQL: Efficient and Verifiable Cloud Query Services for Blockchain Systems

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recommendations! Published in 2022 at "IEEE Transactions on Parallel and Distributed Systems"

DOI: 10.1109/tpds.2021.3113873

Abstract: Despite increasingly emerging applications, a primary concern for blockchain to be fully practical is the inefficiency of data query. Direct queries on the blockchain take much time by searching every block, while indirect queries on… read more here.

Keywords: data query; blockchain systems; query; services blockchain ... See more keywords

Achieve Efficient and Verifiable Conjunctive and Fuzzy Queries over Encrypted Data in Cloud

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recommendations! Published in 2022 at "IEEE Transactions on Services Computing"

DOI: 10.1109/tsc.2019.2924372

Abstract: Due to the high demands of searchability over encrypted data, searchable encryption (SE) has recently received considerable attention and been widely suggested in encrypted cloud storage. Typically, the cloud server is assumed to be honest-but-curious… read more here.

Keywords: efficient verifiable; encrypted data; verifiable conjunctive; data cloud ... See more keywords

EVFL: Towards Efficient Verifiable Federated Learning via Parameter Reuse and Adaptive Sparsification

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recommendations! Published in 2024 at "Mathematics"

DOI: 10.3390/math12162479

Abstract: Federated learning (FL) demonstrates significant potential in Industrial Internet of Things (IIoT) settings, as it allows multiple institutions to jointly construct a shared learning model by exchanging model parameters or gradient updates without the need… read more here.

Keywords: evfl towards; parameter; sparsification; federated learning ... See more keywords