Articles with "secure federated" as a keyword



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sfkit: a web-based toolkit for secure and federated genomic analysis.

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Published in 2023 at "Nucleic acids research"

DOI: 10.1093/nar/gkad464

Abstract: Advances in genomics are increasingly depending upon the ability to analyze large and diverse genomic data collections, which are often difficult to amass due to privacy concerns. Recent works have shown that it is possible… read more here.

Keywords: web based; secure federated; analysis; secure ... See more keywords
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Permissioned Blockchain Frame for Secure Federated Learning

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Published in 2022 at "IEEE Communications Letters"

DOI: 10.1109/lcomm.2021.3121297

Abstract: Federated learning is an emerging technology that solves the privacy problem of training data in multi-party machine learning. However, this technology is vulnerable to a series of system security problems. In this letter, we leverage… read more here.

Keywords: blockchain frame; federated learning; frame secure; secure federated ... See more keywords
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Secure Federated Learning for Cognitive Radio Sensing

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Published in 2023 at "IEEE Communications Magazine"

DOI: 10.1109/mcom.001.2200465

Abstract: This article considers reliable and secure spectrum sensing (SS) based on federated learning (FL) in the cognitive radio (CR) environment. Motivation, architectures, and algorithms of FL in SSare discussed. Security and privacy threats on these… read more here.

Keywords: secure federated; federated learning; learning cognitive; cognitive radio ... See more keywords
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A Secure Federated Transfer Learning Framework

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Published in 2020 at "IEEE Intelligent Systems"

DOI: 10.1109/mis.2020.2988525

Abstract: Machine learning relies on the availability of vast amounts of data for training. However, in reality, data are mostly scattered across different organizations and cannot be easily integrated due to many legal and practical constraints.… read more here.

Keywords: secure federated; transfer learning; transfer; federated transfer ... See more keywords
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FLCert: Provably Secure Federated Learning Against Poisoning Attacks

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Published in 2022 at "IEEE Transactions on Information Forensics and Security"

DOI: 10.1109/tifs.2022.3212174

Abstract: Due to its distributed nature, federated learning is vulnerable to poisoning attacks, in which malicious clients poison the training process via manipulating their local training data and/or local model updates sent to the cloud server,… read more here.

Keywords: provably secure; flcert provably; federated learning; secure federated ... See more keywords
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Efficient and Secure Federated Learning With Verifiable Weighted Average Aggregation

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Published in 2023 at "IEEE Transactions on Network Science and Engineering"

DOI: 10.1109/tnse.2022.3206243

Abstract: Federated learning allows a large number of participants to collaboratively train a global model without sharing participant's local data. Participants train local models with their local data and send gradients to the cloud server for… read more here.

Keywords: aggregation; federated learning; weighted average; secure federated ... See more keywords
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Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

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Published in 2022 at "IEEE Transactions on Smart Grid"

DOI: 10.1109/tsg.2022.3204796

Abstract: As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has… read more here.

Keywords: federated learning; secure federated; detection; smart grid ... See more keywords