Who Cited It

A survey on security and privacy of federated learning

2020 · Future Generation Computer Systems · 1,393 citations · 0 from inside this corpus

Viraaji Mothukuri low, Reza M. Parizi, Seyedamin Pouriyeh, Yan Huang, Ali Dehghantanha, Gautam Srivastava

No abstract in the source record.

A survey on security and privacy of federated learning (2020)A survey on security and priv…A Survey on Transfer Learning (2009)A Survey on Transfer LearningAdvances in neural information processing systems 7 (1996)Advances in neural informatio…Advances in Neural Information Processing Systems 29 (2016)Advances in Neural Informatio…Differential Privacy (2006)Differential PrivacyCommunication-Efficient Learning of Deep Networks from Decentralized Data (2016)Communication-Efficient Learn…Federated Learning: Challenges, Methods, and Future Directions (2020)Federated Learning: Challenge…Membership Inference Attacks Against Machine Learning Models (2017)Membership Inference Attacks …Federated Learning: Strategies for Improving Communication Efficiency (2016)Federated Learning: Strategie…Federated Learning in Mobile Edge Networks: A Comprehensive Survey (2020)Federated Learning in Mobile …Federated Learning With Differential Privacy: Algorithms and Performance Analysis (2020)Federated Learning With Diffe…Robust De-anonymization of Large Sparse Datasets (2008)Robust De-anonymization of La…Ensemble Adversarial Training: Attacks and Defenses (2017)Ensemble Adversarial Training…Privacy-Preserving Deep Learning via Additively Homomorphic Encryption (2017)Privacy-Preserving Deep Learn…Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference A… (2019)Comprehensive Privacy Analysi…Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge (2019)Client Selection for Federate…
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What this paper cites, inside the corpus

PaperYearCited
A Survey on Transfer Learning200923,670
Advances in neural information processing systems 7199614,393
Advances in Neural Information Processing Systems 29201613,474
Differential Privacy20065,337
Communication-Efficient Learning of Deep Networks from Decentralized Data20165,190
Federated Learning: Challenges, Methods, and Future Directions20204,992
Membership Inference Attacks Against Machine Learning Models20174,490
Federated Learning: Strategies for Improving Communication Efficiency20163,050
Federated Learning in Mobile Edge Networks: A Comprehensive Survey20202,538
Federated Learning With Differential Privacy: Algorithms and Performance Analysis20202,357
Robust De-anonymization of Large Sparse Datasets20082,349
Ensemble Adversarial Training: Attacks and Defenses20171,861
Privacy-Preserving Deep Learning via Additively Homomorphic Encryption20171,665
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference A…20191,624
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge20191,528

Links

DOI · OpenAlex record

Topics

Privacy-Preserving Technologies in DataComputer Science
Adversarial Robustness in Machine LearningComputer Science
Cryptography and Data SecurityComputer Science

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  • supports6 author record(s) attached.
  • supports296 reference(s) recorded.
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  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:59+00:00.

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