Who Cited It

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption

2017 · IEEE Transactions on Information Forensics and Security · 1,665 citations · 5 from inside this corpus

Le Trieu Phong, Yoshinori Aono, Takuya Hayashi, Lihua Wang, Shiho Moriai low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Privacy-Preserving Deep Learning via Additively Homomorphic Encryption (2017)Privacy-Preserving Deep Learn…Adaptive Subgradient Methods for Online Learning and Stochastic Optimization (2010)Adaptive Subgradient Methods …Public-Key Cryptosystems Based on Composite Degree Residuosity Classes (2007)Public-Key Cryptosystems Base…Deep Learning with Differential Privacy (2016)Deep Learning with Differenti…Practical Secure Aggregation for Privacy-Preserving Machine Learning (2017)Practical Secure Aggregation …Privacy-Preserving Deep Learning (2015)Privacy-Preserving Deep Learn…SecureML: A System for Scalable Privacy-Preserving Machine Learning (2017)SecureML: A System for Scalab…Foundations of Cryptography (2004)Foundations of CryptographyFederated Machine Learning (2019)Federated Machine LearningFederated Learning in Mobile Edge Networks: A Comprehensive Survey (2020)Federated Learning in Mobile …A survey on federated learning (2021)A survey on federated learningDeep Leakage from Gradients (2020)Deep Leakage from GradientsA survey on security and privacy of federated learning (2020)A survey on security and priv…
12 of 12 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Adaptive Subgradient Methods for Online Learning and Stochastic Optimization20108,621
Public-Key Cryptosystems Based on Composite Degree Residuosity Classes20077,277
Deep Learning with Differential Privacy20166,220
Practical Secure Aggregation for Privacy-Preserving Machine Learning20173,744
Privacy-Preserving Deep Learning20152,325
SecureML: A System for Scalable Privacy-Preserving Machine Learning20171,899
Foundations of Cryptography20041,795

What cites it, inside the corpus

PaperYearCited
Federated Machine Learning20196,228
Federated Learning in Mobile Edge Networks: A Comprehensive Survey20202,538
A survey on federated learning20211,847
Deep Leakage from Gradients20201,532
A survey on security and privacy of federated learning20201,393

Links

DOI · OpenAlex record

Topics

Privacy-Preserving Technologies in DataComputer Science
Cryptography and Data SecurityComputer Science
Stochastic Gradient Optimization TechniquesComputer Science

Is this record sound?

complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports5 author record(s) attached.
  • supports28 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:56+00:00.

sha256 7bc26169e93749d1…