Who Cited It

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

2019 · 1,624 citations · 2 from inside this corpus

Milad Nasr, Reza Shokri, Amir Houmansadr

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.

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference A… (2019)Comprehensive Privacy Analysi…Machine learning a probabilistic perspective (2012)Machine learning a probabilis…Calibrating Noise to Sensitivity in Private Data Analysis (2006)Calibrating Noise to Sensitiv…Deep Learning with Differential Privacy (2016)Deep Learning with Differenti…Communication-Efficient Learning of Deep Networks from Decentralized\n Data (2016)Communication-Efficient Learn…Communication-Efficient Learning of Deep Networks from Decentralized Data (2016)Communication-Efficient Learn…The Algorithmic Foundations of Differential Privacy (2014)The Algorithmic Foundations o…Membership Inference Attacks Against Machine Learning Models (2017)Membership Inference Attacks …The Algorithmic Foundations of Differential Privacy (2013)The Algorithmic Foundations o…Federated Learning: Strategies for Improving Communication Efficiency (2016)Federated Learning: Strategie…Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures (2015)Model Inversion Attacks that …Privacy-Preserving Deep Learning (2015)Privacy-Preserving Deep Learn…A review of applications in federated learning (2020)A review of applications in f…A survey on security and privacy of federated learning (2020)A survey on security and priv…
13 of 13 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
Machine learning a probabilistic perspective20129,324
Calibrating Noise to Sensitivity in Private Data Analysis20067,210
Deep Learning with Differential Privacy20166,220
Communication-Efficient Learning of Deep Networks from Decentralized\n Data20165,645
Communication-Efficient Learning of Deep Networks from Decentralized Data20165,190
The Algorithmic Foundations of Differential Privacy20144,578
Membership Inference Attacks Against Machine Learning Models20174,490
The Algorithmic Foundations of Differential Privacy20134,058
Federated Learning: Strategies for Improving Communication Efficiency20163,050
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures20152,885
Privacy-Preserving Deep Learning20152,325

What cites it, inside the corpus

PaperYearCited
A review of applications in federated learning20201,502
A survey on security and privacy of federated learning20201,393

Links

DOI · Open access copy · OpenAlex record

Topics

Privacy-Preserving Technologies in DataComputer Science
Adversarial Robustness in Machine LearningComputer Science
Stochastic Gradient Optimization TechniquesComputer Science

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complete

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

  • supports3 author record(s) attached.
  • supports65 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…