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An effective and practical gradient inversion attack

https://doi.org/10.1002/int.22997
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/int.22315openalex-snapshot
Querying little is enough: Model inversion attack via latent information
inferredcites →https://doi.org/10.1002/int.22330openalex-snapshot
Analyzing host security using D‐S evidence theory and multisource information fusion
inferredcites →https://doi.org/10.1002/int.22349openalex-snapshot
Camdar‐adv: Generating adversarial patches on 3D object
inferredcites →https://doi.org/10.1002/int.22397openalex-snapshot
Enhancing intrusion detection with feature selection and neural network
inferredcites →https://doi.org/10.1002/int.22529openalex-snapshot
Hybrid sequence‐based Android malware detection using natural language processing
inferredcites →https://doi.org/10.1002/int.22549openalex-snapshot
Meta‐learning and the new challenges of machine learning
inferredcites →https://doi.org/10.1002/int.22680openalex-snapshot
ELAA: An efficient local adversarial attack using model interpreters
inferredcites →https://doi.org/10.1002/int.22720openalex-snapshot
IWA: Integrated gradient‐based white‐box attacks for fooling deep neural networks
inferredcites →https://doi.org/10.1002/int.22727openalex-snapshot
Secure and efficient parameters aggregation protocol for federated incremental learning and its applications
inferredcites →https://doi.org/10.1002/int.22806openalex-snapshot
A novel underwater image restoration method based on decomposition network and physical imaging model
inferredcites →https://doi.org/10.1002/jemt.20294openalex-snapshot
Richardson–Lucy algorithm with total variation regularization for 3D confocal microscope deconvolution
inferredcites →https://doi.org/10.1007/978-3-319-10590-1_53openalex-snapshot
Visualizing and Understanding Convolutional Networks
inferredcites →https://doi.org/10.1007/978-3-319-23633-9_24openalex-snapshot
Privacy Law, Data Sharing Policies, and Medical Data: A Comparative Perspective
inferredcites →https://doi.org/10.1007/978-981-10-5421-1_9openalex-snapshot
Privacy-Preserving Deep Learning: Revisited and Enhanced
inferredcites →https://doi.org/10.1007/s13042-020-01242-zopenalex-snapshot
Adversarial examples: attacks and defenses in the physical world
inferredcites →https://doi.org/10.1007/s41666-020-00082-4openalex-snapshot
Federated Learning for Healthcare Informatics
inferredcites →https://doi.org/10.1016/0167-2789(92)90242-fopenalex-snapshot
Nonlinear total variation based noise removal algorithms
inferredcites →https://doi.org/10.1016/j.ins.2018.07.011openalex-snapshot
A payload-dependent packet rearranging covert channel for mobile VoIP traffic
inferredcites →https://doi.org/10.1016/j.ins.2018.12.023openalex-snapshot
A hierarchical group key agreement protocol using orientable attributes for cloud computing
inferredcites →https://doi.org/10.1016/j.ins.2020.03.066openalex-snapshot
Adversarial attacks on deep-learning-based radar range profile target recognition
inferredcites →https://doi.org/10.1016/j.ins.2020.09.064openalex-snapshot
PPCL: Privacy-preserving collaborative learning for mitigating indirect information leakage
inferredcites →https://doi.org/10.1016/j.jnca.2020.102632openalex-snapshot
Adversarial attacks on deep-learning-based SAR image target recognition
inferredcites →https://doi.org/10.1016/j.jpdc.2019.03.003openalex-snapshot
The security of machine learning in an adversarial setting: A survey
inferredcites →https://doi.org/10.1109/cvpr.2018.00068openalex-snapshot
The Unreasonable Effectiveness of Deep Features as a Perceptual Metric
inferredcites →https://doi.org/10.1109/cvpr46437.2021.01607openalex-snapshot
See through Gradients: Image Batch Recovery via GradInversion
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2019.00029openalex-snapshot
Exploiting Unintended Feature Leakage in Collaborative Learning
inferredcites →https://doi.org/10.1109/tdsc.2022.3143566openalex-snapshot
Attacking Deep Reinforcement Learning With Decoupled Adversarial Policy
inferredcites →https://doi.org/10.1109/tnnls.2019.2953131openalex-snapshot
Communication-Efficient Federated Deep Learning With Layerwise Asynchronous Model Update and Temporally Weighted Aggregation
inferredcites →https://doi.org/10.1145/3298981openalex-snapshot
Federated Machine Learning
inferredcites →https://doi.org/10.1561/2200000083openalex-snapshot
Advances and Open Problems in Federated Learning
inferredcites →https://doi.org/10.48550/arxiv.1511.03575openalex-snapshot
Federated Optimization:Distributed Optimization Beyond the Datacenter
inferredcites →https://doi.org/10.48550/arxiv.2001.02610openalex-snapshot
iDLG: Improved Deep Leakage from Gradients
inferredcites →https://doi.org/10.48550/arxiv.2003.14053openalex-snapshot
Inverting Gradients -- How easy is it to break privacy in federated learning?

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s10462-025-11248-0openalex-snapshot
Deep learning model inversion attacks and defenses: a comprehensive survey
inferred← citeshttps://doi.org/10.1007/s40747-025-02009-1openalex-snapshot
Privacy attack in federated learning is not easy: an experimental study
inferred← citeshttps://doi.org/10.1007/s44443-025-00239-4openalex-snapshot
Leveraging data drift to optimize differential privacy in federated learning via dual-mode switching
inferred← citeshttps://doi.org/10.1109/access.2026.3732519openalex-snapshot
AP3-FedFleet: Asynchronous Federated Learning With Dynamic Layer-Wise Privacy Protection for Heterogeneous IoT Systems
inferred← citeshttps://doi.org/10.1109/aiot63253.2024.00032openalex-snapshot
A Privacy-Preserving Federated Learning Framework for IoT Environment Based on Secure Multi-party Computation
inferred← citeshttps://doi.org/10.1145/3770853openalex-snapshot
Digital Privacy Under Attack: Challenges and Enablers
inferred← citeshttps://doi.org/10.1145/3789456.3789473openalex-snapshot
A Survey of Model Inversion Attacks: An Interface-Prior Perspective
inferred← citeshttps://doi.org/10.1155/2023/4459198openalex-snapshot
Towards Risk‐Free Trustworthy Artificial Intelligence: Significance and Requirements
inferred← citeshttps://doi.org/10.1155/2023/5510329openalex-snapshot
Fast and Accurate Deep Leakage from Gradients Based on Wasserstein Distance
inferred← citeshttps://doi.org/10.3390/tourhosp6020100openalex-snapshot
Phase-Adaptive Federated Learning for Privacy-Preserving Personalized Travel Itinerary Generation
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