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Label‐only membership inference attacks on machine unlearning without dependence of posteriors
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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CSRT rumor spreading model based on complex network
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Enhancing intrusion detection with feature selection and neural network
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An empirical study of supervised email classification in Internet of Things: Practical performance and key influencing factors
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DeepWAF: Detecting Web Attacks Based on CNN and LSTM Models
inferredcites →https://doi.org/10.1007/978-3-030-58592-1_31openalex-snapshot
Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-030-62460-6_52openalex-snapshot
Querying Little Is Enough: Model Inversion Attack via Latent Information
inferredcites →https://doi.org/10.1007/s13042-020-01242-zopenalex-snapshot
Adversarial examples: attacks and defenses in the physical world
inferredcites →https://doi.org/10.1016/j.csbj.2014.11.005openalex-snapshot
Machine learning applications in cancer prognosis and prediction
inferredcites →https://doi.org/10.1016/j.future.2018.06.007openalex-snapshot
Detecting insider attacks in medical cyber–physical networks based on behavioral profiling
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MHAT: An efficient model-heterogenous aggregation training scheme for federated learning
inferredcites →https://doi.org/10.1016/j.neucom.2020.10.081openalex-snapshot
Deep face recognition: A survey
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Gradient-based learning applied to document recognition
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
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Deep Unlearning via Randomized Conditionally Independent Hessians
inferredcites →https://doi.org/10.1109/cvprw56347.2022.00482openalex-snapshot
Efficient Two-stage Model Retraining for Machine Unlearning
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Towards Making Systems Forget with Machine Unlearning
inferredcites →https://doi.org/10.1109/sp.2017.41openalex-snapshot
Membership Inference Attacks Against Machine Learning Models
inferredcites →https://doi.org/10.1109/sp.2019.00065openalex-snapshot
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
inferredcites →https://doi.org/10.1109/tdsc.2019.2894411openalex-snapshot
Searchable Symmetric Encryption with Forward Search Privacy
inferredcites →https://doi.org/10.1109/tdsc.2020.2971598openalex-snapshot
NPMML: A Framework for Non-interactive Privacy-preserving Multi-party Machine Learning
inferredcites →https://doi.org/10.1109/tkde.2022.3174044openalex-snapshot
GATrust: A Multi-Aspect Graph Attention Network Model for Trust Assessment in OSNs
inferredcites →https://doi.org/10.1145/3133956.3134077openalex-snapshot
Machine Learning Models that Remember Too Much
inferredcites →https://doi.org/10.1145/3292500.3330885openalex-snapshot
Auditing Data Provenance in Text-Generation Models
inferredcites →https://doi.org/10.1145/3372297.3417238openalex-snapshot
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models
inferredcites →https://doi.org/10.1145/3460120.3484575openalex-snapshot
Membership Leakage in Label-Only Exposures
inferredcites →https://doi.org/10.1145/3460120.3484756openalex-snapshot
When Machine Unlearning Jeopardizes Privacy
inferredcites →https://doi.org/10.1145/3474369.3486876openalex-snapshot
Differential Privacy Defenses and Sampling Attacks for Membership Inference
inferredcites →https://doi.org/10.14722/ndss.2019.23064openalex-snapshot
MBeacon: Privacy-Preserving Beacons for DNA Methylation Data
inferredcites →https://doi.org/10.14722/ndss.2019.23119openalex-snapshot
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
inferredcites →https://doi.org/10.2478/popets-2019-0008openalex-snapshot
LOGAN: Membership Inference Attacks Against Generative Models
inferredcites →https://doi.org/10.2478/popets-2019-0067openalex-snapshot
Monte Carlo and Reconstruction Membership Inference Attacks against Generative Models
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/aaai.12209openalex-snapshot
A survey of security and privacy issues of machine unlearning
inferred← citeshttps://doi.org/10.1007/978-3-032-00891-6_12openalex-snapshot
Defenses Against Membership Inference Attacks on Unlearned Data
inferred← citeshttps://doi.org/10.1007/978-3-032-06096-9_16openalex-snapshot
“I Forgot About You”: Exploring Multi-Label Unlearning (MLU) for Responsible Facial Recognition Systems
inferred← citeshttps://doi.org/10.1007/978-981-96-1551-3_16openalex-snapshot
Enhancing Privacy in Machine Unlearning: Posterior Perturbation Against Membership Inference Attack
inferred← citeshttps://doi.org/10.1007/s10586-026-06300-9openalex-snapshot
Machine unlearning through model forgetting techniques: application area and emerging methods
inferred← citeshttps://doi.org/10.1007/s11280-023-01149-zopenalex-snapshot
Transfer learning based cascaded deep learning network and mask recognition for COVID-19
inferred← citeshttps://doi.org/10.1007/s11280-023-01159-xopenalex-snapshot
Beyond model splitting: Preventing label inference attacks in vertical federated learning with dispersed training
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113011openalex-snapshot
Enhancing AI safety of machine unlearning for ensembled models
inferred← citeshttps://doi.org/10.1016/j.comnet.2026.112438openalex-snapshot
PSODS-FU: Particle swarm optimization and dynamic scoring-driven federated unlearning framework for IoV
inferred← citeshttps://doi.org/10.1016/j.jiixd.2024.02.001openalex-snapshot
A survey on membership inference attacks and defenses in machine learning
inferred← citeshttps://doi.org/10.1016/j.neucom.2025.131110openalex-snapshot
FeaUn: Feature unlearning in vertical federated learning for IIoT against feature inference attacks
inferred← citeshttps://doi.org/10.1109/globecom54140.2023.10437231openalex-snapshot
Conditional Matching GAN Guided Reconstruction Attack in Machine Unlearning
inferred← citeshttps://doi.org/10.1109/ojcs.2025.3543483openalex-snapshot
Threats, Attacks, and Defenses in Machine Unlearning: A Survey
inferred← citeshttps://doi.org/10.1109/pcds65695.2025.00035openalex-snapshot
Boundary-Anchored Functional Duplication Attacks on Machine Unlearning
inferred← citeshttps://doi.org/10.1109/tccn.2025.3594672openalex-snapshot
A Zero-Shot Federated Unlearning Framework With Stability Verification
inferred← citeshttps://doi.org/10.1109/tdsc.2024.3476533openalex-snapshot
Guaranteeing Data Privacy in Federated Unlearning With Dynamic User Participation
inferred← citeshttps://doi.org/10.1109/tdsc.2025.3542092openalex-snapshot
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
inferred← citeshttps://doi.org/10.1109/tifs.2025.3623364openalex-snapshot
Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage
inferred← citeshttps://doi.org/10.1109/tmc.2025.3582904openalex-snapshot
The Price of Forgetting: Incentive Mechanism Design for Machine Unlearning
inferred← citeshttps://doi.org/10.1109/tps-isa62245.2024.00040openalex-snapshot
Towards Privacy-Preserving and Secure Machine Unlearning: Taxonomy, Challenges and Research Directions
inferred← citeshttps://doi.org/10.1145/3679014openalex-snapshot
A Survey on Federated Unlearning: Challenges, Methods, and Future Directions
inferred← citeshttps://doi.org/10.1145/3779299openalex-snapshot
The Many Faces of Data Deletion: On the Significance and Implications of Deleting Data
inferred← citeshttps://doi.org/10.1186/s13677-023-00478-8openalex-snapshot
IoV data sharing scheme based on the hybrid architecture of blockchain and cloud-edge computing
inferred← citeshttps://doi.org/10.3390/app13169341openalex-snapshot
Machine Unlearning by Reversing the Continual Learning
inferred← citeshttps://doi.org/10.3390/app15095086openalex-snapshot
Graph-Level Label-Only Membership Inference Attack Against Graph Neural Networks
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