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Inference Attack

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TitleStatusHype
A Privacy-Preserving Unsupervised Domain Adaptation Framework for Clinical Text Analysis—0
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks—0
Killing One Bird with Two Stones: Model Extraction and Attribute Inference Attacks against BERT-based APIs—0
Trade-offs and Guarantees of Adversarial Representation Learning for Information Obfuscation—0
Knowledge Cross-Distillation for Membership Privacy—0
On the Alignment of Group Fairness with Attribute Privacy—0
Data Plagiarism Index: Characterizing the Privacy Risk of Data-Copying in Tabular Generative Models—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
DAMIA: Leveraging Domain Adaptation as a Defense against Membership Inference Attacks—0
Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature—0
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges—0
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning—0
An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks—0
An Extension of Fano's Inequality for Characterizing Model Susceptibility to Membership Inference Attacks—0
Comprehensive Privacy Analysis on Federated Recommender System against Attribute Inference Attacks—0
Adversarial Privacy Preservation under Attribute Inference Attack—0
TrISec: Training Data-Unaware Imperceptible Security Attacks on Deep Neural Networks—0
Inferring Communities of Interest in Collaborative Learning-based Recommender Systems—0
Federated Graph Condensation with Information Bottleneck Principles—0
A new membership inference attack that spots memorization in generative and predictive models: Loss-Based with Reference Model algorithm (LBRM)—0
Similarity-based Label Inference Attack against Training and Inference of Split Learning—0
Adversarial Machine Learning-Based Anticipation of Threats Against Vehicle-to-Microgrid Services—0
Active Deep Learning Attacks under Strict Rate Limitations for Online API Calls—0
Interaction-level Membership Inference Attack Against Federated Recommender Systems—0
Is My Data in Your Retrieval Database? Membership Inference Attacks Against Retrieval Augmented Generation—0
Local Model Reconstruction Attacks in Federated Learning and their Uses—0
An Efficient Subpopulation-based Membership Inference Attack—0
Breaking Secure Aggregation: Label Leakage from Aggregated Gradients in Federated Learning—0
A Comprehensive Study of Privacy Risks in Curriculum Learning—0
BLIA: Detect model memorization in binary classification model through passive Label Inference attack—0
Eliminating Label Leakage in Tree-Based Vertical Federated Learning—0
Identity-Focused Inference and Extraction Attacks on Diffusion Models—0
Inference Attacks Against Face Recognition Model without Classification Layers—0
Efficient Membership Inference Attacks by Bayesian Neural Network—0
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability—0
Black-Box Training Data Identification in GANs via Detector Networks—0
Effectiveness of L2 Regularization in Privacy-Preserving Machine Learning—0
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression—0
Bounding Information Leakage in Machine Learning—0
Epsilon*: Privacy Metric for Machine Learning Models—0
A Blessing of Dimensionality in Membership Inference through Regularization—0
Evaluation of Inference Attack Models for Deep Learning on Medical Data—0
An Analysis Of Protected Health Information Leakage In Deep-Learning Based De-Identification Algorithms—0
EXPLORING VULNERABILITIES OF BERT-BASED APIS—0
Eavesdrop the Composition Proportion of Training Labels in Federated Learning—0
Exposing Privacy Gaps: Membership Inference Attack on Preference Data for LLM Alignment—0
A Zero Auxiliary Knowledge Membership Inference Attack on Aggregate Location Data—0
Feature Inference Attack on Shapley Values—0
Pathway to Secure and Trustworthy ZSM for LLMs: Attacks, Defense, and Opportunities—0
A Volumetric Approach to Privacy of Dynamical Systems—0
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