Label-Only Membership Inference Attack Based on Model Explanation
Sign Up to like & getrecommendations! Published in 2024 at "Neural Processing Letters"
DOI: 10.1007/s11063-024-11682-1
Abstract: It is well known that machine learning models (e.g., image recognition) can unintentionally leak information about the training set. Conventional membership inference relies on posterior vectors, and this task becomes extremely difficult when the posterior… read more here.
Keywords: membership inference; inference; label membership; inference attack ... See more keywords
Membership Inference Attacks With Token-Level Deduplication on Korean Language Models
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3239668
Abstract: The confidentiality threat against training data has become a significant security problem in neural language models. Recent studies have shown that memorized training data can be extracted by injecting well-chosen prompts into generative language models.… read more here.
Keywords: token level; language; attack; language models ... See more keywords
Universal and Efficient Adversarial Training Framework With Membership Inference Resistance
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3551762
Abstract: Adversarial training is an effective approach to enhance the robustness of machine learning models via adding adversarial examples into the training phase. However, existing adversarial training methods increase the advantage of membership inference attacks, which… read more here.
Keywords: training framework; training; adversarial training; membership inference ... See more keywords
Label-Only Membership Inference Attacks and Defenses in Semantic Segmentation Models
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2022.3154029
Abstract: Recent research has discovered that deep learning models are vulnerable to membership inference attacks, which can reveal whether a sample is in the training dataset of the victim model or not. Most membership inference attacks… read more here.
Keywords: membership inference; inference attacks; segmentation models;
Attention-Based Membership Inference Attacks on Graph Neural Network Through Topological Features
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2025.3586251
Abstract: Graph Neural Networks (GNNs), a type of machine learning model has been widely used in social networks, drug recommendations, and various other domains. While GNNs provide significant benefits, they also raise privacy concerns such as… read more here.
Keywords: inference attacks; attack; membership inference; attention ... See more keywords
Unlocking Generative Priors: A New Membership Inference Framework for Diffusion Models
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2025.3560776
Abstract: Diffusion models pose risks of privacy breaches and copyright disputes, primarily stemming from the potential utilization of unauthorized data during the training phase. Membership inference is aimed to determine whether a specific sample has been… read more here.
Keywords: diffusion; membership inference; generative priors; diffusion models ... See more keywords
Unveiling Privacy Risks in the Long Tail: Membership Inference in Class Skewness
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Information Forensics and Security"
DOI: 10.1109/tifs.2025.3607261
Abstract: Real-world datasets often exhibit long-tailed distributions, raising important questions about how privacy risks evolve when machine learning (ML) models are applied to such data. In this work, we present a comprehensive analysis of membership inference… read more here.
Keywords: long tailed; privacy risks; privacy; membership inference ... See more keywords
Practical Membership Inference Attack Against Collaborative Inference in Industrial IoT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2020.3046648
Abstract: The effectiveness of state-of-the-art deep learning (DL) models has empowered the development of industrial Internet of things (IIoT). Recently, considering resource-constrained and privacy-required IIoT devices, collaborative inference has been proposed, which splits DL models and… read more here.
Keywords: inference attack; membership inference; inference; collaborative inference ... See more keywords
LTU Attacker for Membership Inference
Sign Up to like & getrecommendations! Published in 2022 at "Algorithms"
DOI: 10.3390/a15070254
Abstract: We address the problem of defending predictive models, such as machine learning classifiers (Defender models), against membership inference attacks, in both the black-box and white-box setting, when the trainer and the trained model are publicly… read more here.
Keywords: ltu attacker; attacker; privacy; attack ... See more keywords
Targeted Training Data Extraction—Neighborhood Comparison-Based Membership Inference Attacks in Large Language Models
Sign Up to like & getrecommendations! Published in 2024 at "Applied Sciences"
DOI: 10.3390/app14167118
Abstract: A large language model refers to a deep learning model characterized by extensive parameters and pretraining on a large-scale corpus, utilized for processing natural language text and generating high-quality text output. The increasing deployment of… read more here.
Keywords: large language; membership inference; training data; extraction ... See more keywords
Mitigating Membership Inference Attacks via Generative Denoising Mechanisms
Sign Up to like & getrecommendations! Published in 2025 at "Mathematics"
DOI: 10.3390/math13193070
Abstract: Membership Inference Attacks (MIAs) pose a significant threat to privacy in modern machine learning systems, enabling adversaries to determine whether a specific data record was used during model training. Existing defense techniques often degrade model… read more here.
Keywords: inference attacks; diffusion; privacy; membership inference ... See more keywords