Cover Image

Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dai, Jiazhu, Lu, Yubing
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Semantic and Clean-label Backdoor Attack against Graph Convolutional Networks
by: Dai, Jiazhu, et al.
Published: (2025)

A Clean-graph Backdoor Attack against Graph Convolutional Networks with Poisoned Label Only
by: Dai, Jiazhu, et al.
Published: (2024)

Double-Dip: Thwarting Label-Only Membership Inference Attacks with Transfer Learning and Randomization
by: Rajabi, Arezoo, et al.
Published: (2024)

Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks
by: Zhang, Yuxiang, et al.
Published: (2026)

Graph Transductive Defense: a Two-Stage Defense for Graph Membership Inference Attacks
by: Niu, Peizhi, et al.
Published: (2024)

Hyperparameters in Score-Based Membership Inference Attacks
by: Pradhan, Gauri, et al.
Published: (2025)

Privacy Auditing of Multi-domain Graph Pre-trained Model under Membership Inference Attacks
by: Luo, Jiayi, et al.
Published: (2025)

Gradient Inversion Attack on Graph Neural Networks
by: Sinha, Divya Anand, et al.
Published: (2024)

LiSA: Leveraging Link Recommender to Attack Graph Neural Networks via Subgraph Injection
by: Zhang, Wenlun, et al.
Published: (2025)

Effective backdoor attack on graph neural networks in link prediction tasks
by: Dai, Jiazhu, et al.
Published: (2024)

Membership Inference Attacks on Discrete Diffusion Language Models
by: Kasivelrajan, Shailesh
Published: (2026)

Generalization and Membership Inference Attack a Practical Perspective
by: Rahmani, Fateme, et al.
Published: (2026)

Membership Inference Attacks Against Time-Series Models
by: Koren, Noam, et al.
Published: (2024)

Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense
by: Zhan, Haoxi, et al.
Published: (2021)

Membership Inference Attack with Partial Features
by: Wang, Xurun, et al.
Published: (2025)

On Membership Inference Attacks in Knowledge Distillation
by: Cui, Ziyao, et al.
Published: (2025)

Neural Breadcrumbs: Membership Inference Attacks on LLMs Through Hidden State and Attention Pattern Analysis
by: Makhija, Disha, et al.
Published: (2025)

Training-free Graph Neural Networks and the Power of Labels as Features
by: Sato, Ryoma
Published: (2024)

On the Privacy Risks of Spiking Neural Networks: A Membership Inference Analysis
by: Guan, Junyi, et al.
Published: (2025)

How does Bayesian Sampling help Membership Inference Attacks?
by: Liu, Zhenlong, et al.
Published: (2025)

Automatic Calibration for Membership Inference Attack on Large Language Models
by: Zade, Saleh Zare, et al.
Published: (2025)

Fundamental Limits of Membership Inference Attacks on Machine Learning Models
by: Aubinais, Eric, et al.
Published: (2023)

Parallelizing Node-Level Explainability in Graph Neural Networks
by: Llorente, Oscar, et al.
Published: (2026)

Similarity-based Label Inference Attack against Training and Inference of Split Learning
by: Liu, Junlin, et al.
Published: (2022)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)

Membership Inference Attacks Against Fine-tuned Diffusion Language Models
by: Chen, Yuetian, et al.
Published: (2026)

Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning
by: Hu, Qiang, et al.
Published: (2024)

GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization
by: Yang, Xiaodong, et al.
Published: (2024)

Inference Attacks Against Graph Generative Diffusion Models
by: Wang, Xiuling, et al.
Published: (2026)

Context-Aware Membership Inference Attacks against Pre-trained Large Language Models
by: Chang, Hongyan, et al.
Published: (2024)

Graphs Unveiled: Graph Neural Networks and Graph Generation
by: Kovács, László, et al.
Published: (2024)

Conformalized Link Prediction on Graph Neural Networks
by: Zhao, Tianyi, et al.
Published: (2024)

AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation
by: Chen, Ying, et al.
Published: (2025)

GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation
by: Galichin, Andrey V., et al.
Published: (2024)

Faithful Interpretation for Graph Neural Networks
by: Hu, Lijie, et al.
Published: (2024)

Label Deconvolution for Node Representation Learning on Large-scale Attributed Graphs against Learning Bias
by: Shi, Zhihao, et al.
Published: (2023)

OpenGLT: A Comprehensive Benchmark of Graph Neural Networks for Graph-Level Tasks
by: Li, Haoyang, et al.
Published: (2025)

Membership Inference Attacks against Large Vision-Language Models
by: Li, Zhan, et al.
Published: (2024)

Center-Based Relaxed Learning Against Membership Inference Attacks
by: Fang, Xingli, et al.
Published: (2024)