Cover Image

GraphPub: Generation of Differential Privacy Graph with High Availability

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xu, Wanghan, Shi, Bin, Liu, Ao, Zhang, Jiqiang, Dong, Bo
Format:	Preprint
Published:	2024
Subjects:	Social and Information Networks Artificial Intelligence Cryptography and Security Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

HiGraph: A Large-Scale Hierarchical Graph Dataset for Malware Analysis
by: Chen, Han, et al.
Published: (2025)

Graph Mining for Cybersecurity: A Survey
by: Yan, Bo, et al.
Published: (2023)

Exposing Privacy Risks in Graph Retrieval-Augmented Generation
by: Liu, Jiale, et al.
Published: (2025)

Privacy-Preserving Graph Embedding based on Local Differential Privacy
by: Li, Zening, et al.
Published: (2023)

MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection
by: Xu, Xiongxiao, et al.
Published: (2023)

Edge Private Graph Neural Networks with Singular Value Perturbation
by: Tang, Tingting, et al.
Published: (2024)

When Graph Structure Becomes a Liability: A Critical Re-Evaluation of Graph Neural Networks for Bitcoin Fraud Detection under Temporal Distribution Shift
by: Maganti, Saket
Published: (2026)

Large Language Models for Link Stealing Attacks Against Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2024)

Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs)
by: Olatunji, Iyiola E., et al.
Published: (2025)

Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency
by: Koskela, Antti, et al.
Published: (2025)

Differential Privacy on Trust Graphs
by: Ghazi, Badih, et al.
Published: (2024)

TBDetector:Transformer-Based Detector for Advanced Persistent Threats with Provenance Graph
by: Wang, Nan, et al.
Published: (2023)

AI-in-the-Loop: Privacy Preserving Real-Time Scam Detection and Conversational Scambaiting by Leveraging LLMs and Federated Learning
by: Hossain, Ismail, et al.
Published: (2025)

Optimality of Staircase Mechanisms for Vector Queries under Differential Privacy
by: Melbourne, James, et al.
Published: (2026)

Connect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation Systems
by: Yao, Mengyu, et al.
Published: (2026)

KnowGraph: Knowledge-Enabled Anomaly Detection via Logical Reasoning on Graph Data
by: Zhou, Andy, et al.
Published: (2024)

FedGraph-VASP: Privacy-Preserving Federated Graph Learning with Post-Quantum Security for Cross-Institutional Anti-Money Laundering
by: Commey, Daniel, et al.
Published: (2026)

Privacy-Preserving Semantic Communications via Multi-Task Learning and Adversarial Perturbations
by: Sagduyu, Yalin E., et al.
Published: (2025)

Local Differential Privacy-Preserving Spectral Clustering for General Graphs
by: Mukherjee, Sayan, et al.
Published: (2023)

Feature-Aware Anisotropic Local Differential Privacy for Utility-Preserving Graph Representation Learning in Metal Additive Manufacturing
by: Islam, MD Shafikul, et al.
Published: (2026)

Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank
by: Epasto, Alessandro, et al.
Published: (2022)

3D-IDS: Doubly Disentangled Dynamic Intrusion Detection
by: Qiu, Chenyang, et al.
Published: (2023)

Mind Your HEARTBEAT! Claw Background Execution Inherently Enables Silent Memory Pollution
by: Zhang, Yechao, et al.
Published: (2026)

AutoVerifier: An Agentic Automated Verification Framework Using Large Language Models
by: Du, Yuntao, et al.
Published: (2026)

Differential Privacy Mechanisms in Neural Tangent Kernel Regression
by: Gu, Jiuxiang, et al.
Published: (2024)

Research on the Design of a Short Video Recommendation System Based on Multimodal Information and Differential Privacy
by: Yang, Haowei, et al.
Published: (2025)

RAG with Differential Privacy
by: Grislain, Nicolas
Published: (2024)

Attacks on Node Attributes in Graph Neural Networks
by: Xu, Ying, et al.
Published: (2024)

Making Privacy-preserving Federated Graph Analytics with Strong Guarantees Practical (for Certain Queries)
by: Liu, Kunlong, et al.
Published: (2024)

Mind the Gap: Mixtures of Gaussians in Approximate Differential Privacy
by: Liu, Huikang, et al.
Published: (2026)

Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems
by: Lilienthal, Derek, et al.
Published: (2023)

"Humans welcome to observe": A First Look at the Agent Social Network Moltbook
by: Jiang, Yukun, et al.
Published: (2026)

On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models
by: Koskela, Antti, et al.
Published: (2025)

Cross-silo Federated Learning with Record-level Personalized Differential Privacy
by: Liu, Junxu, et al.
Published: (2024)

Your Privacy Depends on Others: Collusion Vulnerabilities in Individual Differential Privacy
by: Kaiser, Johannes, et al.
Published: (2026)

Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation
by: Yan, Bo, et al.
Published: (2023)

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy
by: Ponomareva, Natalia, et al.
Published: (2025)

Are We in the AI-Generated Text World Already? Quantifying and Monitoring AIGT on Social Media
by: Sun, Zhen, et al.
Published: (2024)

SoK: Practical Aspects of Releasing Differentially Private Graphs
by: D'Silva, Nicholas, et al.
Published: (2026)

An Attentive Graph Agent for Topology-Adaptive Cyber Defence
by: Sandoval, Ilya Orson, et al.
Published: (2025)