Copertina

GraphSteal: Structural Knowledge Stealing from Graph RAG via Traversal Reconstruction

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Gu, Jinze, Mao, Qinghua, Lin, Xi, Wu, Jun
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Cryptography and Security Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

All Your Knowledge Belongs to Us: Stealing Knowledge Graphs via Reasoning APIs
di: Xi, Zhaohan
Pubblicazione: (2025)

Prompt Stealing Attacks Against Large Language Models
di: Sha, Zeyang, et al.
Pubblicazione: (2024)

PRSA: Prompt Stealing Attacks against Real-World Prompt Services
di: Yang, Yong, et al.
Pubblicazione: (2024)

Stealing Training Graphs from Graph Neural Networks
di: Lin, Minhua, et al.
Pubblicazione: (2024)

Stealing User Prompts from Mixture of Experts
di: Yona, Itay, et al.
Pubblicazione: (2024)

On Stealing Graph Neural Network Models
di: Podhajski, Marcin, et al.
Pubblicazione: (2025)

You Can't Steal Nothing: Mitigating Prompt Leakages in LLMs via System Vectors
di: Cao, Bochuan, et al.
Pubblicazione: (2025)

Intrinsic Fingerprint of LLMs: Continue Training is NOT All You Need to Steal A Model!
di: Yoon, Do-hyeon, et al.
Pubblicazione: (2025)

DM4Steal: Diffusion Model For Link Stealing Attack On Graph Neural Networks
di: Chen, Jinyin, et al.
Pubblicazione: (2024)

Benchmarking Safety Risks of Knowledge-Intensive Reasoning under Malicious Knowledge Editing
di: Mao, Qinghua, et al.
Pubblicazione: (2026)

Teach LLMs to Phish: Stealing Private Information from Language Models
di: Panda, Ashwinee, et al.
Pubblicazione: (2024)

Link Stealing Attacks Against Inductive Graph Neural Networks
di: Wu, Yixin, et al.
Pubblicazione: (2024)

Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity
di: Zhu, Zhihao, et al.
Pubblicazione: (2023)

Prompt Pirates Need a Map: Stealing Seeds helps Stealing Prompts
di: Mächtle, Felix, et al.
Pubblicazione: (2025)

GRID: Protecting Training Graph from Link Stealing Attacks on GNN Models
di: Lou, Jiadong, et al.
Pubblicazione: (2025)

RAG Safety: Exploring Knowledge Poisoning Attacks to Retrieval-Augmented Generation
di: Zhao, Tianzhe, et al.
Pubblicazione: (2025)

GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning
di: Zhu, Jiani, et al.
Pubblicazione: (2024)

How to Steal Reasoning Without Reasoning Traces
di: Zhang, Tingwei, et al.
Pubblicazione: (2026)

Stealing Part of a Production Language Model
di: Carlini, Nicholas, et al.
Pubblicazione: (2024)

Stealix: Model Stealing via Prompt Evolution
di: Zhuang, Zhixiong, et al.
Pubblicazione: (2025)

Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks
di: Guan, Faqian, et al.
Pubblicazione: (2024)

Efficient Data-Free Model Stealing with Label Diversity
di: Liu, Yiyong, et al.
Pubblicazione: (2024)

Merger-as-a-Stealer: Stealing Targeted PII from Aligned LLMs with Model Merging
di: Lu, Lin, et al.
Pubblicazione: (2025)

LinkThief: Combining Generalized Structure Knowledge with Node Similarity for Link Stealing Attack against GNN
di: Zhang, Yuxing, et al.
Pubblicazione: (2024)

BarkBeetle: Stealing Decision Tree Models with Fault Injection
di: Wang, Qifan, et al.
Pubblicazione: (2025)

Transpose Attack: Stealing Datasets with Bidirectional Training
di: Amit, Guy, et al.
Pubblicazione: (2023)

GraphIP-Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?
di: Zhao, Kaixiang, et al.
Pubblicazione: (2026)

InputSnatch: Stealing Input in LLM Services via Timing Side-Channel Attacks
di: Zheng, Xinyao, et al.
Pubblicazione: (2024)

Stealing Training Data from Large Language Models in Decentralized Training through Activation Inversion Attack
di: Dai, Chenxi, et al.
Pubblicazione: (2025)

Examining the Threat Landscape: Foundation Models and Model Stealing
di: Raj, Ankita, et al.
Pubblicazione: (2025)

Stealing Trust: Unraveling Blind Message Attacks in Web3 Authentication
di: Yan, Kailun, et al.
Pubblicazione: (2024)

LLMAtKGE: Large Language Models as Explainable Attackers against Knowledge Graph Embeddings
di: Li, Ting, et al.
Pubblicazione: (2025)

TrEEStealer: Stealing Decision Trees via Enclave Side Channels
di: Sander, Jonas, et al.
Pubblicazione: (2026)

Medical Multimodal Model Stealing Attacks via Adversarial Domain Alignment
di: Shen, Yaling, et al.
Pubblicazione: (2025)

Watermark Stealing in Large Language Models
di: Jovanović, Nikola, et al.
Pubblicazione: (2024)

Autonomous Chain-of-Thought Distillation for Graph-Based Fraud Detection
di: Li, Yuan, et al.
Pubblicazione: (2026)

BESA: Boosting Encoder Stealing Attack with Perturbation Recovery
di: Ren, Xuhao, et al.
Pubblicazione: (2025)

Privacy Backdoors: Stealing Data with Corrupted Pretrained Models
di: Feng, Shanglun, et al.
Pubblicazione: (2024)

When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?
di: Wang, Shang, et al.
Pubblicazione: (2024)

Black-Box Skill Stealing Attack from Proprietary LLM Agents: An Empirical Study
di: Wang, Zihan, et al.
Pubblicazione: (2026)