Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization
Fuente:
arXiv
Saved in:
| Main Authors: | Qiu, Yixiang, Liu, Yanhan, Yu, Hongyao, Fang, Hao, Chen, Bin, Xia, Shu-Tao, Xu, Ke |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filtering
by: Yu, Hongyao, et al.
Published: (2024)
by: Yu, Hongyao, et al.
Published: (2024)
MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
by: Qiu, Yixiang, et al.
Published: (2024)
by: Qiu, Yixiang, et al.
Published: (2024)
ICAS: Detecting Training Data from Autoregressive Image Generative Models
by: Yu, Hongyao, et al.
Published: (2025)
by: Yu, Hongyao, et al.
Published: (2025)
Towards Privacy-Preserving Split Learning: Destabilizing Adversarial Inference and Reconstruction Attacks in the Cloud
by: Higgins, Griffin, et al.
Published: (2025)
by: Higgins, Griffin, et al.
Published: (2025)
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
by: Xu, Xiaoyang, et al.
Published: (2024)
by: Xu, Xiaoyang, et al.
Published: (2024)
Exposing LLM User Privacy via Traffic Fingerprint Analysis: A Study of Privacy Risks in LLM Agent Interactions
by: Zhang, Yixiang, et al.
Published: (2025)
by: Zhang, Yixiang, et al.
Published: (2025)
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
by: Luo, Xinjian, et al.
Published: (2020)
by: Luo, Xinjian, et al.
Published: (2020)
Bayes-Nash Generative Privacy Against Membership Inference Attacks
by: Zhang, Tao, et al.
Published: (2024)
by: Zhang, Tao, et al.
Published: (2024)
Data Reconstruction: Identifiability and Optimization with Sample Splitting
by: Shen, Yujie, et al.
Published: (2026)
by: Shen, Yujie, et al.
Published: (2026)
RASE: Efficient Privacy-preserving Data Aggregation against Disclosure Attacks for IoTs
by: Wang, Zuyan, et al.
Published: (2024)
by: Wang, Zuyan, et al.
Published: (2024)
Privacy Leaks by Adversaries: Adversarial Iterations for Membership Inference Attack
by: Xue, Jing, et al.
Published: (2025)
by: Xue, Jing, et al.
Published: (2025)
Learning to Attack: Uncovering Privacy Risks in Sequential Data Releases
by: Cui, Ziyao, et al.
Published: (2025)
by: Cui, Ziyao, et al.
Published: (2025)
Revisiting Privacy Leakage in Machine Unlearning: Membership Inference Beyond the Forgotten Set
by: Fu, Jie, et al.
Published: (2026)
by: Fu, Jie, et al.
Published: (2026)
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis
by: Deng, Ruijun, et al.
Published: (2025)
by: Deng, Ruijun, et al.
Published: (2025)
Similarity-based Label Inference Attack against Training and Inference of Split Learning
by: Liu, Junlin, et al.
Published: (2022)
by: Liu, Junlin, et al.
Published: (2022)
Approximate DBSCAN under Differential Privacy
by: Qiu, Yuan, et al.
Published: (2025)
by: Qiu, Yuan, et al.
Published: (2025)
Secure and Scalable Face Retrieval via Cancelable Product Quantization
by: Tang, Haomiao, et al.
Published: (2025)
by: Tang, Haomiao, et al.
Published: (2025)
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning
by: Khan, Tanveer, et al.
Published: (2024)
by: Khan, Tanveer, et al.
Published: (2024)
PIG: Privacy Jailbreak Attack on LLMs via Gradient-based Iterative In-Context Optimization
by: Wang, Yidan, et al.
Published: (2025)
by: Wang, Yidan, et al.
Published: (2025)
Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary Information
by: Chhillar, Somiya, et al.
Published: (2025)
by: Chhillar, Somiya, et al.
Published: (2025)
Mitigating Data Poisoning Attacks to Local Differential Privacy
by: Li, Xiaolin, et al.
Published: (2025)
by: Li, Xiaolin, et al.
Published: (2025)
Security and Privacy on Generative Data in AIGC: A Survey
by: Wang, Tao, et al.
Published: (2023)
by: Wang, Tao, et al.
Published: (2023)
Revisiting Training-Inference Trigger Intensity in Backdoor Attacks
by: Lin, Chenhao, et al.
Published: (2025)
by: Lin, Chenhao, et al.
Published: (2025)
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
by: Arcolezi, Héber H., et al.
Published: (2025)
by: Arcolezi, Héber H., et al.
Published: (2025)
A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks
by: Qiu, Yixiang, et al.
Published: (2024)
by: Qiu, Yixiang, et al.
Published: (2024)
Learning-based Privacy-Preserving Graph Publishing Against Sensitive Link Inference Attacks
by: Wu, Yucheng, et al.
Published: (2025)
by: Wu, Yucheng, et al.
Published: (2025)
Passive Inference Attacks on Split Learning via Adversarial Regularization
by: Zhu, Xiaochen, et al.
Published: (2023)
by: Zhu, Xiaochen, et al.
Published: (2023)
Prompt2Fingerprint: Plug-and-Play LLM Fingerprinting via Text-to-Weight Generation
by: Chen, Sixu, et al.
Published: (2026)
by: Chen, Sixu, et al.
Published: (2026)
Auditing Privacy Mechanisms via Label Inference Attacks
by: Busa-Fekete, Róbert István, et al.
Published: (2024)
by: Busa-Fekete, Róbert István, et al.
Published: (2024)
A Linear Reconstruction Approach for Attribute Inference Attacks against Synthetic Data
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2023)
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2023)
Unifying Re-Identification, Attribute Inference, and Data Reconstruction Risks in Differential Privacy
by: Kulynych, Bogdan, et al.
Published: (2025)
by: Kulynych, Bogdan, et al.
Published: (2025)
Membership Inference Attacks on Vision-Language-Action Models
by: Peng, Yuefeng, et al.
Published: (2026)
by: Peng, Yuefeng, et al.
Published: (2026)
Smart Car Privacy: Survey of Attacks and Privacy Issues
by: Deshmukh, Akshay Madhav
Published: (2025)
by: Deshmukh, Akshay Madhav
Published: (2025)
Label Inference Attacks against Federated Unlearning
by: Wang, Wei, et al.
Published: (2025)
by: Wang, Wei, et al.
Published: (2025)
Spore: Efficient and Training-Free Privacy Extraction Attack on LLMs via Inference-Time Hybrid Probing
by: Cui, Yu, et al.
Published: (2026)
by: Cui, Yu, et al.
Published: (2026)
Over-the-Air Collaborative Inference with Feature Differential Privacy
by: Seif, Mohamed, et al.
Published: (2024)
by: Seif, Mohamed, et al.
Published: (2024)
PAnDA: Rethinking Metric Differential Privacy Optimization at Scale with Anchor-Based Approximation
by: Liu, Ruiyao, et al.
Published: (2025)
by: Liu, Ruiyao, et al.
Published: (2025)
Revisiting the LiRA Membership Inference Attack Under Realistic Assumptions
by: Jebreel, Najeeb, et al.
Published: (2026)
by: Jebreel, Najeeb, et al.
Published: (2026)
CURE: Privacy-Preserving Split Learning Done Right
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
From Mean to Extreme: Formal Differential Privacy Bounds on the Success of Real-World Data Reconstruction Attacks
by: Riess, Anneliese, et al.
Published: (2024)
by: Riess, Anneliese, et al.
Published: (2024)
Similar Items
-
Rank Matters: Understanding and Defending Model Inversion Attacks via Low-Rank Feature Filtering
by: Yu, Hongyao, et al.
Published: (2024) -
MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense
by: Qiu, Yixiang, et al.
Published: (2024) -
ICAS: Detecting Training Data from Autoregressive Image Generative Models
by: Yu, Hongyao, et al.
Published: (2025) -
Towards Privacy-Preserving Split Learning: Destabilizing Adversarial Inference and Reconstruction Attacks in the Cloud
by: Higgins, Griffin, et al.
Published: (2025) -
A Stealthy Wrongdoer: Feature-Oriented Reconstruction Attack against Split Learning
by: Xu, Xiaoyang, et al.
Published: (2024)