Saved in:
| Main Authors: | Wu, Genqiang, Zhang, Xiaoying, Qi, Yu, Wang, Hao, Wang, Jikui, He, Yeping |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.00689 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Maximal $α$-Leakage for Quantum Privacy Mechanisms
by: Yang, Bo-Yu, et al.
Published: (2024)
by: Yang, Bo-Yu, et al.
Published: (2024)
Achieving Dalenius' Goal of Data Privacy with Practical Assumptions
by: Wu, Genqiang, et al.
Published: (2017)
by: Wu, Genqiang, et al.
Published: (2017)
Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage
by: Saeidian, Sara, et al.
Published: (2025)
by: Saeidian, Sara, et al.
Published: (2025)
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
by: Wang, Weiqi, et al.
Published: (2025)
by: Wang, Weiqi, et al.
Published: (2025)
The Gradient Puppeteer: Adversarial Domination in Gradient Leakage Attacks through Model Poisoning
by: Xiang, Kunlan, et al.
Published: (2025)
by: Xiang, Kunlan, et al.
Published: (2025)
Rethinking Disclosure Prevention with Pointwise Maximal Leakage
by: Saeidian, Sara, et al.
Published: (2023)
by: Saeidian, Sara, et al.
Published: (2023)
SMOTE and Mirrors: Exposing Privacy Leakage from Synthetic Minority Oversampling
by: Ganev, Georgi, et al.
Published: (2025)
by: Ganev, Georgi, 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)
Observable Channels, Not Just Storage: Evaluating Privacy Leakage in LLM Agent Pipelines
by: Huang, Tao, et al.
Published: (2026)
by: Huang, Tao, et al.
Published: (2026)
EdgeLeakage: Membership Information Leakage in Distributed Edge Intelligence Systems
by: Chen, Kongyang, et al.
Published: (2024)
by: Chen, Kongyang, et al.
Published: (2024)
Evaluating Privacy Leakage in Split Learning
by: Qiu, Xinchi, et al.
Published: (2023)
by: Qiu, Xinchi, et al.
Published: (2023)
LeakAgent: RL-based Red-teaming Agent for LLM Privacy Leakage
by: Nie, Yuzhou, et al.
Published: (2024)
by: Nie, Yuzhou, et al.
Published: (2024)
Analysis of Privacy Leakage in Federated Large Language Models
by: Vu, Minh N., et al.
Published: (2024)
by: Vu, Minh N., et al.
Published: (2024)
Unveiling Client Privacy Leakage from Public Dataset Usage in Federated Distillation
by: Shi, Haonan, et al.
Published: (2025)
by: Shi, Haonan, et al.
Published: (2025)
Membership Information Leakage in Federated Contrastive Learning
by: Chen, Kongyang, et al.
Published: (2024)
by: Chen, Kongyang, et al.
Published: (2024)
The Hidden Cost of Correlation: Rethinking Privacy Leakage in Local Differential Privacy
by: Jayawardana, Sandaru, et al.
Published: (2025)
by: Jayawardana, Sandaru, et al.
Published: (2025)
Real-Time Privacy Risk Measurement with Privacy Tokens for Gradient Leakage
by: Meng, Jiayang, et al.
Published: (2025)
by: Meng, Jiayang, et al.
Published: (2025)
CoLA: A Choice Leakage Attack Framework to Expose Privacy Risks in Subset Training
by: Li, Qi, et al.
Published: (2026)
by: Li, Qi, et al.
Published: (2026)
Slowly Scaling Per-Record Differential Privacy
by: Finley, Brian, et al.
Published: (2024)
by: Finley, Brian, et al.
Published: (2024)
RTBAS: Defending LLM Agents Against Prompt Injection and Privacy Leakage
by: Zhong, Peter Yong, et al.
Published: (2025)
by: Zhong, Peter Yong, et al.
Published: (2025)
Synth-MIA: A Testbed for Auditing Privacy Leakage in Tabular Data Synthesis
by: Ward, Joshua, et al.
Published: (2025)
by: Ward, Joshua, et al.
Published: (2025)
S-Leak: Leakage-Abuse Attack Against Efficient Conjunctive SSE via s-term Leakage
by: Su, Yue, et al.
Published: (2025)
by: Su, Yue, et al.
Published: (2025)
PrivTru: A Privacy-by-Design Data Trustee Minimizing Information Leakage
by: Gehring, Lukas, et al.
Published: (2025)
by: Gehring, Lukas, et al.
Published: (2025)
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)
Sanitize Your Responses: Mitigating Privacy Leakage in Large Language Models
by: Fu, Wenjie, et al.
Published: (2025)
by: Fu, Wenjie, et al.
Published: (2025)
Maximal Information Leakage from Quantum Encoding of Classical Data
by: Farokhi, Farhad
Published: (2023)
by: Farokhi, Farhad
Published: (2023)
Information Leakage Envelopes
by: Saeidian, Sara, et al.
Published: (2026)
by: Saeidian, Sara, et al.
Published: (2026)
Nonmalleable Progress Leakage
by: Cecchetti, Ethan
Published: (2025)
by: Cecchetti, Ethan
Published: (2025)
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction Attack
by: Lumbut, Chayadon, et al.
Published: (2024)
by: Lumbut, Chayadon, et al.
Published: (2024)
CompLeak: Deep Learning Model Compression Exacerbates Privacy Leakage
by: Li, Na, et al.
Published: (2025)
by: Li, Na, et al.
Published: (2025)
Exploiting Sequence Number Leakage: TCP Hijacking in NAT-Enabled Wi-Fi Networks
by: Yang, Yuxiang, et al.
Published: (2024)
by: Yang, Yuxiang, et al.
Published: (2024)
Information Leakage in Data Linkage
by: Christen, Peter, et al.
Published: (2025)
by: Christen, Peter, et al.
Published: (2025)
A Framework for Managing Multifaceted Privacy Leakage While Optimizing Utility in Continuous LBS Interactions
by: Bkakria, Anis, et al.
Published: (2024)
by: Bkakria, Anis, et al.
Published: (2024)
PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning
by: Hou, Sizai, et al.
Published: (2024)
by: Hou, Sizai, et al.
Published: (2024)
Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions
by: Liu, Jinxin, et al.
Published: (2024)
by: Liu, Jinxin, et al.
Published: (2024)
Information Leakage from Embedding in Large Language Models
by: Wan, Zhipeng, et al.
Published: (2024)
by: Wan, Zhipeng, et al.
Published: (2024)
What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
by: Fan, Mingyuan, et al.
Published: (2026)
by: Fan, Mingyuan, et al.
Published: (2026)
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
by: Rashid, Md Rafi Ur, et al.
Published: (2024)
by: Rashid, Md Rafi Ur, et al.
Published: (2024)
CanaryBench: Stress Testing Privacy Leakage in Cluster-Level Conversation Summaries
by: Mehta, Deep
Published: (2026)
by: Mehta, Deep
Published: (2026)
DeepLeak: Privacy Enhancing Hardening of Model Explanations Against Membership Leakage
by: Hmida, Firas Ben, et al.
Published: (2026)
by: Hmida, Firas Ben, et al.
Published: (2026)
Similar Items
-
Maximal $α$-Leakage for Quantum Privacy Mechanisms
by: Yang, Bo-Yu, et al.
Published: (2024) -
Achieving Dalenius' Goal of Data Privacy with Practical Assumptions
by: Wu, Genqiang, et al.
Published: (2017) -
Evaluating Differential Privacy on Correlated Datasets Using Pointwise Maximal Leakage
by: Saeidian, Sara, et al.
Published: (2025) -
CRFU: Compressive Representation Forgetting Against Privacy Leakage on Machine Unlearning
by: Wang, Weiqi, et al.
Published: (2025) -
The Gradient Puppeteer: Adversarial Domination in Gradient Leakage Attacks through Model Poisoning
by: Xiang, Kunlan, et al.
Published: (2025)