Cover Image

SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Xia, Yuyang, Liu, Ruixuan, Xiong, Li
Format:	Preprint
Published:	2025
Subjects:	Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

UniAud: A Unified Auditing Framework for High Auditing Power and Utility with One Training Run
by: Liu, Ruixuan, et al.
Published: (2025)

ContextLeak: Auditing Leakage in Private In-Context Learning Methods
by: Choi, Jacob, et al.
Published: (2025)

Auditing Private Prediction
by: Chadha, Karan, et al.
Published: (2024)

Revealing the True Cost of Locally Differentially Private Protocols: An Auditing Perspective
by: Arcolezi, Héber H., et al.
Published: (2023)

Nearly Tight Black-Box Auditing of Differentially Private Machine Learning
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2024)

DPDR: Gradient Decomposition and Reconstruction for Differentially Private Deep Learning
by: Liu, Yixuan, et al.
Published: (2024)

Optimal Guarantees for Auditing Rényi Differentially Private Machine Learning
by: Kim, Benjamin D., et al.
Published: (2026)

Private, Auditable, and Distributed Ledger for Financial Institutes
by: Eloul, Shaltiel, et al.
Published: (2025)

Auditable Ledger Snapshot for Non-Repudiable Cross-Blockchain Communication
by: Sengupta, Tirthankar, et al.
Published: (2025)

Differentially Private Auditing Under Strategic Response
by: Burnat, Florian A. D.
Published: (2026)

Behavioral Canaries: Auditing Private Retrieved Context Usage in RL Fine-Tuning
by: Chen, Chaoran, et al.
Published: (2026)

Sharpening Kubernetes Audit Logs with Context Awareness
by: Franzil, Matteo, et al.
Published: (2025)

The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD
by: Steinke, Thomas, et al.
Published: (2024)

"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation
by: Annamalai, Meenatchi Sundaram Muthu Selva, et al.
Published: (2024)

PCDP-SGD: Improving the Convergence of Differentially Private SGD via Projection in Advance
by: Sha, Haichao, et al.
Published: (2023)

Sequentially Auditing Differential Privacy
by: González, Tomás, et al.
Published: (2025)

Private, Verifiable, and Auditable AI Systems
by: South, Tobin
Published: (2025)

Privacy Audit as Bits Transmission: (Im)possibilities for Audit by One Run
by: Xiang, Zihang, et al.
Published: (2025)

DiffAudit: Auditing Privacy Practices of Online Services for Children and Adolescents
by: Figueira, Olivia, et al.
Published: (2024)

A Trajectory-Based Safety Audit of Clawdbot (OpenClaw)
by: Chen, Tianyu, et al.
Published: (2026)

Auditing $f$-Differential Privacy in One Run
by: Mahloujifar, Saeed, et al.
Published: (2024)

Model Context Protocol for Vision Systems: Audit, Security, and Protocol Extensions
by: Tiwari, Aditi, et al.
Published: (2025)

LiquiLM: Bridging the Semantic Gap in Liquidity Flaw Audit via DCN and LLMs
by: Liu, Zekai, et al.
Published: (2026)

A Game-Theoretic Analysis of Auditing Differentially Private Algorithms with Epistemically Disparate Herd
by: Yang, Ya-Ting, et al.
Published: (2024)

DP-BREM: Differentially-Private and Byzantine-Robust Federated Learning with Client Momentum
by: Gu, Xiaolan, et al.
Published: (2023)

Securing Private Federated Learning in a Malicious Setting: A Scalable TEE-Based Approach with Client Auditing
by: Takagi, Shun, et al.
Published: (2025)

KV-Auditor: Auditing Local Differential Privacy for Correlated Key-Value Estimation
by: Xu, Jingnan, et al.
Published: (2025)

Curator Attack: When Blackbox Differential Privacy Auditing Loses Its Power
by: Wang, Shiming, et al.
Published: (2024)

Privacy in Theory, Bugs in Practice: Grey-Box Auditing of Differential Privacy Libraries
by: Cebere, Tudor, et al.
Published: (2026)

Framework for Risk-Based IoT Cybersecurity Audit Engagements
by: Hanson, Danielle, et al.
Published: (2026)

Auditing Differential Privacy Guarantees Using Density Estimation
by: Koskela, Antti, et al.
Published: (2024)

Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare
by: Zhou, Juexiao, et al.
Published: (2023)

Locally Differentially Private In-Context Learning
by: Zheng, Chunyan, et al.
Published: (2024)

Auditing Differential Privacy in the Black-Box Setting
by: Shi, Kaining, et al.
Published: (2025)

Sealing the Audit-Runtime Gap for LLM Skills
by: Shen, Tingda, et al.
Published: (2026)

Tight Privacy Audit in One Run
by: Xiang, Zihang, et al.
Published: (2025)

How Well Can Differential Privacy Be Audited in One Run?
by: Keinan, Amit, et al.
Published: (2025)

On the Effectiveness of Mempool-based Transaction Auditing
by: Albrecht, Jannik, et al.
Published: (2026)

Holding Secrets Accountable: Auditing Privacy-Preserving Machine Learning
by: Lycklama, Hidde, et al.
Published: (2024)

PrivacyPeek: Auditing What LLM-Based Agents Acquire, Not Just What They Say
by: Zhang, Mingxuan, et al.
Published: (2026)