ExpProof : Operationalizing Explanations for Confidential Models with ZKPs
Fuente:
arXiv
Saved in:
| Main Authors: | Yadav, Chhavi, Laufer, Evan Monroe, Boneh, Dan, Chaudhuri, Kamalika |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FairProof : Confidential and Certifiable Fairness for Neural Networks
by: Yadav, Chhavi, et al.
Published: (2024)
by: Yadav, Chhavi, et al.
Published: (2024)
Can We Infer Confidential Properties of Training Data from LLMs?
by: Huang, Pengrun, et al.
Published: (2025)
by: Huang, Pengrun, et al.
Published: (2025)
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
by: Srivastava, Megha, et al.
Published: (2024)
by: Srivastava, Megha, et al.
Published: (2024)
DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
by: Wang, Erchi, et al.
Published: (2026)
by: Wang, Erchi, et al.
Published: (2026)
Influence-based Attributions can be Manipulated
by: Yadav, Chhavi, et al.
Published: (2024)
by: Yadav, Chhavi, et al.
Published: (2024)
A Middle Path for On-Premises LLM Deployment: Preserving Privacy Without Sacrificing Model Confidentiality
by: Huang, Hanbo, et al.
Published: (2024)
by: Huang, Hanbo, et al.
Published: (2024)
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis
by: Veeraragavan, Narasimha Raghavan, et al.
Published: (2024)
by: Veeraragavan, Narasimha Raghavan, et al.
Published: (2024)
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
by: Rabanser, Stephan, et al.
Published: (2025)
by: Rabanser, Stephan, et al.
Published: (2025)
SPICED: Syntactical Bug and Trojan Pattern Identification in A/MS Circuits using LLM-Enhanced Detection
by: Chaudhuri, Jayeeta, et al.
Published: (2024)
by: Chaudhuri, Jayeeta, et al.
Published: (2024)
Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis
by: Kotal, Anantaa, et al.
Published: (2023)
by: Kotal, Anantaa, et al.
Published: (2023)
Auditing $f$-Differential Privacy in One Run
by: Mahloujifar, Saeed, et al.
Published: (2024)
by: Mahloujifar, Saeed, et al.
Published: (2024)
PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking
by: Deng, Haiyu, et al.
Published: (2025)
by: Deng, Haiyu, et al.
Published: (2025)
NANOZK: Layerwise Zero-Knowledge Proofs for Verifiable Large Language Model Inference
by: Wang, Zhaohui Geoffrey
Published: (2026)
by: Wang, Zhaohui Geoffrey
Published: (2026)
Open-Weight LLM Fine-Tuning Defenses are Susceptible to Simple Attacks
by: Kuo, Kevin, et al.
Published: (2026)
by: Kuo, Kevin, et al.
Published: (2026)
On the Consistency of GNN Explanations for Malware Detection
by: Shokouhinejad, Hossein, et al.
Published: (2025)
by: Shokouhinejad, Hossein, et al.
Published: (2025)
Extending XReason: Formal Explanations for Adversarial Detection
by: Jemaa, Amira, et al.
Published: (2024)
by: Jemaa, Amira, et al.
Published: (2024)
Explanation as a Watermark: Towards Harmless and Multi-bit Model Ownership Verification via Watermarking Feature Attribution
by: Shao, Shuo, et al.
Published: (2024)
by: Shao, Shuo, et al.
Published: (2024)
FedPoP: Federated Learning Meets Proof of Participation
by: İşler, Devriş, et al.
Published: (2025)
by: İşler, Devriş, et al.
Published: (2025)
RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
by: Cheng, Zelei, et al.
Published: (2024)
by: Cheng, Zelei, et al.
Published: (2024)
ZKLoRA: Efficient Zero-Knowledge Proofs for LoRA Verification
by: Roy, Bidhan, et al.
Published: (2025)
by: Roy, Bidhan, et al.
Published: (2025)
ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs
by: Maheri, Mohammad M, et al.
Published: (2025)
by: Maheri, Mohammad M, et al.
Published: (2025)
A Survey of Zero-Knowledge Proof Based Verifiable Machine Learning
by: Peng, Zhizhi, et al.
Published: (2025)
by: Peng, Zhizhi, et al.
Published: (2025)
BACSA: A Bias-Aware Client Selection Algorithm for Privacy-Preserving Federated Learning in Wireless Healthcare Networks
by: Yadav, Sushilkumar, et al.
Published: (2024)
by: Yadav, Sushilkumar, et al.
Published: (2024)
zkFL: Zero-Knowledge Proof-based Gradient Aggregation for Federated Learning
by: Wang, Zhipeng, et al.
Published: (2023)
by: Wang, Zhipeng, et al.
Published: (2023)
Towards Trustworthy AI: Secure Deepfake Detection using CNNs and Zero-Knowledge Proofs
by: Islam, H M Mohaimanul, et al.
Published: (2025)
by: Islam, H M Mohaimanul, et al.
Published: (2025)
A Multi-Dimensional Quality Scoring Framework for Decentralized LLM Inference with Proof of Quality
by: Tian, Arther, et al.
Published: (2026)
by: Tian, Arther, et al.
Published: (2026)
WASP: Benchmarking Web Agent Security Against Prompt Injection Attacks
by: Evtimov, Ivan, et al.
Published: (2025)
by: Evtimov, Ivan, et al.
Published: (2025)
Machine Learning with Privacy for Protected Attributes
by: Mahloujifar, Saeed, et al.
Published: (2025)
by: Mahloujifar, Saeed, et al.
Published: (2025)
Privacy Amplification for the Gaussian Mechanism via Bounded Support
by: Hu, Shengyuan, et al.
Published: (2024)
by: Hu, Shengyuan, et al.
Published: (2024)
Privacy-Preserving Retrieval-Augmented Generation with Differential Privacy
by: Koga, Tatsuki, et al.
Published: (2024)
by: Koga, Tatsuki, et al.
Published: (2024)
A Survey of Privacy-Preserving Model Explanations: Privacy Risks, Attacks, and Countermeasures
by: Nguyen, Thanh Tam, et al.
Published: (2024)
by: Nguyen, Thanh Tam, et al.
Published: (2024)
Agentic Misalignment: How LLMs Could Be Insider Threats
by: Lynch, Aengus, et al.
Published: (2025)
by: Lynch, Aengus, et al.
Published: (2025)
Aggressive Compression Enables LLM Weight Theft
by: Brown, Davis, et al.
Published: (2026)
by: Brown, Davis, et al.
Published: (2026)
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual Explanations
by: Ezzeddine, Fatima, et al.
Published: (2024)
by: Ezzeddine, Fatima, et al.
Published: (2024)
Learning Privacy-Preserving Student Networks via Discriminative-Generative Distillation
by: Ge, Shiming, et al.
Published: (2024)
by: Ge, Shiming, et al.
Published: (2024)
SecAlign: Defending Against Prompt Injection with Preference Optimization
by: Chen, Sizhe, et al.
Published: (2024)
by: Chen, Sizhe, et al.
Published: (2024)
Confidential Federated Computations
by: Eichner, Hubert, et al.
Published: (2024)
by: Eichner, Hubert, et al.
Published: (2024)
On Differentially Private U Statistics
by: Chaudhuri, Kamalika, et al.
Published: (2024)
by: Chaudhuri, Kamalika, et al.
Published: (2024)
Model-based Large Language Model Customization as Service
by: Wu, Zhaomin, et al.
Published: (2024)
by: Wu, Zhaomin, et al.
Published: (2024)
A Survey on Model Extraction Attacks and Defenses for Large Language Models
by: Zhao, Kaixiang, et al.
Published: (2025)
by: Zhao, Kaixiang, et al.
Published: (2025)
Similar Items
-
FairProof : Confidential and Certifiable Fairness for Neural Networks
by: Yadav, Chhavi, et al.
Published: (2024) -
Can We Infer Confidential Properties of Training Data from LLMs?
by: Huang, Pengrun, et al.
Published: (2025) -
Optimistic Verifiable Training by Controlling Hardware Nondeterminism
by: Srivastava, Megha, et al.
Published: (2024) -
DPrivBench: Benchmarking LLMs' Reasoning for Differential Privacy
by: Wang, Erchi, et al.
Published: (2026) -
Influence-based Attributions can be Manipulated
by: Yadav, Chhavi, et al.
Published: (2024)