Privacy-Preserving Verifiable Neural Network Inference Service
Fuente:
arXiv
Saved in:
| Main Authors: | Riasi, Arman, Guajardo, Jorge, Hoang, Thang |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
by: Behnia, Rouzbeh, et al.
Published: (2023)
by: Behnia, Rouzbeh, et al.
Published: (2023)
Local Differential Privacy for Federated Learning with Fixed Memory Usage and Per-Client Privacy
by: Behnia, Rouzbeh, et al.
Published: (2025)
by: Behnia, Rouzbeh, et al.
Published: (2025)
Privacy-Preserving Mechanisms Enable Cheap Verifiable Inference of LLMs
by: Pal, Arka, et al.
Published: (2026)
by: Pal, Arka, et al.
Published: (2026)
Efficient and Verifiable Privacy-Preserving Convolutional Computation for CNN Inference with Untrusted Clouds
by: Lu, Jinyu, et al.
Published: (2025)
by: Lu, Jinyu, et al.
Published: (2025)
Preserving Node-level Privacy in Graph Neural Networks
by: Xiang, Zihang, et al.
Published: (2023)
by: Xiang, Zihang, et al.
Published: (2023)
Privacy-Preserving 3-Layer Neural Network Training
by: Chiang, John
Published: (2023)
by: Chiang, John
Published: (2023)
On Polynomial Approximations for Privacy-Preserving and Verifiable ReLU Networks
by: Ali, Ramy E., et al.
Published: (2020)
by: Ali, Ramy E., et al.
Published: (2020)
Privacy-Preserving Hierarchical Model-Distributed Inference
by: Dehkordi, Fatemeh Jafarian, et al.
Published: (2024)
by: Dehkordi, Fatemeh Jafarian, et al.
Published: (2024)
Privacy-Preserving Inference for Quantized BERT Models
by: Lu, Tianpei, et al.
Published: (2025)
by: Lu, Tianpei, et al.
Published: (2025)
Panther: A Cost-Effective Privacy-Preserving Framework for GNN Training and Inference Services in Cloud Environments
by: Chen, Congcong, et al.
Published: (2025)
by: Chen, Congcong, et al.
Published: (2025)
A User-Centric, Privacy-Preserving, and Verifiable Ecosystem for Personal Data Management and Utilization
by: Zafar, Osama, et al.
Published: (2025)
by: Zafar, Osama, et al.
Published: (2025)
CENTAUR: Bridging the Impossible Trinity of Privacy, Efficiency, and Performance in Privacy-Preserving Transformer Inference
by: Luo, Jinglong, et al.
Published: (2024)
by: Luo, Jinglong, et al.
Published: (2024)
Efficient Privacy-Preserving KAN Inference Using Homomorphic Encryption
by: Lai, Zhizheng, et al.
Published: (2024)
by: Lai, Zhizheng, et al.
Published: (2024)
Degree-Preserving Randomized Response for Graph Neural Networks under Local Differential Privacy
by: Hidano, Seira, et al.
Published: (2022)
by: Hidano, Seira, et al.
Published: (2022)
Privacy-Preserved Neural Graph Databases
by: Hu, Qi, et al.
Published: (2023)
by: Hu, Qi, et al.
Published: (2023)
Privacy-Preserving Intrusion Detection using Convolutional Neural Networks
by: Kodys, Martin, et al.
Published: (2024)
by: Kodys, Martin, et al.
Published: (2024)
Towards Deep Encrypted Training: Low-Latency, Memory-Efficient, and High-Throughput Inference for Privacy-Preserving Neural Networks
by: Njungle, Nges Brian, et al.
Published: (2026)
by: Njungle, Nges Brian, et al.
Published: (2026)
Comparison of Fully Homomorphic Encryption and Garbled Circuit Techniques in Privacy-Preserving Machine Learning Inference
by: Cheerla, Kalyan, et al.
Published: (2025)
by: Cheerla, Kalyan, et al.
Published: (2025)
TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks
by: Maheri, Mohammad M, et al.
Published: (2025)
by: Maheri, Mohammad M, et al.
Published: (2025)
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
by: Frimpong, Eugene, et al.
Published: (2024)
by: Frimpong, Eugene, et al.
Published: (2024)
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
by: Noorbakhsh, Sayedeh Leila, et al.
Published: (2024)
by: Noorbakhsh, Sayedeh Leila, et al.
Published: (2024)
Privacy-Preserving Offloading for Large Language Models in 6G Vehicular Networks
by: Badidi, Ikhlasse, et al.
Published: (2025)
by: Badidi, Ikhlasse, et al.
Published: (2025)
Agentic Privacy-Preserving Machine Learning
by: Zhang, Mengyu, et al.
Published: (2025)
by: Zhang, Mengyu, et al.
Published: (2025)
Data Privacy Preservation on the Internet of Things
by: Sen, Jaydip, et al.
Published: (2023)
by: Sen, Jaydip, et al.
Published: (2023)
Preserving Privacy and Security in Federated Learning
by: Nguyen, Truc, et al.
Published: (2022)
by: Nguyen, Truc, et al.
Published: (2022)
SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud
by: Duan, Shijin, et al.
Published: (2024)
by: Duan, Shijin, et al.
Published: (2024)
Modeling Neural Networks with Privacy Using Neural Stochastic Differential Equations
by: Hong, Sanghyun, et al.
Published: (2025)
by: Hong, Sanghyun, et al.
Published: (2025)
Verifying LLM Inference to Detect Model Weight Exfiltration
by: Rinberg, Roy, et al.
Published: (2025)
by: Rinberg, Roy, et al.
Published: (2025)
Provable Privacy Attacks on Trained Shallow Neural Networks
by: Smorodinsky, Guy, et al.
Published: (2024)
by: Smorodinsky, Guy, et al.
Published: (2024)
Privacy Preserving Reinforcement Learning for Population Processes
by: Yang-Zhao, Samuel, et al.
Published: (2024)
by: Yang-Zhao, Samuel, et al.
Published: (2024)
Privacy-Preserving Vertical K-Means Clustering
by: Mazzone, Federico, et al.
Published: (2025)
by: Mazzone, Federico, et al.
Published: (2025)
Privacy-Preserving Fair Synthetic Tabular Data
by: Sarmin, Fatima J., et al.
Published: (2025)
by: Sarmin, Fatima J., et al.
Published: (2025)
Privacy Preservation through Practical Machine Unlearning
by: Dilworth, Robert
Published: (2025)
by: Dilworth, Robert
Published: (2025)
Federated Inference: Toward Privacy-Preserving Collaborative and Incentivized Model Serving
by: Seo, Jungwon, et al.
Published: (2026)
by: Seo, Jungwon, et al.
Published: (2026)
Tempo: Confidentiality Preservation in Cloud-Based Neural Network Training
by: Xu, Rongwu, et al.
Published: (2024)
by: Xu, Rongwu, et al.
Published: (2024)
A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Privacy-Preserving Optimal Parameter Selection for Collaborative Clustering
by: Ghasemian, Maryam, et al.
Published: (2024)
by: Ghasemian, Maryam, et al.
Published: (2024)
Automated Privacy-Preserving Techniques via Meta-Learning
by: Carvalho, Tânia, et al.
Published: (2024)
by: Carvalho, Tânia, et al.
Published: (2024)
Preserving Expert-Level Privacy in Offline Reinforcement Learning
by: Sharma, Navodita, et al.
Published: (2024)
by: Sharma, Navodita, et al.
Published: (2024)
opp/ai: Optimistic Privacy-Preserving AI on Blockchain
by: So, Cathie, et al.
Published: (2024)
by: So, Cathie, et al.
Published: (2024)
Similar Items
-
Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
by: Behnia, Rouzbeh, et al.
Published: (2023) -
Local Differential Privacy for Federated Learning with Fixed Memory Usage and Per-Client Privacy
by: Behnia, Rouzbeh, et al.
Published: (2025) -
Privacy-Preserving Mechanisms Enable Cheap Verifiable Inference of LLMs
by: Pal, Arka, et al.
Published: (2026) -
Efficient and Verifiable Privacy-Preserving Convolutional Computation for CNN Inference with Untrusted Clouds
by: Lu, Jinyu, et al.
Published: (2025) -
Preserving Node-level Privacy in Graph Neural Networks
by: Xiang, Zihang, et al.
Published: (2023)