Enhancing Accuracy-Privacy Trade-off in Differentially Private Split Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Pham, Ngoc Duy, Phan, Khoa Tran, Chilamkurti, Naveen |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Split Learning without Local Weight Sharing to Enhance Client-side Data Privacy
by: Pham, Ngoc Duy, et al.
Published: (2022)
by: Pham, Ngoc Duy, et al.
Published: (2022)
A Novel Endorsement Protocol to Secure BFT-Based Consensus in Permissionless Blockchain
by: Xu, Ziqiang, et al.
Published: (2024)
by: Xu, Ziqiang, et al.
Published: (2024)
PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoT
by: Duy, Phan The, et al.
Published: (2026)
by: Duy, Phan The, et al.
Published: (2026)
PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy
by: Duy, Phan The, et al.
Published: (2026)
by: Duy, Phan The, et al.
Published: (2026)
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)
Enhancing Gradient Variance and Differential Privacy in Quantum Federated Learning
by: Phan, Duc-Thien, et al.
Published: (2025)
by: Phan, Duc-Thien, et al.
Published: (2025)
Advances in Differential Privacy and Differentially Private Machine Learning
by: Das, Saswat, et al.
Published: (2024)
by: Das, Saswat, et al.
Published: (2024)
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off
by: Li, Yuecheng, et al.
Published: (2024)
by: Li, Yuecheng, et al.
Published: (2024)
Federated Learning in Genetics: Extended Analysis of Accuracy, Performance and Privacy Trade-offs
by: Hannemann, Anika, et al.
Published: (2024)
by: Hannemann, Anika, et al.
Published: (2024)
Red-MIRROR: Agentic LLM-based Autonomous Penetration Testing with Reflective Verification and Knowledge-augmented Interaction
by: Khang, Tran Vy, et al.
Published: (2026)
by: Khang, Tran Vy, et al.
Published: (2026)
A Pervasive, Efficient and Private Future: Realizing Privacy-Preserving Machine Learning Through Hybrid Homomorphic Encryption
by: Nguyen, Khoa, et al.
Published: (2024)
by: Nguyen, Khoa, et al.
Published: (2024)
Accuracy-Privacy Trade-off in the Mitigation of Membership Inference Attack in Federated Learning
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
by: Ahamed, Sayyed Farid, et al.
Published: (2024)
Improving Parameter-Efficient Federated Learning with Differentially Private Refactorization
by: Tran, Linh, et al.
Published: (2026)
by: Tran, Linh, et al.
Published: (2026)
The Privacy-Utility Trade-off in the Topics API
by: Alvim, Mário S., et al.
Published: (2024)
by: Alvim, Mário S., et al.
Published: (2024)
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
FairDP: Certified Fairness with Differential Privacy
by: Tran, Khang, et al.
Published: (2023)
by: Tran, Khang, et al.
Published: (2023)
Accuracy-First Rényi Differential Privacy and Post-Processing Immunity
by: Räisä, Ossi, et al.
Published: (2025)
by: Räisä, Ossi, et al.
Published: (2025)
Private Linear Regression with Differential Privacy and PAC Privacy
by: Yang, Hillary, et al.
Published: (2024)
by: Yang, Hillary, et al.
Published: (2024)
Mitigating Privacy-Utility Trade-off in Decentralized Federated Learning via $f$-Differential Privacy
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Differentially Private Relational Learning with Entity-level Privacy Guarantees
by: Huang, Yinan, et al.
Published: (2025)
by: Huang, Yinan, et al.
Published: (2025)
Calibrating Practical Privacy Risks for Differentially Private Machine Learning
by: Gu, Yuechun, et al.
Published: (2024)
by: Gu, Yuechun, et al.
Published: (2024)
E-FreeM2: Efficient Training-Free Multi-Scale and Cross-Modal News Verification via MLLMs
by: Phan, Van-Hoang, et al.
Published: (2025)
by: Phan, Van-Hoang, et al.
Published: (2025)
Beyond Privacy Trade-offs with Structured Transparency
by: Trask, Andrew, et al.
Published: (2020)
by: Trask, Andrew, et al.
Published: (2020)
Balancing Security and Accuracy: A Novel Federated Learning Approach for Cyberattack Detection in Blockchain Networks
by: Khoa, Tran Viet, et al.
Published: (2024)
by: Khoa, Tran Viet, et al.
Published: (2024)
Revisiting Privacy-Utility Trade-off for DP Training with Pre-existing Knowledge
by: Zheng, Yu, et al.
Published: (2024)
by: Zheng, Yu, et al.
Published: (2024)
DMLDroid: Deep Multimodal Fusion Framework for Android Malware Detection with Resilience to Code Obfuscation and Adversarial Perturbations
by: Trung, Doan Minh, et al.
Published: (2025)
by: Trung, Doan Minh, et al.
Published: (2025)
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
by: Tang, Xinyu, et al.
Published: (2023)
by: Tang, Xinyu, et al.
Published: (2023)
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy
by: Schwethelm, Kristian, et al.
Published: (2024)
by: Schwethelm, Kristian, et al.
Published: (2024)
$f$-Differential Privacy Filters: Validity and Approximate Solutions
by: Tran, Long, et al.
Published: (2026)
by: Tran, Long, et al.
Published: (2026)
Synthetic Data: Revisiting the Privacy-Utility Trade-off
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
by: Sarmin, Fatima Jahan, et al.
Published: (2024)
NOIR: Privacy-Preserving Generation of Code with Open-Source LLMs
by: Nguyen, Khoa, et al.
Published: (2026)
by: Nguyen, Khoa, et al.
Published: (2026)
Privacy Leakage via Output Label Space and Differentially Private Continual Learning
by: Tobaben, Marlon, et al.
Published: (2024)
by: Tobaben, Marlon, et al.
Published: (2024)
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence
by: Feng, Shuya, et al.
Published: (2024)
by: Feng, Shuya, et al.
Published: (2024)
AQUA-LLM: Evaluating Accuracy, Quantization, and Adversarial Robustness Trade-offs in LLMs for Cybersecurity Question Answering
by: Gungor, Onat, et al.
Published: (2025)
by: Gungor, Onat, et al.
Published: (2025)
CURE: Privacy-Preserving Split Learning Done Right
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
by: Kanpak, Halil Ibrahim, et al.
Published: (2024)
Private Sum Computation: Trade-Offs between Communication, Randomness, and Privacy
by: Chou, Remi A., et al.
Published: (2026)
by: Chou, Remi A., et al.
Published: (2026)
xOffense: An Autonomous Multi-Agent Framework for Penetration Testing with Domain-Adapted Large Language Models
by: Luong, Phung Duc, et al.
Published: (2025)
by: Luong, Phung Duc, et al.
Published: (2025)
Differentially Private Spectral Graph Clustering: Balancing Privacy, Accuracy, and Efficiency
by: Koskela, Antti, et al.
Published: (2025)
by: Koskela, Antti, et al.
Published: (2025)
Flatness-aware Sequential Learning Generates Resilient Backdoors
by: Pham, Hoang, et al.
Published: (2024)
by: Pham, Hoang, et al.
Published: (2024)
When FinTech Meets Privacy: Securing Financial LLMs with Differential Private Fine-Tuning
by: Zhu, Sichen, et al.
Published: (2025)
by: Zhu, Sichen, et al.
Published: (2025)
Similar Items
-
Split Learning without Local Weight Sharing to Enhance Client-side Data Privacy
by: Pham, Ngoc Duy, et al.
Published: (2022) -
A Novel Endorsement Protocol to Secure BFT-Based Consensus in Permissionless Blockchain
by: Xu, Ziqiang, et al.
Published: (2024) -
PenTiDef: Decentralized Federated Intrusion Detection System with Differential Privacy and Latent-Space Defense via Blockchain Coordination in IIoT
by: Duy, Phan The, et al.
Published: (2026) -
PoC-Adapt: Semantic-Aware Automated Vulnerability Reproduction with LLM Multi-Agents and Reinforcement Learning-Driven Adaptive Policy
by: Duy, Phan The, et al.
Published: (2026) -
Revisiting Locally Differentially Private Protocols: Towards Better Trade-offs in Privacy, Utility, and Attack Resistance
by: Arcolezi, Héber H., et al.
Published: (2025)