Imagen de Portada

Privacy Preserving Machine Learning for Electric Vehicles: A Survey

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Sani, Abdul Rahman, Hassan, Muneeb Ul, Gao, Longxiang, Chen, Jinjun
Formato:	Preprint
Publicado:	2022
Materias:	Cryptography and Security
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Evaluating the Vulnerability Landscape of LLM-Generated Smart Contracts
por: Do, Hoang Long, et al.
Publicado: (2026)

Privacy-Preserving Machine Learning for IoT: A Cross-Paradigm Survey and Future Roadmap
por: Zaman, Zakia, et al.
Publicado: (2026)

QRïS: A Preemptive Novel Method for Quishing Detection Through Structural Features of QR
por: Akram, Muhammad Wahid, et al.
Publicado: (2025)

Deep Q-Learning Assisted Bandwidth Reservation for Multi-Operator Time-Sensitive Vehicular Networking
por: Al-Khatib, Abdullah, et al.
Publicado: (2025)

ALFA: A Safe-by-Design Approach to Mitigate Quishing Attacks Launched via Fancy QR Codes
por: Akram, Muhammad Wahid, et al.
Publicado: (2026)

Exemplifying Emerging Phishing: QR-based Browser-in-The-Browser (BiTB) Attack
por: Akram, Muhammad Wahid, et al.
Publicado: (2025)

Privacy Preserving Charge Location Prediction for Electric Vehicles
por: Marlin, Robert, et al.
Publicado: (2025)

State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey
por: Zhang, Chaoyu, et al.
Publicado: (2024)

Efficient Privacy-Preserving Machine Learning with Lightweight Trusted Hardware
por: Huang, Pengzhi, et al.
Publicado: (2022)

Enhancing Noisy Functional Encryption for Privacy-Preserving Machine Learning
por: Scheu-Hachtel, Linda, et al.
Publicado: (2025)

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning
por: Behnia, Rouzbeh, et al.
Publicado: (2023)

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

A Novel Review of Stability Techniques for Improved Privacy-Preserving Machine Learning
por: DuPlessie, Coleman, et al.
Publicado: (2024)

Agentic Privacy-Preserving Machine Learning
por: Zhang, Mengyu, et al.
Publicado: (2025)

A Survey on Privacy-Preserving Computing in the Automotive Domain
por: Yuca, Nergiz, et al.
Publicado: (2025)

The Communication-Friendly Privacy-Preserving Machine Learning against Malicious Adversaries
por: Lu, Tianpei, et al.
Publicado: (2024)

Blind Evaluation Framework for Fully Homomorphic Encryption and Privacy-Preserving Machine Learning
por: Lee, Hunjae "Timothy", et al.
Publicado: (2023)

Improving Privacy-Preserving Techniques for Smart Grid using Lattice-based Cryptography
por: Darzi, Saleh, et al.
Publicado: (2024)

Privacy-preserving Machine Learning in Internet of Vehicle Applications: Fundamentals, Recent Advances, and Future Direction
por: Islam, Nazmul, et al.
Publicado: (2025)

Privacy-Preserving State Estimation in the Presence of Eavesdroppers: A Survey
por: Yan, Xinhao, et al.
Publicado: (2024)

Bicoptor 2.0: Addressing Challenges in Probabilistic Truncation for Enhanced Privacy-Preserving Machine Learning
por: Zhou, Lijing, et al.
Publicado: (2023)

Privacy-Preserving Customer Churn Prediction Model in the Context of Telecommunication Industry
por: Sana, Joydeb Kumar, et al.
Publicado: (2024)

Efficient and Privacy-Preserving Federated Learning based on Full Homomorphic Encryption
por: Guo, Yuqi, et al.
Publicado: (2024)

A Comprehensive Survey on Edge Data Integrity Verification: Fundamentals and Future Trends
por: Zhao, Yao, et al.
Publicado: (2022)

Human-Centered Interactive Anonymization for Privacy-Preserving Machine Learning: A Case for Human-Guided k-Anonymity
por: Gajavalli, Sri Harsha
Publicado: (2025)

A Pervasive, Efficient and Private Future: Realizing Privacy-Preserving Machine Learning Through Hybrid Homomorphic Encryption
por: Nguyen, Khoa, et al.
Publicado: (2024)

Privacy-Preserving Generative Models: A Comprehensive Survey
por: Padariya, Debalina, et al.
Publicado: (2025)

Privacy-Preserving Screening for Record Linkage
por: Huang, Chenyu, et al.
Publicado: (2026)

Fusion of Machine Learning and Blockchain-based Privacy-Preserving Approach for Health Care Data in the Internet of Things
por: Bezanjani, Behnam Rezaei, et al.
Publicado: (2025)

Activate Me!: Designing Efficient Activation Functions for Privacy-Preserving Machine Learning with Fully Homomorphic Encryption
por: Njungle, Nges Brian, et al.
Publicado: (2025)

SFPDML: Securer and Faster Privacy-Preserving Distributed Machine Learning based on MKTFHE
por: Wang, Hongxiao, et al.
Publicado: (2022)

Privacy Preserving Machine Learning Workflow: from Anonymization to Personalized Differential Privacy Budgets in Federated Learning
por: Díaz, Judith Sáinz-Pardo, et al.
Publicado: (2026)

A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks
por: Liu, Hengzhu, et al.
Publicado: (2024)

Privacy-Preserving Data in IoT-based Cloud Systems: A Comprehensive Survey with AI Integration
por: Dhinakaran, D., et al.
Publicado: (2024)

Secure Sparse Matrix Multiplications and their Applications to Privacy-Preserving Machine Learning
por: Damie, Marc, et al.
Publicado: (2025)

CURE: Privacy-Preserving Split Learning Done Right
por: Kanpak, Halil Ibrahim, et al.
Publicado: (2024)

Privacy Preservation through Practical Machine Unlearning
por: Dilworth, Robert
Publicado: (2025)

Privacy-Preserving Fair Synthetic Tabular Data
por: Sarmin, Fatima J., et al.
Publicado: (2025)

Leveraging Functional Encryption and Deep Learning for Privacy-Preserving Traffic Forecasting
por: Adom, Isaac, et al.
Publicado: (2025)

Privacy Preservation and Identity Tracing Prevention in AI-Driven Eye Tracking for Interactive Learning Environments
por: Rehman, Abdul, et al.
Publicado: (2025)