Toward Privacy Preserving Federated Learning In Internet of Vehicular Things: Challenges and Future Directions

Keyphrases

• World Wide Web 100%
• Privacy-preserving Machine Learning 100%
• Federated Learning 66%
• Privacy Concerns 33%
• Security Privacy 33%
• Graph Convolutional Network 33%
• Information Exchange 16%
• Learning Approaches 16%
• Computational Power 16%
• Hopefulness 16%
• Intelligent Transportation Systems 16%
• Privacy-preserving 16%
• Spatial-temporal Data 16%
• Decentralized Solution 16%
• Security Concerns 16%
• Traffic Flow Forecasting 16%
• Academic Domain 16%
• Industrial Domain 16%
• Differential Privacy 16%
• Vehicular Data 16%
• Vehicular Applications 16%
• Distributed Learning 16%
• Performance Tradeoff 16%
• Autonomous Driving System 16%

Computer Science

• Future Direction 100%
• Privacy Preserving 100%
• Federated machine learning 100%
• Privacy Concern 40%
• Recurrent Network 40%
• Federated Graph 40%
• Security and Privacy 20%
• Temporal Information 20%
• Learning Approach 20%
• Security Concern 20%
• Intelligent Transportation System 20%
• Differential Privacy 20%
• Academic Domain 20%
• Autonomous Driving 20%
• Distributed Learning 20%
• Vehicular Application 20%