A software-defined wrapper discriminant federated learning-reinforcement attention adversarial regression approach for privacy and task management in cloud edge computing

Key Points

• Privacy is enhanced through a federated learning model, reducing risks associated with centralized data storage.
• The approach utilizes adversarial regression techniques to optimize performance across diverse tasks, emphasizing privacy.
• Assessment of the federated learning framework showcases improved task management while preserving user data confidentiality.
• This model highlights the relevance of software-defined solutions to enhance privacy and performance in cloud edge environments.