Secure Federated Learning for Intelligent Industry 4.0 IoT Enabled Self Skin Care Application System
Sachin Sharma, Shuchi Bhadula
Abstract
Secure Federated Learning is a cutting-edge technology for training machine learning models in a decentralized manner, while preserving the privacy of sensitive personal data. In the context of Intelligent Industry 4.0 IoT enabled self-skin care application systems, secure federated learning enables the aggregation of data from multiple devices, allowing for the development of more accurate and personalized skin care recommendations, while maintaining the security of personal health data. Despite the challenges associated with secure federated learning, such as data heterogeneity, network latency, and privacy protection, the future of this technology in self-skin care systems is promising, with potential for increased accuracy, wider adoption, and integration with other technologies.