A Multi-Criteria Intelligence AID Methodology and IoT Based Data Protection Using Machine Learning

IoT-powered devices have become one of the key companions of humans in recent times. Almost every sector of the modern market is heavily reliant on IoT-powered devices such as smartphones, computers and other smart gadgets. This has resulted in the massive availability of digital data containing the personal information of the users. This has caused a massive issue regarding data privacy on IoT-powered devices in recent times. This has resulted in the application of ML-based technologies for fostering better data protection. The concerned study has focused on the role of the different ML-powered technologies such as federated learning and differential learning models. Thai entre study has also focused on numerical analysis of the issues associated with the mentioned models during data protection. It has also provided survey data regarding different FL-based algorithms such as LM, NN, NM, DT and CM. This study has analyzed the issues and strengths of ML-based data protection on local and global data sets.