Server-Enabled Information Transmission Through Networks Using Federated Learning Approach

The research paper deals with the usage of federated learning in keeping sensitive and vulnerable information safely through differential privacy. It can be widely used in banking institutions and tertiary care facility which are more susceptible of cyberattacks. It highlights the benefits of integration of electronics with computer science for getting optimal output. By leveraging the strength of devices which are connected together such as modem, router, switches, etc., the following method emphasizes the advantages of end-to-end encryption within an institution. The research paper overall provides appreciable insights into the capable applications and advantages to make us more safe digitally. The execution of result evaluation of proposed model displays the best performance with accuracy rate of 93.7% and a mean access time of 7.87 s. This can be helpful in the growth of creative approach to guarantee the privacy as well as integrity of person`s data and promotion of confidence and trust in digital workspace.