Security Analysis of SplitFed Learning. (arXiv:2212.01716v1 [cs.LG])

Split Learning (SL) and Federated Learning (FL) are two prominent distributed
collaborative learning techniques that maintain data privacy by allowing
clients to never share their private data with other clients and servers, and
fined extensive IoT applications in smart healthcare, smart cities, and smart
industry. Prior work has extensively explored the security vulnerabilities of
FL in the form of poisoning attacks. To mitigate the effect of these attacks,
several defenses have also been proposed. Recently, a hybrid of both learning …

analysis security security analysis