A survey on federated unlearning: Challenges, methods, and future directions
In recent years, the notion of “the right to be forgotten”(RTBF) has become a crucial aspect of
data privacy for digital trust and AI safety, requiring the provision of mechanisms that support …
data privacy for digital trust and AI safety, requiring the provision of mechanisms that support …
Efficient verifiable protocol for privacy-preserving aggregation in federated learning
Federated learning has gained extensive interest in recent years owing to its ability to
update model parameters without obtaining raw data from users, which makes it a viable …
update model parameters without obtaining raw data from users, which makes it a viable …
Long-term privacy-preserving aggregation with user-dynamics for federated learning
Privacy-preserving aggregation protocol is an essential building block in privacy-enhanced
federated learning (FL), which enables the server to obtain the sum of users' locally trained …
federated learning (FL), which enables the server to obtain the sum of users' locally trained …