
Lancelot, the secure federated learning system
A team of researchers in Hong Kong has released a system called Lancelot, which represents the first practical implementation of federated learning while also being protected from data tampering attacks and confidentiality breaches. Federated learning allows multiple participants (clients) to jointly train a model without revealing the source data. This approach is particularly important in medicine and finance, where personal information is strictly regulated. However, these systems are vulnerable to data poisoning : an attacker can upload fake updates and distort the results . Federated learning methods have partially solved this problem by discarding suspicious updates, but they have not protected against










