Blockchain Secured Federated Learning

Definition ∞ Blockchain secured federated learning is an approach that combines decentralized machine learning with blockchain technology to enhance data privacy and model integrity. This method allows multiple participants to collaboratively train a shared machine learning model without centralizing their raw data. The blockchain component records and verifies the model updates, providing an immutable and auditable trail of the training process. This structure helps ensure data confidentiality and guard against malicious alterations to the learning model.
Context ∞ The intersection of artificial intelligence and blockchain technology, particularly in federated learning, is a rapidly growing area of interest for data privacy and security. This approach is gaining traction in sectors requiring sensitive data handling, such as healthcare and finance. Future advancements will likely focus on improving the scalability and efficiency of these combined systems while maintaining strong cryptographic assurances.