How does federated learning enhance privacy in cybersecurity by enabling collaboration without sharing sensitive data?
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How does federated learning enhance privacy in cybersecurity by enabling collaboration without sharing sensitive data?
Federated learning enhances privacy in cybersecurity by allowing multiple parties to collaborate on a machine learning model without sharing the underlying sensitive data. This is achieved by training the model locally on each participant’s device using their own data, and then only sharing encrypted updates or aggregated model parameters instead of raw data. This way, individual data stays on users’ devices and is not exposed during the model training process, thus reducing the risk of privacy breaches.