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As a Machine Learning Engineer at a leading financial institution, you are tasked with designing a secure and efficient biometric authentication system for the mobile banking app. The system must authenticate users via fingerprints while ensuring that sensitive biometric data is not stored in the bank's databases to comply with strict privacy regulations. Additionally, the solution must be scalable to accommodate millions of users worldwide and cost-effective to implement. Given these constraints, which machine learning strategy would you recommend for training and deploying this model effectively? Please choose the best option.
A
Implementing MD5 hashing to encrypt the biometric data before storage.
B
Utilizing Federated Learning to train the model across users' devices without centralizing the data.
C
Applying Differential Privacy techniques to anonymize the biometric data before processing.
D
Deploying a Data Loss Prevention API to monitor and protect the biometric data in transit.