A company has deployed an automated analytics platform across operations for tasks such as voice recognition. Which approach best addresses the risk that malicious users will degrade this platform’s outputs by altering the data used for training future models?
Restrict system logs to privileged accounts
Validate the training set and look for any suspicious inputs before use
Use one encryption process for every data set so training is uniform
Turn off monitoring capabilities when the platform updates its models
Ensuring that training data is thoroughly validated and monitored for suspicious inputs is a strong defense against tampering. Logging controls or universal encryption processes do not directly address the risk of manipulated data that could undermine the platform’s predictive outputs, while deactivating monitoring further exposes the system to unauthorized modifications.
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