In your role at a leading Banking group, you're tasked with enhancing the security of customer data processing. The project involves the automated collection and processing of large datasets from various documents, which contain highly sensitive information such as credit card numbers and personal identification details. Due to strict compliance requirements, this sensitive data must not be disclosed in any form. Your team is considering several techniques to ensure data confidentiality by substituting sensitive data with surrogate characters, while maintaining the data's usability for analysis. Which of the following techniques would be most appropriate for this scenario, considering the need for data utility and compliance with data protection regulations? (Choose two options if option E is available) | Google Professional Machine Learning Engineer Quiz