Secure Data Vault: Protecting Sensitive Information with SQL Security Features

This challenge focuses on implementing robust security measures within a SQL database to protect sensitive data. You'll be tasked with designing and implementing SQL queries and security features like row-level security (RLS), column-level encryption, and dynamic data masking to ensure data confidentiality and integrity. This is crucial for compliance with regulations like GDPR and HIPAA and for safeguarding sensitive business information.

Problem Description

You are responsible for securing a database containing customer financial information for a fictional online banking platform, "SecureBank." The database includes tables for Customers, Accounts, and Transactions. The Customers table contains Personally Identifiable Information (PII) like names, addresses, and social security numbers (SSN). The Accounts table stores account details, including balances. The Transactions table records all financial transactions.

Your task is to implement the following security features using SQL:

Row-Level Security (RLS): Implement RLS to restrict access to transaction data based on the customer's role. "Bank Managers" should have access to all transactions, while "Customer Service Representatives" should only see transactions for customers assigned to them. Assume a CSR_ID column exists in the Transactions table linking each transaction to a CSR.
Column-Level Encryption: Encrypt the SSN column in the Customers table using a suitable encryption method supported by your SQL database system. The encryption should be transparent to authorized users (Bank Managers) who need to decrypt it for specific operations.
Dynamic Data Masking: Mask the Account Balance column in the Accounts table for users who are not Bank Managers. Masking should replace the actual balance with a partially visible value (e.g., "XXX,XXX.XX") while still allowing users to see that there is a balance.

Expected Behavior:

Bank Managers should be able to view all data without restrictions.
Customer Service Representatives should only see transaction data for their assigned customers.
All users (except Bank Managers) should see encrypted SSNs and masked account balances.
The encryption and masking should be implemented in a way that minimizes performance impact.

Edge Cases to Consider:

What happens if a CSR is assigned to multiple customers?
How do you handle decryption of the SSN when a Bank Manager needs to access it?
How do you ensure that the masking is consistent across different queries and views?
What happens if a user's role changes? How do you ensure the security policies are updated accordingly?

Examples

Example 1:

Input:  A CSR with ID 'CSR002' attempts to query the Transactions table.
Output: The CSR only sees transactions associated with customers for whom CSR002 is responsible. Other transactions are filtered out.
Explanation: RLS filters the transactions based on the CSR's ID.

Example 2:

Input: A regular user (not a Bank Manager) queries the Customers table.
Output: The SSN column is displayed as encrypted data (e.g., "ENC(SSN)").
Explanation: Column-level encryption hides the actual SSN.

Example 3:

Input: A regular user queries the Accounts table.
Output: The Account Balance column is displayed as a masked value (e.g., "XXX,XXX.XX").
Explanation: Dynamic data masking hides the full account balance.

Constraints

Database System: Assume a standard SQL database system (e.g., PostgreSQL, MySQL, SQL Server, Oracle). Specify the system you are using in your solution.
Encryption Algorithm: Choose a suitable encryption algorithm supported by your chosen database system. Document your choice.
Masking Format: The masking format for account balances should be consistent (e.g., always show the last two digits).
Performance: The implemented security features should not significantly degrade query performance. Consider indexing and other optimization techniques.
Data Volume: Assume a large dataset (millions of records) for all tables.

Notes

This challenge focuses on the implementation of security features, not the design of the database schema itself. You can assume the tables already exist with the specified columns.
You are expected to provide SQL code snippets demonstrating the implementation of RLS, column-level encryption, and dynamic data masking.
Consider using database-specific functions and features for encryption and masking.
Clearly document your assumptions and choices regarding encryption algorithms, masking formats, and database-specific syntax.
Pseudocode is acceptable for outlining the overall approach, but SQL code is required for the actual implementation. Focus on the SQL statements needed to achieve the security goals.
Think about how to manage roles and permissions within your database system to control access to the security features themselves.