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(TLS) or Secure Socket Layer (SSL) are used to protect data as it is transmitted between the user and the database. This ensures that any data exchanged, such as login credentials or credit card numbers, is encrypted while it is in transit. When encrypting sensitive data, it is crucial to securely manage the encryption keys, as their exposure would compromise the security of the encrypted data. Key management systems (KMS) are used to securely store and rotate encryption keys. 2. Data Masking and Tokenization While encryption is effective at protecting data, it can be cumbersome to work with in certain scenarios, especially in development or testing environments.
Data masking and tokenization are alternative methods to reduce the risk of exposure. Data Masking: This technique involves altering sensitive data in such a way that it remains usable for testing and analysis purposes but cannot be reverse-engineered taiwan phone number database to reveal the original information. For example, credit card numbers might be replaced with "XXXX-XXXX-XXXX-1234" to maintain the format but conceal the full number. Tokenization: Tokenization involves replacing sensitive data with a unique, random string (a "token") that has no exploitable value. The real data is stored in a secure, centralized location, and the tokens are used in place of the real data.

This way, even if a database is compromised, attackers only gain access to the meaningless tokens instead of the actual sensitive data. These techniques help minimize the exposure of sensitive data while still allowing businesses to perform necessary operations. 3. Access Control and Role-Based Authentication One of the key principles of data security is limiting access to sensitive data based on the role and need-to-know basis. Database access should be restricted so that only authorized personnel or applications can retrieve or modify sensitive data. Role-Based Access Control (RBAC): RBAC involves assigning specific roles to users and applications within the organization.
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