Data Security
===================================


✍️ **1. Data Encyption**

The process of encoding data to protect it from unauthorized access, both when stored on disk (at-rest) and when transmitted across networks (in-transit).

✍️ **2. Data Masking**

The technique of obscuring sensitive data by replacing it with fictitious or scrambled data, ensuring that sensitive information is not exposed to unauthorized users.

✍️ **3. Data Access Control**

A method of substituting sensitive data with non-sensitive tokens, allowing the original data to be protected while still enabling some operations to be performed.

✍️ **4. Data Auditing**

The practice of monitoring, recording, and analyzing data-related activities and events, enabling the detection of unauthorized access, data breaches, or compliance violations.

✍️ **5. Data Anonymization**

The process of removing personally identifiable information (PIl) from datasets to protect individual privacy while preserving the utility of the data for analysis.

✍️ **6. Data Pseudonymization**

A technique that replaces sensitive data with pseudonyms or artificial identifiers, reducing the risk of re-identification while maintaining some level of data usability.

✍️ **7. Security Monitoring**

The practice of continuously monitoring and analyzing data systems, networks, and activities for potential security threats, vulnerabilities, or breaches.

✍️ **8. Activity Monitoring**

The continuous monitoring and analysis of database activities and transactions to detect and prevent unauthorized access, data leaks, or policy violations.

✍️ **9. Data Loss Prevention**

A set of tools and practices designed to protect sensitive data from unauthorized access, leakage, or theft, by monitoring, detecting, and blocking potential data breaches.