Which detection method helps avoid incidents involving employees' own personal information?

Which detection method helps avoid incidents involving employees' own personal information?

• A. Exact Data Matching
• B. Email pattern detection
• C. Contextual risk scoring
• D. Anonymization

Answer: (A)

Exact Data Matching focuses on identifying exact, predefined data values—like an employee’s own social security number or other personal identifiers—across data streams and storage. When those exact values appear in emails, chats, USB drives, or cloud uploads, the DLP system can block, quarantine, or alert. Because it uses precise matches, it can reliably detect and prevent incidents involving employees' own personal information, ensuring such sensitive values aren’t leaked or misused. In contrast, detecting by email patterns looks for formats or generic addresses rather than the actual data values, so it may miss the specific personal data. Contextual risk scoring weighs risk based on factors like user, location, or data type but doesn’t enforce blocking of a known sensitive value by itself. Anonymization masks data to reduce exposure but doesn’t identify or stop the transmission of the real personal data value.

Exact Data Matching focuses on identifying exact, predefined data values—like an employee’s own social security number or other personal identifiers—across data streams and storage. When those exact values appear in emails, chats, USB drives, or cloud uploads, the DLP system can block, quarantine, or alert. Because it uses precise matches, it can reliably detect and prevent incidents involving employees' own personal information, ensuring such sensitive values aren’t leaked or misused. In contrast, detecting by email patterns looks for formats or generic addresses rather than the actual data values, so it may miss the specific personal data. Contextual risk scoring weighs risk based on factors like user, location, or data type but doesn’t enforce blocking of a known sensitive value by itself. Anonymization masks data to reduce exposure but doesn’t identify or stop the transmission of the real personal data value.