What methods are used to identify data exfiltration?

Common techniques used to identify data exfiltration and track stolen information in cyber incidents include:

1. Network monitoring: Monitoring network traffic for unusual patterns or data transfers to unfamiliar locations.
2. Endpoint detection and response (EDR): Using EDR tools to monitor and analyze activities on endpoints, identify unusual behavior, and detect data exfiltration attempts.
3. Data loss prevention (DLP): Implementing DLP solutions to prevent unauthorized transfer of sensitive data and track data movement.
4. Behavioral analytics: Utilizing machine learning and behavioral analysis to detect anomalies in user behavior and identify potential data exfiltration.
5. Forensic analysis: Conducting forensic investigations to trace the source of the breach, determine the extent of data exfiltration, and identify the stolen information.
6. Encryption: Encrypting sensitive data to protect it from being accessed in case of unauthorized access or data theft.
7. User and entity behavior analytics (UEBA): Monitoring user activities and analyzing behavior to identify suspicious actions that may indicate data exfiltration.
8. SIEM (Security Information and Event Management): Using SIEM tools to aggregate and analyze security event data to detect and respond to data exfiltration incidents effectively.

These techniques help organizations in identifying and tracking data exfiltration and stolen information to mitigate the impact of cyber incidents.