What types of sensitive data do DLP solutions aim to protect, including personally identifiable information (PII), financial data, intellectual property, and health records?

How do regular expressions (regex) play a role in DLP, providing a method for identifying patterns in text, such as credit card numbers or social security numbers, to prevent data leakage?

Can you provide an example of a regex pattern used to detect Social Security Numbers (SSNs), ensuring that SSNs are identified and protected from unauthorized access or sharing?

What are the legal implications of implementing DLP, particularly regarding privacy rights, regulatory compliance, and the potential legal consequences of mishandling sensitive data?

How does DLP support incident response by helping identify and block data breaches in real time, and providing insights for investigation and remediation after an incident?

What are the key differences between DLP and Digital Rights Management (DRM), where DLP focuses on preventing data loss and DRM controls how data is used or shared?

What key considerations should be made when selecting a DLP vendor, such as the vendor’s experience, compatibility with existing infrastructure, and ability to scale with the organization’s needs?

How does DLP integrate with SIEM systems, enhancing threat detection and response by providing real-time data monitoring, alerts, and analysis of sensitive data movements and violations?

What are the common metrics used to measure the effectiveness of a DLP system, such as the number of blocked incidents, false positives, compliance adherence, and user awareness levels?

How does DLP manage data in SaaS applications, ensuring that sensitive data shared through cloud platforms is protected and preventing leaks across cloud-based environments?