Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

In regulated industries, organizations are dealing with more sensitive data than ever before. This includes consumer IDs, financial and health-related data, and even behavioral insights. However, when this sensitive data finds its way into test, analytic, or development environments, it poses a direct compliance and security threat. This is where data masking comes in. It enables the use of realistic data by removing or modifying personal identifiers.

When you work in cybersecurity, whether you're steering the operational team, or in a more strategic role, the mission is the same: protect the business. But when it comes to executing that mission, finding consensus on the best approach can be hard. At this pivotal point in the evolution of cybersecurity, as automation becomes table stakes and AI adoption accelerates, it is important that stakeholders are pulling in the same direction. However, recent ThreatQuotient research highlights real differences in how CISOs and Heads of IR approach the introduction of AI into cybersecurity strategy and practice.