The cybersecurity industry's approach to data protection has only ever resolved the depth of security problems. There are data loss prevention (DLP), information rights management (IRM), encryption and many solutions available that can only protect a few pieces of data well.
What companies, organizations and governments need is a security approach that enables a massive breadth of protection. It's critical to protect as much data as possible at all times. A breadth-of-security model has not been possible with legacy solutions because all depth-of-security features interfere with end-user workflows.
The cybersecurity industry's approach to data protection has only ever resolved the depth of security problems. There are data loss prevention (DLP), information rights management (IRM), encryption and many solutions available that can only protect a few pieces of data well.
A depth-of-security approach doesn't prevent any of the massive data breach examples mentioned previously.
What companies, organizations and governments need is a security approach that enables a massive breadth of protection. It's critical to protect as much data as possible at all times. A breadth-of-security model has not been possible with legacy solutions because all depth-of-security features interfere with end-user workflows.
As a result, companies and users protect as little data as possible — which is why many security professionals implement a “discover, classify and then protect” model. This paradigm doesn’t protect massive amounts of data against large beaches. It protects as little data as possible.