Modern business relies on data, which is a key resource for every organization. Technological advances mean that information is no longer stored exclusively in offices or server rooms, but flows freely between clouds, applications, and the devices of employees working from any location. Such mobility, while very beneficial, poses significant risks to traditional security models. The question arises: how can data be effectively controlled and protected when it is everywhere and constantly on the move?

From perimeter to zero trust model

Previous security solutions focused on protecting the company’s network boundaries. However, this approach is now becoming insufficient. The answer is the Secure Access Service Edge (SASE) concept, which provides data-oriented protection regardless of where the data is processed or stored. This platform includes Security Service Edge (SSE) and Zero Trust Data Security, with the main focus on securing information rather than the infrastructure itself.

The key assumption of the modern approach is the Zero Trust model, according to which no user or device can be trusted by default. Instead of putting up virtual “walls” around the organization, a consistent set of rules and control mechanisms is used to protect data in any environment without overburdening employees and administrators.

Multi-layered prevention – the DLP accuracy pyramid

Effective data protection requires a variety of techniques with varying levels of detail. Forcepoint illustrates this with the concept of the “Accuracy Pyramid” in Data Loss Prevention (DLP) systems, in which successive layers correspond to increasingly precise security methods:

  • Keywords and phrases – detecting data based on simple lists of terms.
  • File type recognition – identification of materials by format, e.g., Office documents or CAD files.
  • Data classifiers – recognition of sensitive information (e.g., social security numbers, credit card numbers) regardless of file format.
  • Machine learning – analysis of user behavior to detect unusual cases of data disclosure.
  • Fingerprinting – creating a digital fingerprint of a document, which allows even fragments copied to other files to be recognized.
  • PreciseID – the most accurate method based on a unique file hash, detecting even modified copies or screenshots.

Incident analysis and intelligent protection

Modern DLP tools are not limited to blocking threats. They also provide detailed incident analysis, identifying the source, data flow channel, and potential recipient. This makes it possible to apply remediation mechanisms such as encryption or pseudonymization, as well as to refer the matter to the appropriate persons, e.g., the Data Protection Officer (DPO).

One of the most innovative approaches is Risk-Adaptive Protection. The system tracks employee behavior and assigns them a risk level in real time. Security policies are then dynamically adjusted—low-risk activities are only monitored, while high-risk users may have the same activities immediately blocked and reported to the administrator.

Effective data protection in today’s distributed ecosystem requires a shift away from static and network-centric methods. These are being replaced by intelligent systems that focus on data and the context in which it is used. This approach not only minimizes the risk of leaks, but also supports the flexibility and efficiency of an organization’s work.

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