Preventing Data Leaks - in eight Steps

More and more data is flowing between clouds, end devices and AI tools - traditional security concepts are reaching their limits. However, data loss prevention (DLP) can be implemented effectively with a clear strategy. Eight steps show how companies can reliably protect their information.

1. Define goals and use cases
   Determine whether the aim is to protect intellectual property, comply with regulatory requirements or safeguard hybrid working models. Create a risk profile based on this: Which data types, channels and consequences are relevant?

2. Draw up an implementation plan
   Develop a roadmap, involve stakeholders, clarify responsibilities (e.g. installation, policy maintenance, incident handling) and define a schedule with tests.

3. Define guidelines and workflows
   Develop rules with specialist departments: Which actions (email, cloud upload, USB) are permitted, logged, encrypted or blocked? Define workflows for manual intervention in the event of critical incidents

4. Introduce and initially monitor DLP
   Install solution, monitor data movement and test policies. Make adjustments before enforcement starts. Critical risks (e.g. mass uploads to the Internet) can be blocked immediately.

5. Enforce policies step by step
   Start with the most sensitive data and channels, maintain monitoring and dynamically adjust policies - ideally depending on the context, for example in the event of unusual access or large volumes of data.

6. Make optimizations
   Use analyses, target risky behavior, check effectiveness and continuously adapt policies to new technologies and threats.

7. Carry out a company-wide rollout
   Extend protection to additional data and channels, adopt or adapt policies. Modern solutions make scaling much easier.

8. Extend DLP to DSPM
   Data Security Posture Management enables automatic data recognition and classification, removes superfluous authorizations and redundant data, thus reducing risks and costs.

Fabian Glöser, Team Lead Sales Engineering Nordics, Central & Eastern Europe at Forcepoint © Forcepoint

DLP is not a mammoth project. With a clear structure, modern tools and AI-supported classification, initial results can be achieved after just a few weeks.
Fabian Glöser, Team Lead Sales Engineering Nordics, Central & Eastern Europe at Forcepoint, says: "A structured approach ensures that human resources are used optimally and that the project goals are not lost sight of. Modern DLP and DSPM solutions also use AI for data classification and come with a ready-made policy set, which significantly reduces manual effort. In many projects, we have completed data discovery and data classification after just two to four weeks, know what is happening with sensitive data and can enforce the first company-specific guidelines."