Dynamic Data Protection
The modern zero-trust architecture
pushes organizations to adopt a more data- and user-centric approach, while moving away from
peripheral-centric approaches. It is a key element
of today's digital business.
Forcepoint's Dynamic Data Protection (DDP) fits
your zero-trust architecture and features:
Personalized adaptive data strategy
Behavioral analysis-driven insights
Data discovery and classification
Maximize the efficiency of security analysts and reduce fatigue
Improve the effectiveness of DLP through behavioral analysis
Personalized adaptive data strategy
Replace extensive and comprehensive security with personalized, adaptive data strategies that will not slow down employees.
Use comprehensive behavior analysis to generate a unique risk score for each user
Apply fine-grained strategies one-to-one based on individual users’ risk scores
Behavioral analysis-driven insight
Dynamic data protection is based on the award-winning enterprise DLP and leverages Forcepoint's
dynamic user protection for cloud hosting behavior analysis.
Unify discovery, analysis and execution, improve the efficiency of investigation of surface anomalies,
and proactively protect your data
Reduce manual decision making and overall alert
volume
Data discovery and classification
Discover data across all channels (including cloud, network, and endpoints), and use classification solutions to safely process critical data and IP.
Identify and protect sensitive data in the corporate environment, such as detection in file servers, SharePoint, Exchange, and databases
Seamless integration with classification solutions
such as Boldon James™, Microsoft® Azure Information Protection and Titus™
Maximize the efficiency of security
a nalysts and reduce alert fatigue
Dynamic data protection transforms an
organization from an event-centric approach
to a risk-centric approach to data protection
Stay ahead of leaks through the orchestration
of policy adjustments at the user level Improve
investigation efficiency and increase team capacity
