Project Description:
The project partners are working on a solution in the PA-SIEM project that will extend existing SIEM systems by profile-based anomaly detection.
A novel method is being investigated to detect security-related events quickly and reliably based on behavioral changes - without violating data protection. Both real-time events and large amounts of long-term data must be monitored automatically in order to detect conspicuous behavioral patterns. The primary use case considered is the unauthorized removal of confidential data from a network.
The methods and methods to be developed are integrated into a demonstrator in order to be able to evaluate the applicability of the technically and legally secure procedures in real application scenarios and to demonstrate them to potential customers.
On the event of the adoption of the draft regulation laying down measures for a high common level of cybersecurity at the institutions, bodies, offices and agencies of the Union, the AI4HealthSec project kicked off a process to provide its opinion.
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