At JNIC 2023, I presented the PreventUEBA solution as part of the TDA en Ciberseguretat project, an initiative focused on advancing applied research and innovation in cybersecurity.
The presentation introduced PreventUEBA as a data-driven approach to analysing user behaviour and identifying early indicators of cyber risk. Developed within the framework of the TDA project, the solution aims to move beyond traditional reactive security models by focusing on proactive risk prevention and user-centric analysis.
By leveraging behavioural analytics and machine learning techniques, PreventUEBA enables the detection of exposure patterns related to threats such as phishing, unsafe browsing, or compromised credentials. The system provides actionable insights that help organisations prioritise mitigation efforts and reduce their attack surface.
This work reflects the broader objectives of the TDA en Ciberseguretat project, which seeks to bridge research and real-world application, fostering the development of innovative cybersecurity solutions with direct impact on organisations and society.