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UEBA or User and Entity Behaviour Analytics uses rules and machine-learning models to detect unusual behaviour patterns. Sequential anomaly rules analyse actions over time and compare them to normal behaviour, while machine-learning models compare behaviour to peer groups. This helps identify insider threats, compromises, and data exfiltration.

By monitoring behaviour and detecting anomalies, UEBA helps prevent security breaches and protect sensitive data. by combining sequential anomaly rules and machine-learning models, UEBA provides a comprehensive approach to detect and prevent insider threats, compromises, and data exfiltration. This proactive approach helps organisations enhance their security posture by identifying suspicious behaviour and taking appropriate actions to mitigate potential risks before they lead to significant breaches or data loss.

Download the EveryCloud data sheet to learn more about UEBA

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