LinkShadow’s user and entity behavior analytics(UEBA) uses supervised and unsupervised machine learning algorithms to flag anomalies in users and entities. Our algorithms can pick up anomalies without any configuration and continuously improves its capabilities by analyzing your data. The data models improvise with analyst feedback and volume thereby reducing false positives. These self-learning algorithms continuously adapt and improve themselves driving the accuracy of detection as attacks evolve.
A combination of analyst feedback with the rigorous learning loop, LinkShadow analyses the context in which the asset/user operates providing intelligent analysis and noise-free alerts.