Abstract: Methods, systems, and devices for data management are described. A system supporting malware detection may obtain event data such as risk scores corresponding to events associated with a set of computing entities. Using the event data, the system may construct a graph that includes nodes that represent the set of computing entities, and edges that represent the events, where the edges are between initiator and affected nodes and are associated with the respective event risk scores. Using the graph, respective node risk scores may be calculated for at least some nodes of the graph, and one or more anomalous nodes may be identified based on the one or more anomalous nodes having respective node risk scores that satisfy a threshold. The system may then output an indication of one or more computing entities corresponding to the one or more anomalous nodes.

Abstract: Methods, systems, and devices for data management are described. A system supporting malware detection may obtain event data such as risk scores corresponding to events associated with a set of computing entities. Using the event data, the system may construct a graph that includes nodes that represent the set of computing entities, and edges that represent the events, where the edges are between initiator and affected nodes and are associated with the respective event risk scores. Using the graph, respective node risk scores may be calculated for at least some nodes of the graph, and one or more anomalous nodes may be identified based on the one or more anomalous nodes having respective node risk scores that satisfy a threshold. The system may then output an indication of one or more computing entities corresponding to the one or more anomalous nodes.