Splunk Inc.

John Clifton Pierce

George Apostolopoulos

Joseph Auguste Zadeh

Rodolfo Soto

Various embodiments of the present invention set forth techniques for security monitoring of a network connection, including analyzing network traffic data for a network connection associated with a computing device, identifying one or more network traffic metrics for the network connection based on the network traffic data, determining that the network connection corresponds to at least one network connection profile based on the one or more network traffic metrics, detecting a potential security threat for the network connection based on the one or more network traffic metrics and the at least one network connection profile, and initiating a mitigation action with respect to the network connection in response to detecting the potential security threat. Advantageously, the techniques allow detecting potential security threats based on network traffic metrics and categorizations, without requiring monitoring of the content or the total volume of all traffic exchanged via the connection.

Security monitoring of network connections using metrics data

Techniques are described for analyzing data regarding activity in an IT environment to determine information regarding the entities associated with the activity and using the information to detect anomalous activity that may be indicative of malicious activity. In an embodiment, a plurality of events reflecting activity by a plurality of entities in an IT environment are processed to resolve the identities of the entities, discover how the entities fit within a topology of the IT environment, and determine what the entities are. This information is then used to generate an entity relationship graph that includes nodes representing the entities in the IT environment and edges connecting the nodes representing interaction relationships between the entities. In some embodiments, baselines are established by monitoring the activity between entities. This baseline information can be represented in the entity relationship graph in the form of directionality applied to the edges. The entity relationship graph can then be monitored to detect anomalous activity.

Anomaly detection based on changes in an entity relationship graph

Anomaly detection based on information technology environment topology

Techniques are described for analyzing data regarding activity in an IT environment to determine information regarding the entities associated with the activity and using the information to detect anomalous activity that may be indicative of malicious activity. In an embodiment, a plurality of events reflecting activity by a plurality of entities in an IT environment are processed to resolve the identities of the entities, discover how the entities fit within a topology of the IT environment, and determine what the entities are. This information is then used to generate a entity relationship graph that includes nodes representing the entities in the IT environment and edges connecting the nodes representing interaction relationships between the entities. In some embodiments, baselines are established by monitoring the activity between entities. This baseline information can be represented in the entity relationship graph in the form of directionality applied to the edges. The entity relationship graph can then be monitored to detect anomalous activity.

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San Jose, CA, United States of America

John Clifton Pierce