Processing and storing event data in a knowledge graph format for anomaly detection

This invention describes a method for detecting unusual activity in computer systems. It gathers data about what machines and human users are doing across various IT tools like identity management, cloud, and network monitoring. This collected data is then standardized and stored in a special database called a knowledge graph, which is optimized to quickly identify anomalies.

Why it matters: The exponential growth of IT event data since 2022 makes the knowledge graph's efficient, on-demand anomaly query capabilities more critical and performant.

Status: Not in forceListed as no longer active. The specific reason is not in the record we hold.
How hard to build: SpecializedSoftware logic, knowledge graph, anomaly detection algorithms

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