Connecting the Dots With Machine DataMatthew Joseff of Splunk on Fighting Fraud With Better Data
Machine data and machine learning have the potential to connect disparate data sources, enabling better fraud detection and prevention, says Matthew Joseff of Splunk, who highlights real-world examples of fighting fraud with better data.
In a video interview at Information Security Media Group's recent New York Security Summit, Joseff discusses:
- The difference between machine data and other data sources;
- Use cases for machine data;
- Applications for machine data use in security and fraud prevention.
Joseff is senior security specialist and "minister of reality" at Splunk. Previously, he worked at several startups, integrating technology with real-world productivity.