Artificial Intelligence & Machine Learning , Next-Generation Technologies & Secure Development

Connecting the Dots With Machine Data

Matthew Joseff of Splunk on Fighting Fraud With Better Data
Matthew Joseff, senior security specialist, Splunk

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.

See Also: User Entity & Behavior Analytics 101: Strategies to Detect Unusual Security Behaviors

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.

About the Author

Nick Holland

Nick Holland

Former Director, Banking and Payments

Holland focused on the intersection of digital banking, payments and security technologies. He has spoken at a variety of conferences and events, including Mobile World Congress, Money2020, Next Bank and SXSW, and has been quoted by The Wall Street Journal, CNN Money, MSNBC, NPR, Forbes, Fortune, BusinessWeek, Time Magazine, The Economist and the Financial Times.

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