How can we verify identity using unstructured data from a user device? While biometrics like fingerprinting and facial recognition are often used for authentication, research around natural language processing has found people's use of language as uniquely identifying.

In this session, we will discuss multiple facets of language modeling:

  • Efficacy on different kinds of unstructured text within a corporate network
  • As a technique to detect anomalous user activity, compromised accounts, and stolen credentials
  • As an integral part of a cybersecurity program in addition to UEBA and risk-adaptive protection
Chris Poirel

Chris Poirel

Dr. Chris Poirel leads the data processing engineering team in the development of core analytic infrastructure and contributes heavily to all Forcepoint UEBA (formerly RedOwl) data science efforts. Chris joined RedOwl in 2013 after completing his PhD in computer science at Virginia Tech.

Eduardo Luiggi

Dr. Eduardo Luiggi serves as a Senior Data Scientist at Forcepoint (formerly RedOwl), where he is responsible for regulatory and cybersecurity enterprise solutions. He has a PhD in Experimental High Energy Physics from Vanderbilt University and conducted postdoctoral research at the University of Colorado, where he led a statistical data analysis team at the Large Hadron Collider.