Log In Now!
The Science Behind Detecting Compromised Identities
Start Date:7/16/2020
Start Time:10:00 AM MDT
Duration:25 minutes
Abstract:
Speaker: Dana Kaufman
Most compromised identities show a deviation from the user’s normal behavior in their interactions with the Identity Provider. It may seem easy to detect compromised account by using simple rules based on past behavior, but these simple rules generate too many false positives, and the signal gets lost in the noise. Come get a peek under the hood of the data science and how behavioral analytics, machine learning and other risk signals can be used to design high-quality identity compromise detection algorithm working in real-time.
Most compromised identities show a deviation from the user’s normal behavior in their interactions with the Identity Provider. It may seem easy to detect compromised account by using simple rules based on past behavior, but these simple rules generate too many false positives, and the signal gets lost in the noise. Come get a peek under the hood of the data science and how behavioral analytics, machine learning and other risk signals can be used to design high-quality identity compromise detection algorithm working in real-time.
Not registered for the The Science Behind Detecting Compromised Identities webcast and interested in signing up? Click below:
Register Now!Speakers
Dana Kaufman
Principal PM Manager – Identity Security and Protection Team
Microsoft
Dana Kaufman is a PM Manager on the Identity Security and Protection team in Microsoft Azure’s Identity Division. Dana leads a team of PMs and Researchers who work on security protection solutions across all of Microsoft’s identity systems. With over 2 decades of experience in the enterprise and consumer software space, he previously worked on advanced machine learning based protection systems for Microsoft’s consumer identities.
By logging in, you agree to the Terms of Use and Privacy Policy.