Mike Kiser

Global Security Advocate, Office of the CTO; SailPoint Technologies
Mike Kiser is insecure. He has been this way since birth, despite holding a panoply of industry positions over the past 20 years—from the Office of the CTO to Security Strategist to Security Analyst to Security Architect—that might imply otherwise. In spite of this, he has designed, directed, and advised on large-scale security deployments for a global clientele. In a past life, he simulated galactic collisions on Cray Y-MP supercomputers. He is currently in a long-term relationship with fine haberdashery, is a chronic chronoptimist (look it up), and delights in needlessly convoluted verbiage. He has been a speaker on topics ranging from identity governance to security analytics, network security, and various related privacy issues, and is the co-host of a podcast illuminating all things identity. He warmly embraces the notion that security is more of a state of mind than a destination.

Mike's Session


Thursday, June 27
11:30 - 12:20 pm
Monroe
Sailpoint Masterclass: What’s AI got to do, got to do with it?
Great music does not spring out of nothingness —in the hands of a talented producer, trivial melodies become emotionally powerful works of art. Artificial intelligence and machine learning can play a similar role in identity. We’ll learn from Tina Turner*, Dr. Dre*, Sting*, and yes, even Taylor Swift* as we explore how machine learning can improve our approach to identity, building up a live-produced, original song as we go. As we construct the song, we’ll develop a machine learning use case for identity: use of the SIR (susceptible, infected, recovered) model for the spread of disease to predict the spread of entitlements and access within an identity population. Along the way, we’ll describe different techniques available for machine learning and explore their strengths and weaknesses for application to identity use cases. In the past, there has been a danger in seeing every problem as solvable by AI. We'll sift through the marketing hype as we identify real-world scenarios where machine learning can be used today to improve the efficacy of ongoing identity programs. *Note that neither Tina Turner, Dr. Dre, Sting, nor Taylor Swift will be in attendance. If this changes, this abstract will be updated.

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