|John McClurg, Cylance

VP & Ambassador-At-Large of Cylance. Served as the CSO of numerous companies (Dell, Honeywell, and Lucent) and in the U.S. Intelligence Community (FBI, CIA, DOE, DOD). Was voted one of America’s 25 most influential security professionals; holds a J.D. Degree from Brigham Young University; Co-chaired the Overseas Security Advisory Council (OSAC) of the U.S. Department of State; and served as the founding Chairman of the International Security Foundation. Holds an MA in Organizational Behavior, BS and BA degrees in University Studies and Philosophy from Brigham Young, and advanced doctoral studies in Philosophical Hermeneutics at UNC-Chapel Hill and UCLA.
“Not If But When”–Leveraging AI to Jettison the Mantras of the Past
From almost the moment I left academia for government service and thereafter, I was introduced to and have lived stymied, notwithstanding other intentions, in the world of the Reactive and its associated “Defense in Depth” complexity and cost. Proactive prevention eluded me. The security industry has profited quite nicely historically from the insecurity of the world and this reactive paradigm. For decades we in the security profession, have relied on the best technology we had at the time to deflect the onslaught of what we faced daily in the way of malware and other attacks. The effectiveness of that AV technology was always predicated on having latest signatures on hand, which the adversaries could easily defeat with just the slightest modification of their last iteration. That signature-based paradigm required much in the way of downstream resources and expense and usually at least one “sacrificial lamb” upon which to let each new instance of threat sink its teeth. On a good day the capture and deflection rates rarely rose above 50%, requiring that we labor assiduously to manage leaderships’ expectations. We finally got leadership to understand and accept what became almost a mantra in the industry: “It’s not if but when” –as galling professionally as that admission was to make. However, just as predicted 50 years ago by Thomas Kuhn in his book the Structure of Scientific Revolutions, we’re seeing the dawn of a new day where AI’s machine learning and advance mathematical algorithms now offer validated deflection rates, pre-execution, in the realm of 99%. Our discussion will explore my generation’s journey toward this emerging new paradigm, its challenges, and what it portends for the future.
Schedule of Events