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Monthly Chapter Meeting – November 2021 (VIRTUAL)
November 4, 2021 @ 6:00 pm - 8:30 pm
Monthly Chapter Meeting | November 4, 2021 | 6-8:30pm
REGISTRATION – ONE LINK FOR ALL – YOU MUST RSVP
Guest & Member Registration – https://www.eventbrite.com/e/raleigh-issa-chapter-meeting-november-2021-virtual-tickets-202789588117
6:00 PM – 6:15PM – Board Updates
6:15 PM to 7:15 PM –Keynote Presentation: Applying advances in machine learning to improving cybersecurity by Michael
7:15 PM to 8:30 PM – Back to Basics: TBD
7:15 PM to 9 PM – Career Services: TBD
* Informal discussion: ~7:15-7:30 pm
* Formal Presentation & Q&A: 7:30-8:30 pm
* Recruiter Update & Job Opportunities: ~8:30-9:00 pm (can end earlier)
Title: Applying advances in machine learning to improving cybersecurity
In today’s world, you can’t make it through your day without hearing something about artificial intelligence.
But, the majority of recent noteworthy achievements in machine learning are the result of large models trained on large labeled datasets; this is termed “supervised learning”. Supervised methods require labels for each sample. For example, in computer vision, this could be labeling images as containing a cat or a dog, something any person can easily do.
Unfortunately, this simple labeling scheme is not always feasible.
When you stray from the more traditional domains of machine learning, like computer vision, towards data-driven solutions for more esoteric domains like cybersecurity or networking, labeled data becomes scarce. Instead of being able to outsource labeling to anyone, subject matter experts need to be brought in, and they are in short supply. How would most people know if an API call or an SQL query is malicious or abnormal?
Anomaly detection methods are preferred over supervised approaches when the cost of obtaining labels is high. In this talk, we walk through why anomaly detection methods are effective, how they can be applied to real-world problems, how to simplify deployment into existing infrastructure and where this field is headed.
Michael, Executive Director of Research and Engineering at IOMAXIS, LLC Bio:
Michael is the Executive Director of Research and Engineering at IOMAXIS, LLC, a privately held company predominately providing cyber infrastructure, secure data transport, and engineering services for federal clients. His current focus is finding new ways to bring innovation in the areas of cyber, communications, and computing.
Michael, a North Carolina native, received his BS in Physics from Wake Forest University (2007) and received his Ph.D. from NC State University (Physics, 2012). Prior to IOMAXIS, Michael spent 7 years as a Lead Scientist at the Naval Surface Warfare Center, working on advanced concept development across a broad array of technologies spanning computational electromagnetics, meta-materials, high energy lasers, and artificial intelligence.
Personally, Michael is passionate about how emerging technologies can be used to dramatically impact people’s lives.
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