Graham Holmes — Adversarial Machine Learning

Graham Holmes is the founder and owner of AoP CyberSecurity, LLC whose mission is to enable organizations to “create scalable and effective strategies for trustworthy outcomes. ” His career includes over 22 years as a leader at Cisco Systems, where he infamously served as my boss for a period of time, and before that he served in the US Navy as a commissioned officer for 9 years. Graham joins us to discuss adversarial machine learning. We explore the threats and attacks in an AI/ML world, and review solutions to address these challenges using trust as a foundation. Please enjoy this conversation with Graham Holmes. We explore the threats and attacks in an artificial intelligence machine learning world and review solutions to address these challenges using trust as a foundation.

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About Security Journey
Graham Holmes is the founder and owner of AOP Cybersecurity, whose mission is to enable organizations to create scalable and effective strategies for trustworthy outcomes.
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Connect with Graham Holmes:
→ Life 3.0
→ Microsoft Security Development Lifecycle (SDL)

Mentioned in this episode:
→ Life 3.0
→ Microsoft Security Development Lifecycle (SDL)
→ Artificial Intelligence

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Chapters:
00:00 Meet Graham Holmes: Graham Holmes — Adversarial Machine Learning
02:31 Yeah, that's awesome, and congratulations on that. And it's some, I
06:32 So our topic then is adversarial machine learning. And so I
08:53 It sounds like— and actually, I didn't even— I forgot to
13:44 Graham, is it full— can you reverse engineer Kind of what
25:21 Yeah, because when you think about a vulnerability in a modern
27:38 You know, we've talked about, uh, definitely importance of, of application
32:14 Since we've covered— I feel like we've covered the attacks well
35:41 So you've, uh, you're branching out on a new venture here
37:40 Here's a— and I know we're coming to the close here
40:54 Graham, are there any, uh, resources that you would recommend
43:31 That's, uh, great. Uh, Life 2.0, I'm gonna remember that. Check