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🗓️ 21 November 2024

⏱️ 25 minutes

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Summary

Introducing Bridging AI and Cybersecurity Gaps with Mileva Security Labs’ Harriet Farlow from Threat Vector by Palo Alto Networks.

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Join us in this episode of Threat Vector as guest host Michael Heller shares his conversation with Harriet Farlow, CEO of Mileva Security Labs and a pioneer in AI security research. With a background spanning AI and national cybersecurity, Harriet shares her journey into adversarial machine learning and the critical importance of addressing AI security vulnerabilities. They discuss how AI models are increasingly exposed to cyber-attacks and why organizations must adopt proactive security measures. Tune in to explore the technical and policy challenges of AI risk, key gaps in model security, and how Mileva Security Labs is working to close these. This episode is essential for cybersecurity leaders looking to protect their systems from evolving AI-based threats.

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About Threat Vector

Threat Vector, Palo Alto Networks podcast, is your premier destination for security thought leadership. Join us as we explore pressing cybersecurity threats, robust protection strategies, and the latest industry trends.

The podcast features in-depth discussions with industry leaders, Palo Alto Networks experts, and customers, providing crucial insights for security decision-makers.

Whether you're looking to stay ahead of the curve with innovative solutions or understand the evolving cybersecurity landscape, Threat Vector equips you with the knowledge needed to safeguard your organization.

Palo Alto Networks

Palo Alto Networks enables your team to prevent successful cyberattacks with an automated approach that delivers consistent security across the cloud, network, and mobile. ⁠http://paloaltonetworks.com⁠

DISCLAIMER: Please note, this is an independent podcast episode not affiliated with, endorsed by, or produced in conjunction with the host podcast feed or any of its media entities. The views and opinions expressed in this episode are solely those of the creators and guests. For any concerns, please reach out to [email protected].

Transcript

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0:00.0	You're listening to the Cyberwire Network, powered by N2K.
0:09.7	The formal pressing issue is the potential for nation states or criminals or just road actors in general to hack the AI that we have now, which they can do.
0:28.7	Welcome to Threat Fector, the Palo Alto Networks podcast where we discuss pressing cybersecurity threats, resilience, and uncover insights into the latest industry trends.
0:38.2	Now, I'm your host, David Moulton, Director of Thought Leadership for Unit 42.
0:45.8	For today's episode, I'm handing over the mic to Michael Heller, our executive producer,
0:50.2	to share his conversation with Harriet Farlow, CEO of Malava Security Labs, and a PhD candidate
0:55.6	in adversarial machine learning. Harriet has a unique background that spans both data science and
1:01.5	cybersecurity, having worked across defense projects in Australia, served in the Australian
1:06.8	government and gained critical experience in the Australian Signals Directorate, the nation's
1:12.2	equivalent of the NSA. She's also a regular speaker at DefCon and is focused on identifying
1:18.0	novel security risks and AI models. Michael and Harriet were both at DefCon this year and recorded
1:23.7	at the event. They discussed AI security, machine learning, and how organizations often
1:29.9	lack awareness of the threats they face. Harriet's work highlights not only the risk, but the ways
1:34.6	that companies can proactively address AI security in a landscape that still lacks mandatory
1:39.8	regulation. Here's their conversation. All right. Well, Harriet, welcome to Threat Factor and thanks for taking the time to talk.
1:47.0	No, thank you. It's great to chat.
1:49.0	So starting off with the easy question. What was your journey to get into cybersecurity?
1:55.0	Hmm. Well, I didn't think that I would end up working in AI security, that's for sure.
2:02.6	My bachelor was in physics and I didn't really know what to do with it, so I did what a lot of physicists
2:07.6	do, and that is to end up in data science.
2:10.6	I was a data scientist for a while in a consulting company in Australia, mostly on defence
2:16.6	projects. I then moved to the United States to work at a startup.
	...

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