Bridging AI and Cybersecurity Gaps with Mileva Security Labs’ Harriet Farlow
Nov 21, 2024
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Harriet Farlow, CEO of Mileva Security Labs and a PhD candidate in adversarial machine learning, discusses the critical intersection of AI and cybersecurity. She shares her transformative journey from physics to AI security, emphasizing urgent vulnerabilities inherent in AI technologies. Farlow advocates for proactive security measures and the importance of robust policy reforms. The conversation highlights unique attack surfaces in AI systems and stresses enhancing AI literacy among professionals to combat evolving threats.
Organizations must integrate cybersecurity methodologies into their AI practices to address vulnerabilities from adversarial machine learning.
There is an urgent need for education on AI security risks to build awareness and mitigate exploitable vulnerabilities in AI models.
Deep dives
The Emerging Threat of AI Security
AI security is becoming an increasingly relevant concern as both nation states and criminal actors have the ability to hack AI systems. Many organizations are still unaware of the risks associated with adversarial machine learning, which can leave their systems vulnerable. For instance, Harriet Farlow highlights that while AI and cybersecurity teams often operate in silos, it is critical for organizations to integrate cybersecurity methodologies into their AI practices. This lack of awareness puts businesses at risk, especially since there are currently no mandated regulations governing AI security.
Bridging the Gap Between AI and Cybersecurity
There is a significant gap in training regarding the security of AI, with many data scientists unfamiliar with the adversarial risks their models face. Farlow discusses her research, which focuses on quantifying risks in computer vision and natural language processing by creating new attack scenarios. A key issue is that most professionals in AI are not trained in cyber threats, leading to exploitable vulnerabilities in their models. Organizations must prioritize education around AI security to build a more robust understanding of potential attacks.
Policy Approaches for AI Safety
Farlow emphasizes the importance of developing comprehensive policies focused on AI security, contrasting the current trend of prioritizing AI adoption without addressing the potential risks. Most existing AI policies are primarily concerned with economic advantages rather than the systems' security themselves. The need for a balanced approach that considers both national security and the safety of AI technologies is essential. Advocating for better security practices and transparency from AI companies, as well as increased awareness among stakeholders, can help mitigate the risks associated with unregulated AI.
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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Palo Alto Networks
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