Enhancing AI Security: Challenges and Strategies

This chapter explores the complexities and unique challenges of securing AI-driven applications, focusing on the need for integrated security measures throughout the development lifecycle. It discusses the importance of collaborative efforts among various stakeholders and the use of tailored risk frameworks to identify and mitigate vulnerabilities. Additionally, the chapter emphasizes a proactive and adaptive approach to security that balances innovation with effective risk management.

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What does it take to secure AI-based applications in the cloud? In this episode, host Ashish Rajan sits down with Bar-el Tayouri, Head of Mend AI at Mend.io, to dive deep into the evolving world of AI security. From uncovering the hidden dangers of shadow AI to understanding the layers of an AI Bill of Materials (AIBOM), Bar-el breaks down the complexities of securing AI-driven systems. Learn about the risks of malicious models, the importance of red teaming, and how to balance innovation with security in a dynamic AI landscape.