Evaluating Real-World Adversarial ML Attack Risks and Effective Management: Robustness vs Non-ML Mitigations

In this episode, co-hosts Badar Ahmed and Daryan Dehghanpisheh are joined by Drew Farris (Principal, Booz Allen Hamilton) and Edward Raff (Chief Scientist, Booz Allen Hamilton) to discuss themes from their paper, "You Don't Need Robust Machine Learning to Manage Adversarial Attack Risks," co-authored with Michael Benaroch.

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Additional tools and resources to check out:
Protect AI Radar: End-to-End AI Risk Management
Protect AI’s ML Security-Focused Open Source Tools
LLM Guard - The Security Toolkit for LLM Interactions
Huntr - The World's First AI/Machine Learning Bug Bounty Platform