Guest:

  • Alex Polyakov, CEO of Adversa.ai

Topics:

  • You did research by analyzing 2000 papers on AI attacks released in the previous decade. What are the main insights?
  • How do you approach discovering the relevant threat models for various AI systems and scenarios?
  • Which threats are real today vs in a few years?
  • What are the common attack vectors? What do you see in the field of supply chain attacks on AI, software supply, data?
  • All these reported cyberphysical attacks on computer vision, how real are they, and what are the possible examples of exploitation? Are they a real danger to people?
  • What are the main differences between protecting AI vs protecting traditional enterprise applications?
  • Who should be responsible for Securing AI? What about for building trustworthy AI?
  • Given that the machinery of AI is often opaque, how to go about discovering vulnerabilities? Is there responsible disclosure for AI vulnerabilities, such as in open-source models and in public APIs?
  • What should companies do first, when embarking on an AI security program? Who should have such a program?

Resources:

  • “EP52 Securing AI with DeepMind CISO” (ep52)
  • “EP68 How We Attack AI? Learn More at Our RSA Panel!” (ep68)
  • Adversarial AI attacks work on Humans (!)
  • “Maverick* Research: Your Smart Machine Has Been Conned! Now What?” (2015)
  • “The Road to Secure and Trusted AI” by Adversa AI
  • “Towards Trusted AI Week 37 – What are the security principles of AI and ML?”
  • Adversa AI blog
  • AIAAIC Repository
  • Machine Learning Security Evasion Competition at MLSec