Your question is Design ML for API Abuse Detection. Take a moment with it on the right.
Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).
You are building a public-facing API gateway for external developers. You need machine learning to help decide whether incoming requests should be allowed, challenged, rate-limited, or blocked based on authentication and authorization risk signals.
What authentication and authorization strategies would you implement for a public-facing API gateway?