Aca

Problem Statement You have deployed an ML model and someone asks: “Is it robust to adversarial attack?” You do not have a principled way to answer. You could fuzz every input, but that is expensive and tells you nothing about which attacks are structurally impossible versus which are just untested. You need a method that maps the attack surface before you start testing. Adversarial Control Analysis (ACA) gives you that map. It is a three-step process that classifies every input by who controls it, then focuses your defenses on the inputs the adversary cannot manipulate. I have applied it across six domains – network IDS, vulnerability management, AI agents, post-quantum crypto, fraud detection, and ML supply chains – and the finding is always the same: the inputs the attacker cannot touch are your real defense. ...