Deterrence Threshold Histogram: Risk vs Reward

Prevention policy for cybercrime is ultimately an economics problem: an attacker acts when the expected reward outweighs the expected cost. This 2D simulator renders that decision as a live histogram of 180 agents' fixed risk thresholds, with a sweeping expected-utility line separating those willing to attack from those currently deterred, and an animated outcome lane below the baseline where in-flight attempts resolve into defense-held or breach outcomes in real time. Tune the same three levers real defenders control (detection investment, punishment severity, target hardening) plus the payoff attackers are chasing, and watch the population, the sweeping E[U] line, and the running tally of value protected versus value breached respond — the same rational-choice model, drawn from Gary Becker's economics of crime, read here as a distribution instead of an orbiting crowd.