Cybercrime Deterrence Model: Risk vs Reward

Prevention policy for cybercrime is ultimately an economics problem: an attacker acts when the expected reward outweighs the expected cost. This simulator renders that decision as a live population of 180 agents orbiting a protected target — each holding its own risk threshold — and lets you adjust the three levers real defenders control (detection investment, punishment severity, target hardening) plus the payoff attackers are chasing. Watch attacks launch, get blocked, get traced, or succeed in real time, while live readouts track the expected-utility calculation, the predicted attacker share, and the running tally of value protected versus value breached — the same rational-choice model, drawn from Gary Becker's economics of crime, that underlies real-world cybercrime prevention strategy.