Every network intrusion detection system faces the same design question: where do you draw the alert line? Score every connection for anomalousness, and a threshold set too low buries the security operations center in false alerts. Set too high, and a genuine intrusion passes through with no alert at all.
The AI Network Security Lab models 6,000 simulated connections, a small fraction of them real intrusions carrying elevated anomaly scores with overlap into the benign range. Moving the alert threshold higher cuts the alert volume analysts must review, but some real intrusions inevitably fall below the line.
The lesson generalizes past network security: any system that scores individual events for risk and must decide where to draw an action line faces this same trade-off between review workload and missed detections.
🧪 Try it yourself: the AI Network Security Lab simulation lets you move the alert threshold and watch the fleet-wide outcome update live.
🧪 Try it yourself: the AI Network Security Lab simulation lets you experiment with everything described above directly in your browser.