Perebor & Security
Perebor Perebor
Security Security
Perebor Perebor
Hey, have you ever tried using machine‑learning models to flag unusual patterns in access logs? I’ve been tinkering with one that learns normal behavior and flags deviations in real time. Think it could help tighten up perimeter checks?
Security Security
Security: That sounds solid. Machine learning can spot the odd ones quick, but make sure you have a good baseline and keep a human eye on the alerts. Too many false positives could blind you to real threats. Keep the logs tight and the thresholds tuned.
Perebor Perebor
Got it, fine-tuning the thresholds is a must. I’ll run some statistical tests on the baseline data to set the exact cut‑offs and then keep an eye on the false‑positive rate. That way we stay sharp without getting overwhelmed.
Security Security
Security: Sounds good. Just remember to update the baseline regularly—people’s habits shift, and the system can drift. Stay alert.
Perebor Perebor
Right, I'll schedule a routine re‑training every week or so to keep the model fresh. That should catch any drift before it becomes an issue.
Security Security
Security: Weekly re‑training is a good plan. Keep the logs clean and the model logged so you can audit any changes. Stay vigilant.