Five signs data drift is already undermining your security models
via venturebeat.com
Short excerpt below. Read at the original source.
Data drift happens when the statistical properties of a machine learning (ML) model’s input data change over time, eventually rendering its predictions less accurate. Cybersecurity professionals who rely on ML for tasks like malware detection and network threat analysis find that undetected data drift can create vulnerabilities. A model trained on old attack patterns may […]