Hybrid MLOps framework for automated lifecycle management of adaptive phishing detection models.

ABSTRACT: Phishing detection models degrade quickly due to drift, adversarial evasion, and fairness issues. Existing MLOps platforms mainly automate deployment and monitoring. Prior works have examined SHAP-based monitoring, retraining, or fairness audits separately, but lack an integrated theory of resilience for adversarial environments. We introduce the Hybrid MLOps Framework (HAMF), a system designed to embed resilience and ethical governance into the lifecycle of phishing detection models. HAMF is 'hybrid' because it unifies proactive and reactive adaptation, combining automation with stakeholder oversight, and embedding resilience with ethical governance. HAMF treats resilience as an integrated lifecycle property, designed to simultaneously preserve model accuracy, fairness, and stakeholder tr

SUBMITTER: Reda A 

PROVIDER: S-EPMC12586440 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature