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Centralized detection models often fail to deliver timely or scalable responses under real-world IoT conditions.\u00a0This study proposes a hybrid fog\u2013cloud architecture tailored for healthcare-oriented IoT threat detection, incorporating blockchain-based auditability. The architecture utilizes fog- and cloud-level XGBoost classifiers trained on BoT-IoT and ToN-IoT datasets, with SMOTE applied to mitigate class imbalance. A lightweight blockchain module is integrated at the fog layer to log predictions in real-time for tamper-evident traceability. Simulations were performed using 50 fog-predicted events to evaluate performance, energy usage, and blockchain entropy.\u00a0The system achieved an average block creation time of under 20 ms with minimal CPU and memory overhead. It also demonstrated robustness against tampering, preserving data integrity. The fog-level model achieved competitive metrics (AUC = 1, F1-score = 98.70%, Accuracy = 99.80%) compared to the cloud model, while outperforming it in terms of response latency and localized decision-making.\u00a0The proposed blockchain-integrated fog\u2013cloud framework enables secure, low-latency, and scalable threat detection for healthcare IoT systems, offering a promising foundation for privacy-aware edge intelligence.<\/jats:p>","DOI":"10.1007\/s10586-025-05932-7","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T20:32:15Z","timestamp":1768077135000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Energy-efficient threat detection in IoT healthcare using AI and blockchain-enhanced fog\u2013cloud architecture"],"prefix":"10.1007","volume":"29","author":[{"given":"Malak","family":"Alamri","sequence":"first","affiliation":[]},{"given":"Noshina","family":"Tariq","sequence":"additional","affiliation":[]},{"given":"Mamoona","family":"Humayun","sequence":"additional","affiliation":[]},{"given":"Menwa","family":"Alshammeri","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"key":"5932_CR1","doi-asserted-by":"publisher","first-page":"59353","DOI":"10.1109\/ACCESS.2021.3073408","volume":"9","author":"N Mishra","year":"2021","unstructured":"Mishra, N., Pandya, S.: Internet of things applications, security challenges, attacks, intrusion detection, and future visions: A systematic review. 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