Ensuring patient safety in IoMT: A systematic literature review of behavior-based intrusion detection systems
Authors:
- Jordi DoménechJDJordi Doménech
- Isabel V. Martin-FausIMIsabel V. Martin-Faus
- Saber MhiriSMSaber Mhiri
- Josep PeguerolesJPJosep Pegueroles
Open Access
- 5 November 2024
- journal article
- review article
- Published by Elsevier in Internet of Things
- Vol. 28
Abstract
No abstract availableKeywords
This publication has 79 references indexed in Scilit:
- Federated transfer learning for attack detection for Internet of Medical ThingsInternational Journal of Information Security, 2024
- Rough Fermatean fuzzy decision-based approach for modelling IDS classifiers in the federated learning of IoMT applicationsNeural Computing and Applications, 2023
- A comprehensive systematic and bibliometric review of the IoT-based healthcare systemsCluster Computing, 2023
- RETRACTED ARTICLE: IoT-based intrusion detection system for healthcare using RNNBiLSTM deep learning strategy with custom featuresSoft Computing, 2023
- An overview of machine learning methods in enabling IoMT-based epileptic seizure detectionThe Journal of Supercomputing, 2023
- Feature engineering based performance analysis of ML and DL algorithms for Botnet attack detection in IoMTInternational Journal of System Assurance Engineering and Management, 2023
- Internet of Things intrusion detection systems: a comprehensive review and future directionsCluster Computing, 2022
- TrIDS: an intelligent behavioural trust based IDS for smart healthcare systemCluster Computing, 2022
- An investigation and comparison of machine learning approaches for intrusion detection in IoMT networkThe Journal of Supercomputing, 2022
- Anomaly-based intrusion detection system using multi-objective grey wolf optimisation algorithmJournal of Ambient Intelligence and Humanized Computing, 2019