articleInternational Journal of Innovative Science and Research Technology (IJISRT)Apr 3, 2024DIAMOND OA
Artificial Intelligence and Machine Learning Techniques for Anomaly Detection and Threat Mitigation in Cloud-Connected Medical Devices
OAOmolola AkinolaAAAkintunde AkinolaIVIfenna Victor IfeanyiOOOmowunmi OyerindeOJOyedele Joseph Adewole
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Abstract
The Internet of Medical Things (IoMT) has begun functioning like this: improved patient monitoring and an easily accessible digital data warehouse. Despite that, this methodology of the internet will potentially have a counter balance which risks for patient data might involve hacking, data theft, and unauthorized access that may contain great consequences for patient privacy and safety. This article examines the possibility of utilizing new AI technology, including inter alia deep learning, unsupervised learning, and ensemble learning to further boost anomaly detection and threat management in connected cloud medical systems. Many old rules and approaches based on statistics lose relevancy versus the dynamics…
Citation impact
282
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- FWCI
- 87.14
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- 100%
- References
- 31
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Authors
7Topics & keywords
Topics
Keywords
- Anomaly detection
- Cloud computing
- Computer science
- Computer security
- Artificial intelligence
- Operating system
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