Anomaly detection in IoT-based healthcare: machine learning for enhanced security
CECOS University · Imam Mohammad ibn Saud Islamic University
Abstract
Internet of Things (IoT) integration in healthcare improves patient care while also making healthcare delivery systems more effective and economical. To fully realize the advantages of IoT in healthcare, it is imperative to overcome issues with data security, interoperability, and ethical considerations. IoT sensors periodically measure the health-related data of the patients and share it with a server for further evaluation. At the server, different machine learning algorithms are applied which help in early diagnosis of diseases and issue alerts in case vital signs are out of the normal range. Different cyber attacks can be launched on IoT devices which can result in compromised security and privacy of…
Citation impact
- FWCI
- 43.14
- Percentile
- 100%
- References
- 21
Authors
2Topics & keywords
- Computer science
- Overfitting
- Machine learning
- Artificial intelligence
- Random forest
- Perceptron
- Dimensionality reduction
- Anomaly detection