Isolation Forest Based Anomaly Detection Approach for Wireless Body Area Networks
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-27409-1_123
Reference21 articles.
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2. Al-Mishmish, H., Alkhayyat, A., Rahim, H.A., Hammood, D.A., Ahmad, R.B., Abbasi, Q.H.: Critical data-based incremental cooperative communication for wireless body area network. Sensors 18, 3661 (2018)
3. Khan, F.A., Haldar, N.A.H., Ali, A., Iftikhar, M., Zia, T.A., Zomaya, A.Y.: A continuous change detection mechanism to identify anomalies in ECG signals for WBAN-based healthcare environments. IEEE Access 5, 13531–13544 (2017)
4. Mohamed, M.B., Makhlouf, A.M., Fakhfakh, A.: Correlation for efficient anomaly detection in medical environment. In: 2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC), pp. 548–553. IEEE, (Year)
5. Salem, O., Serhrouchni, A., Mehaoua, A., Boutaba, R.: Event detection in wireless body area networks using Kalman filter and power divergence. IEEE Trans. Netw. Serv. Manag. 15, 1018–1034 (2018)
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