Anomaly Detection in IoT Networks—Classifications and Analysis Techniques
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-48573-2_67
Reference9 articles.
1. Sahu, N.K., Mukherjee, I.: Machine learning based anomaly detection for IoT network: (Anomaly detection in IoT network). In: 4th International Conference on Trends in Electronics and Informatics (ICOEI) (48184), pp. 787–794. IEEE (2020)
2. Han, S., Wu, Q., Yang, Y.: Machine learning for Internet of Things anomaly detection under low-quality data. Int. J. Distrib. Sens. Netw. 18(10), 15501329221133764 (2022)
3. Munir, M., Siddiqui, S.A., Dengel, A., Ahmed, S.: DeepAnT: a deep learning approach for unsupervised anomaly detection in time series. IEEE Access 7, 1991–2005 (2018)
4. Yasaei, R., Hernandez, F., Faruque, M.A.A.: IoT-CAD: context-aware adaptive anomaly detection in IoT systems through sensor association. In: Proceedings of the 39th International Conference on Computer-Aided Design, pp. 1–9 (2020)
5. Shahraki, A., Taherkordi, A., Haugen, Ø.: TONTA: Trend-based online network traffic analysis in ad-hoc IoT networks. Comput. Netw. 194, 108125 (2021)
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