Data-Driven Methods for Wi-Fi Anomaly Detection
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-62495-7_36
Reference10 articles.
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2. Redmore, J., Teckchandani, A.: Top key performance indicators in Wi-Fi. CableLabs Technical Brief, July 2016 (2016)
3. Cook, A.A., Mısırlı, G., Fan, Z.: Anomaly detection for IoT time-series data: a survey. IEEE Internet Things J. 7(7), 6481–6494 (2020). https://doi.org/10.1109/JIOT.2019.2958185
4. Syafrudin, M., Alfian, G., Fitriyani, N.L., Rhee, J.: Performance analysis of IoT-based sensor, big data processing, and machine learning model for real-time monitoring system in automotive manufacturing. Sensors 18, 2946 (2018). https://doi.org/10.3390/s18092946
5. Gaddam, A., Wilkin, T., Angelova, M.: Anomaly detection models for detecting sensor faults and outliers in the IoT - a survey. In: Proceedings of the IEEE International Conference on Software Testing, Verification and Validation Workshops, pp. 1–6 (2019). https://doi.org/10.1109/ICST46873.2019.9047684
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