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Detection of Anomalous Behavior in Wireless Devices Using Changepoint Analysis.

, , , , and . ICIOT, page 82-90. IEEE, (2019)

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Detection of Anomalous Behavior in Wireless Devices Using Changepoint Analysis., , , , and . ICIOT, page 82-90. IEEE, (2019)Machine Learning Based Malware Detection in Wireless Devices Using Power Footprints., , , , , , and . ISSE, page 1-8. IEEE, (2019)Towards Developing a Robust Intrusion Detection Model Using Hadoop-Spark and Data Augmentation for IoT Networks., , , , and . Sensors, 22 (20): 7726 (2022)Experimental study of energy and bandwidth costs of web advertisements on smartphones., , , and . MobiCASE, page 90-97. IEEE, (2014)Data Balancing and Hyper-parameter Optimization for Machine Learning Algorithms for Secure IoT Networks., , , and . Q2SWinet, page 71-78. ACM, (2022)Reflection on Software Architecture Practices - What Works, What Remains to Be Seen, and What Are the Gaps., , and . WICSA, page 221-222. IEEE Computer Society, (2005)Google Traces Analysis for Deep Machine Learning Cloud Elastic Model., , , and . SmartNets, page 1-6. IEEE, (2019)A price setting approach to power trading in cognitive radio networks., , , , and . ICUMT, page 878-883. IEEE, (2012)Detection of unknown applications in smartphones: A signal processing perspective., , , , , , and . CCECE, page 1-6. IEEE, (2017)A Power Signal Based Dynamic Approach to Detecting Anomalous Behavior in Wireless Devices., , , , and . MobiWac, page 9-18. ACM, (2018)