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Experimental study of energy and bandwidth costs of web advertisements on smartphones.

, , , and . MobiCASE, page 90-97. IEEE, (2014)

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Detection of anomalous behavior of smartphones using signal processing and machine learning techniques., , , , , , and . PIMRC, page 1-7. IEEE, (2017)Smart mobile web browsing., , and . iCAST/UMEDIA, page 671-679. IEEE, (2013)Deep Learning Based Approach for Classifying Power Signals and Detecting Anomalous Behavior of Wireless Devices., , and . SERVICES, page 92-98. IEEE, (2019)Vehicular Networks for a Greener Environment: A Survey., , , and . IEEE Commun. Surv. Tutorials, 15 (3): 1372-1388 (2013)An insight into mobile advertising and its impact on the resources of handheld devices: a survey., , and . Int. J. Big Data Intell., 6 (1): 50-67 (2019)Unsupervised Detection of Anomalous Behavior in Wireless Devices based on Auto-Encoders., , , , , , and . NOMS, page 1-7. IEEE, (2020)Detection of unknown applications in smartphones: A signal processing perspective., , , , , , and . CCECE, page 1-6. IEEE, (2017)A Strongly Non-Intrusive Methodology to Monitor and Detect Anomalous Behaviour of Wireless Devices., , , , and . ISSE, page 1-8. IEEE, (2020)Using Deep Learning to Classify Power Consumption Signals of Wireless Devices: An Application to Cybersecurity., , , and . ICASSP, page 2032-2036. IEEE, (2018)SMoW: An Energy-Bandwidth Aware Web Browsing Technique for Smartphones., and . IEEE Access, (2014)