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The proposed method consists of an algorithm that classifies the data it receives by testing the belongingness of their standard deviation values to established confidence intervals. 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(2006). Detecting Subverted Cryptographic Protocols by Entropy Checking, Laboratoire Specification et Verification."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Wood, D., Apthorpe, N., and Feamster, N. (2017, January 3). Cleartext Data Transmissions in Consumer IoT Medical Devices. Proceedings of the 2017 Workshop on Internet of Things Security and Privacy (IoTS&P \u201917), Dallas, TX, USA.","DOI":"10.1145\/3139937.3139939"},{"key":"ref_3","unstructured":"Cha, S., and Kim, H. (2016, January 25\u201327). Detecting Encrypted Traffic: A Machine Learning Approach. Proceedings of the 17th International Workshop (WISA 2016), Jeju Island, Korea."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/j.1538-7305.1948.tb01338.x","article-title":"A Mathematical Theory of Communication","volume":"27","author":"Shannon","year":"1948","journal-title":"Bell Syst. Tech. J."},{"key":"ref_5","unstructured":"Dorfinger, P. (2010). 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