Identification of User Application by an External Eavesdropper using Machine Learning Analysis on Network Traffic

An eavesdropper may infer the computer applications a person uses by collecting and analyzing the network traffic they generate. Such inference may be performed despite applying encryption on the generated packets. In this paper, we investigate the extent of the ability of several machine learning algorithms to perform this privacy breach on the network traffic generated by a user. We measure their accuracy in identifying different applications...