@article{028862bb719b4a498fcc150d6136731d,
title = "Transfer learning for user action identication in mobile apps via encrypted traffic analysis",
abstract = "Recent academic studies have demonstrated the possibility of inferring user actions performed in mobile apps by analyzing the resulting encrypted network traffic. Due to the multitude of app versions, mobile operating systems, and device models (collectively referred to in this paper as configurations) previous approaches are not applicable to real life settings. In this work, we ex-tend the ability of these approaches to generalize across different configurations. We treat the different configurations as a case for transfer learning, and adapt the co-training method to sup-port the transfer learning process. Our approach leverages a small number of labeled instances of encrypted traffic from a source configuration, in order to construct a classifier capable of identi-fying a users actions in a different (target) configuration which is completely unlabeled. Experi-ments on real datasets collected from different applications on Android devices show that the proposed method achieves F1 measures over 0.8 for most of the considered user actions.",
keywords = "co-training, encrypted network traffic, social applications, transfer learning",
author = "Edita Grolman and Andrey Finkelshtein and Rami Puzis and Asaf Shabtai and Gershon Celniker and Ziv Katzir and Liron Rosenfeld",
note = "Funding Information: The authors would like to thank Dvir Cohen and Tatiana Frenklah for their support and involvement at various stages of this research. The research was supported by the Commerce, Office of the Chief Scientist of Israel and by the Ministry of Science & Technology of Israel and Kreitman “Negev{"} Fellowship at the Ben-Gurion University of the Negev. Funding Information: Dr. Rami Puzis is a senior lecturer at the Department of Software and Information Systems Engineering at Ben-Gurion University. Rami has graduated BSc in Software Engineering and MSc and PhD in Information Systems Engineering. He was a post doctoral research associate in the Lab for Computational Cultural Dynamics, University of Maryland. His main research interests include network analysis with applications to security, social networks, computer communication, and simulations. Rami has managed multiple research projects funded by Deutsche Telekom AG, Israeli Ministry of Defense, Israeli Ministry of Trade and Commerce, and leading cybersecurity industries in Israel. His recent research projects focused on web intelligence, security awareness in mobile environments, protecting organizations from attacks through social networks. Publisher Copyright: {\textcopyright} 2018 IEEE.",
year = "2018",
month = mar,
day = "1",
doi = "10.1109/MIS.2018.111145120",
language = "English",
volume = "33",
pages = "40--53",
journal = "IEEE Intelligent Systems",
issn = "1541-1672",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",
}