University of Oulu

M. A. Hoque et al., "Context-driven Encrypted Multimedia Traffic Classification on Mobile Devices," 2022 IEEE International Conference on Pervasive Computing and Communications (PerCom), 2022, pp. 54-64, doi: 10.1109/PerCom53586.2022.9762389.

Context-driven encrypted multimedia traffic classification on mobile devices

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Author: Hoque, Mohammad A.1; Finley, Benjamin1; Rao, Ashwin1;
Organizations: 1University of Helsinki, Finland
2Georgia Institute of Technology, Atlanta, USA
3University of Oulu
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2022
Publish Date: 2022-10-11


The Internet has been experiencing immense growth in multimedia traffic from mobile devices. The increase in traffic presents many challenges to user-centric networks, network operators, and service providers. Foremost among these challenges is the inability of networks to determine the types of encrypted traffic and thus the level of network service the traffic needs for maintaining an acceptable quality of experience. Therefore, end devices are a natural fit for performing traffic classification since end devices have more contextual information about the device usage and traffic. This paper proposes a novel approach that classifies multimedia traffic types produced and consumed on mobile devices. The technique relies on a mobile device’s detection of its multimedia context characterized by its utilization of different media input/output components, e.g., camera, microphone, and speaker. We develop an algorithm, MediaSense, which senses the states of multiple I/O components and identifies the specific multimedia context of a mobile device in real-time. We demonstrate that MediaSense classifies encrypted multimedia traffic in real-time as accurately as deep learning approaches and with even better generalizability.

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Series: IEEE International Conference on Pervasive Computing and Communications
ISSN: 2474-2503
ISSN-E: 2474-249X
ISSN-L: 2474-249X
ISBN: 978-1-6654-1643-6
ISBN Print: 978-1-6654-1644-3
Pages: 55 - 64
DOI: 10.1109/PerCom53586.2022.9762389
Host publication: 2022 IEEE International Conference on Pervasive Computing and Communications (PerCom)
Conference: IEEE International Conference on Pervasive Computing and Communications
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: The work was supported by the Academy of Finland IDEAMILL project (Grant Number 335934), 5GEAR project (Grant Number 319669), and FIT project (Grant Number 325570). Mostafa Ammar’s work was partially supported by NSF grant NETS: 1909040.
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