In-app Activity Recognition from Wi-Fi Encrypted Traffic.pdf (373.53 kB)
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In-app activity recognition from Wi-Fi encrypted traffic

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In today’s world mobile applications have been widely used, which bring great convenience to people’s lives. However, at the same time user privacy is potentially threatened. This paper shows that a passive eavesdropper can identify fine grained user activities (known as in-app activities) by analysing encrypted traffic collected by sniffing a wireless network. Even though encryption protocols are used to secure communications over the Internet, side channel data such as frame length, inter arrival time and direction are still leaked from encrypted traffic. To identify in-app activities from this side channel data machine learning techniques are used. Furthermore, we show that just by observing only a small subset of encrypted traffic (rather than observing the entire transaction), one can identify in-app activities accurately. The proposed solution was evaluated with 51 in-app activities from three popular social networking apps and obtained high detection accuracy, 95.4% when Bayes Net algorithm is used.

Funding

UK-India Education Research Initiative (UKIERI) through grant UGC-UKIERI-2016-17-019.

History

School

  • Loughborough University London

Published in

Intelligent Computing: Proceedings of the 2020 Computing Conference

Volume

1

Pages

685 - 697

Source

Science and Information Conference (SAI 2020)

Publisher

Springer

Version

AM (Accepted Manuscript)

Rights holder

© Springer Nature Switzerland AG

Publisher statement

This is a pre-copyedited version of a contribution published in Intelligent Computing: Proceedings of the 2020 Computing Conference edited by Kohei Arai, Supriya Kapoor and Rahul Bhatia published by Springer. The definitive authenticated version is available online via http://dx.doi.org/10.1007/978-3-030-52249-0_46.

Acceptance date

31/10/2019

Publication date

2020-07-04

Copyright date

2020

ISBN

9783030522483; 9783030522490

eISSN

2194-5357

Book series

Advances in Intelligent Systems and Computing; 1228

Language

en

Editor(s)

Kohei Arai, Supriya Kapoor, Rahul Bhatia

Location

London, UK

Event dates

16th July 2020 - 17th July 2020

Depositor

Dr Safak Dogan Deposit date: 13 December 2019

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