research-article

Who do you sync you are?: smartphone fingerprinting via application behaviour

Authors:

Ivan MartinovicAuthors Info & Claims

WiSec '13: Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks

Pages 7 - 12

https://doi.org/10.1145/2462096.2462099

Published: 17 April 2013 Publication History

Abstract

The overall network traffic patterns generated by today's smartphones result from the typically large and diverse set of installed applications. In addition to the traffic generated by the user, most applications generate characteristic traffic from their background activities, such as periodic update requests or server synchronisation. Although the encryption of transmitted data in 3G networks prevents an eavesdropper from analysing the content, periodic traffic patterns leak side-channel information like timing and data volume. In this work, we extract such side-channel features from network traffic generated from the most popular applications, such as Facebook, WhatsApp, Skype, Dropbox, and others, and evaluate whether they can be used to reliably identify a smartphone. By computing fingerprints from approx,6,hours of background traffic, we show that 15 minutes of monitored traffic suffice to reliably identify a smartphone based on its behavioural fingerprint with a success probability of 90%.

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Cited By

Yang XHuang YGuo JZhang DWang Q(2024)Eavesdropping Mobile Apps and Actions Through Wireless Traffic in the Open WorldAdvanced Intelligent Computing Technology and Applications10.1007/978-981-97-5609-4_1(3-15)Online publication date: 31-Jul-2024
https://doi.org/10.1007/978-981-97-5609-4_1
Yang XXu JLi G(2023)Efficient Fingerprinting Attack on Web Applications: An Adaptive Symbolization ApproachElectronics10.3390/electronics1213294812:13(2948)Online publication date: 4-Jul-2023
https://doi.org/10.3390/electronics12132948
Anamuro CLagrange X(2023)Mobile traffic classification through burst traffic statistical features2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)10.1109/VTC2023-Spring57618.2023.10200032(1-5)Online publication date: Jun-2023
https://doi.org/10.1109/VTC2023-Spring57618.2023.10200032
Show More Cited By

Index Terms

Who do you sync you are?: smartphone fingerprinting via application behaviour
1. Security and privacy
  1. Network security

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Published In

cover image ACM Conferences

WiSec '13: Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks

April 2013

230 pages

ISBN:9781450319980

DOI:10.1145/2462096

General Chair:
Levente Buttyán
Budapest University of Technology and Economics, Hungary
,
Program Chairs:
Ahmad-Reza Sadeghi
Technische Universitaet Darmstadt, Fraunhofer SIT, Intel-CRISC, Germany
,
Marco Gruteser
Rutgers University, USA

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSAC: ACM Special Interest Group on Security, Audit, and Control

In-Cooperation

SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 April 2013

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WISEC'13

Sponsor:

SIGSAC

WISEC'13: Sixth ACM Conference on Security and Privacy in Wireless and Mobile Networks

April 17 - 19, 2013

Budapest, Hungary

Acceptance Rates

WiSec '13 Paper Acceptance Rate 26 of 70 submissions, 37%;

Overall Acceptance Rate 98 of 338 submissions, 29%

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Citations

Cited By

Yang XHuang YGuo JZhang DWang Q(2024)Eavesdropping Mobile Apps and Actions Through Wireless Traffic in the Open WorldAdvanced Intelligent Computing Technology and Applications10.1007/978-981-97-5609-4_1(3-15)Online publication date: 31-Jul-2024
https://doi.org/10.1007/978-981-97-5609-4_1
Yang XXu JLi G(2023)Efficient Fingerprinting Attack on Web Applications: An Adaptive Symbolization ApproachElectronics10.3390/electronics1213294812:13(2948)Online publication date: 4-Jul-2023
https://doi.org/10.3390/electronics12132948
Anamuro CLagrange X(2023)Mobile traffic classification through burst traffic statistical features2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)10.1109/VTC2023-Spring57618.2023.10200032(1-5)Online publication date: Jun-2023
https://doi.org/10.1109/VTC2023-Spring57618.2023.10200032
Berdich AGroza BMayrhofer R(2023)A Survey on Fingerprinting Technologies for Smartphones Based on Embedded TransducersIEEE Internet of Things Journal10.1109/JIOT.2023.327788310:16(14646-14670)Online publication date: 15-Aug-2023
https://doi.org/10.1109/JIOT.2023.3277883
Dai JXu XXiao F(2023)GLADSComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.109652225:COnline publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1016/j.comnet.2023.109652
Abd Elaziz MAl‐qaness MDahou AAlsamhi SAbualigah LIbrahim REwees A(2023) Evolution toward intelligent communications: Impact of deep learning applications on the future of 6G technology WIREs Data Mining and Knowledge Discovery10.1002/widm.152114:1Online publication date: 7-Nov-2023
https://doi.org/10.1002/widm.1521
Engelberg AWool AHong YWang L(2022)Classification of Encrypted IoT Traffic despite Padding and ShapingProceedings of the 21st Workshop on Privacy in the Electronic Society10.1145/3559613.3563191(1-13)Online publication date: 7-Nov-2022
https://dl.acm.org/doi/10.1145/3559613.3563191
Dalai ASahoo B(2022)A Device Fingerprinting Technique to Authenticate End-user Devices in Wireless Networks2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)10.1109/iSSSC56467.2022.10051406(1-6)Online publication date: 15-Dec-2022
https://doi.org/10.1109/iSSSC56467.2022.10051406
Li SLiu CLi ZYang QXu AGou G(2022)BSBA: Burst Series Based Approach for Identifying Fake Free-traffic2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM54355.2022.00019(31-39)Online publication date: Jun-2022
https://doi.org/10.1109/WoWMoM54355.2022.00019
Zhu ZShi JWang CXiong GHao ZGou G(2022)MCFM: Discover Sensitive Behavior from Encrypted Traffic in Industrial Control System2022 IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)10.1109/TrustCom56396.2022.00124(897-904)Online publication date: Dec-2022
https://doi.org/10.1109/TrustCom56396.2022.00124
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