poster

Device analyzer: a privacy-aware platform to support research on the Android ecosystem

Authors:

Daniel T. Wagner,

Daniel R. Thomas,

Alastair R. Beresford,

Andrew RiceAuthors Info & Claims

WiSec '15: Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks

Article No.: 34, Pages 1 - 2

https://doi.org/10.1145/2766498.2774992

Published: 22 June 2015 Publication History

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Abstract

Device Analyzer is an Android app available from the Google Play store. It is designed to collect a large range of data from the handset and, with agreement from our contributors, share it with researchers around the world. Researchers can access the data collected, and can also use the platform to support their own user studies. In this paper we provide an overview of the privacy-enhancing techniques used in Device Analzyer, including transparency, consent, purpose, access, withdrawal, and accountability. We also demonstrate the utility of our platform by assessing the security of the Android ecosystem to privilege escalation attacks and determine that 88% of Android devices are, on average, vulnerable to one or more of these type of attacks.

References

[1]

D. T. Wagner, A. Rice, and A. R. Beresford, "Device Analyzer: Understanding smartphone usage.," in Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous 2013), Springer, 2014, pp. 195--208, isbn: 978-3-319-11568-9.

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[2]

https://deviceanalyzer.cl.cam.ac.uk/keyValuePairs.htm.

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[3]

https://deviceanalyzer.cl.cam.ac.uk/.

Google Scholar

[4]

C. Information Commissioner of Ontario, Privacy by design, See https://privacybydesign.ca/.

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[5]

M. Langheinrich, "Privacy by design---principles of privacy-aware ubiquitous systems," in Proceedings of the Third International Conference on Ubiquitous Computing (UbiComp), Atlanta, Georgia, USA: Springer-Verlag, 2001, pp. 273--291, isbn: 3-540-42614-0.

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Graham-Knight JCorbett JLasserre PLiang HHasan K(2020)Exploring Haptic Feedback for Common Message Notification Between Intimate Couples with SmartwatchesProceedings of the 32nd Australian Conference on Human-Computer Interaction10.1145/3441000.3441012(245-252)Online publication date: 2-Dec-2020
https://dl.acm.org/doi/10.1145/3441000.3441012
Abbott JMacLeod HNurain NEkobe GPatil SBrewster SFitzpatrick GCox AKostakos V(2019)Local Standards for Anonymization Practices in Health, Wellness, Accessibility, and Aging Research at CHIProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300692(1-14)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290605.3300692
Chatzopoulos DBermejo CHaq ELi YHui P(2019)D2D Task Offloading: A Dataset-Based Q&AIEEE Communications Magazine10.1109/MCOM.2018.170087357:2(102-107)Online publication date: Feb-2019
https://doi.org/10.1109/MCOM.2018.1700873
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Device analyzer: a privacy-aware platform to support research on the Android ecosystem

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Information & Contributors

Information

Published In

WiSec '15: Proceedings of the 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks

June 2015

256 pages

ISBN:9781450336239

DOI:10.1145/2766498

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

In-Cooperation

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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 June 2015

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Qualifiers

Poster

Funding Sources

EPSRC

Conference

WiSec'15

Sponsor:

SIGSAC
US Army Research Office
NSF

WiSec'15: 8th ACM Conference on Security & Privacy in Wireless and Mobile Networks

June 22 - 26, 2015

New York, New York

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Overall Acceptance Rate 98 of 338 submissions, 29%

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Cited By

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Graham-Knight JCorbett JLasserre PLiang HHasan K(2020)Exploring Haptic Feedback for Common Message Notification Between Intimate Couples with SmartwatchesProceedings of the 32nd Australian Conference on Human-Computer Interaction10.1145/3441000.3441012(245-252)Online publication date: 2-Dec-2020
https://dl.acm.org/doi/10.1145/3441000.3441012
Abbott JMacLeod HNurain NEkobe GPatil SBrewster SFitzpatrick GCox AKostakos V(2019)Local Standards for Anonymization Practices in Health, Wellness, Accessibility, and Aging Research at CHIProceedings of the 2019 CHI Conference on Human Factors in Computing Systems10.1145/3290605.3300692(1-14)Online publication date: 2-May-2019
https://dl.acm.org/doi/10.1145/3290605.3300692
Chatzopoulos DBermejo CHaq ELi YHui P(2019)D2D Task Offloading: A Dataset-Based Q&AIEEE Communications Magazine10.1109/MCOM.2018.170087357:2(102-107)Online publication date: Feb-2019
https://doi.org/10.1109/MCOM.2018.1700873
Jayarajah KBalan RRadhakrishnan MMisra ALee YBalan RMisra AAgarwal SMascolo C(2016)LiveLabsProceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services10.1145/2906388.2906400(1-15)Online publication date: 20-Jun-2016
https://dl.acm.org/doi/10.1145/2906388.2906400
Chen LWang LZhang DLi SPan G(2016)EnUp: Energy-Efficient Data Uploading for Mobile Crowd Sensing Applications2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld)10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0168(1074-1078)Online publication date: Jul-2016
https://doi.org/10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0168
Lepinski MLevin DMcCarthy DWatro RLack MHallenbeck DSlater D(2016)Privacy-Enhanced Android for Smart Cities ApplicationsSmart City 360°10.1007/978-3-319-33681-7_6(66-77)Online publication date: 29-Jun-2016
https://doi.org/10.1007/978-3-319-33681-7_6

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