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Your installed apps reveal your gender and more!

Authors:

Suranga Seneviratne,

Aruna Seneviratne,

Prasant Mohapatra,

Anirban MahantiAuthors Info & Claims

SPME '14: Proceedings of the ACM MobiCom workshop on Security and privacy in mobile environments

Pages 1 - 6

https://doi.org/10.1145/2646584.2646587

Published: 11 September 2014 Publication History

Abstract

In this paper, we highlight a potential privacy threat in the current smartphone platforms, which allows any third party to collect a snapshot of installed applications without the user's consent. This can be exploited by third parties to infer various user attributes similar to what is done through tracking. We show that using only installed apps, user's gender, a demographic attribute that is frequently used in targeted advertising, can be instantly predicted with an accuracy around 70%, by training a classifier using established supervised learning techniques.

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Cited By

Motsakou Gandze HWang PHu YYang JCheng K(2024)Which Store Should I Choose? A Comparative Study of Third-Party Mobile App Store Based on Quality EvaluationAdvanced Data Mining and Applications10.1007/978-981-96-0811-9_24(345-360)Online publication date: 13-Dec-2024
https://doi.org/10.1007/978-981-96-0811-9_24
Ahmed MAhmed N(2022)Exploring Unique App Signature of the Depressed and Non-depressed Through Their Fingerprints on AppsPervasive Computing Technologies for Healthcare10.1007/978-3-030-99194-4_15(218-239)Online publication date: 23-Mar-2022
https://doi.org/10.1007/978-3-030-99194-4_15
Neal TWoodard D(2019)You Are Not Acting Like Yourself: A Study on Soft Biometric Classification, Person Identification, and Mobile Device UseIEEE Transactions on Biometrics, Behavior, and Identity Science10.1109/TBIOM.2019.29058681:2(109-122)Online publication date: Apr-2019
https://doi.org/10.1109/TBIOM.2019.2905868
Show More Cited By

Index Terms

Your installed apps reveal your gender and more!
1. Security and privacy
  1. Human and societal aspects of security and privacy
  2. Network security
2. Social and professional topics
  1. Computing / technology policy
    1. Privacy policies

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image ACM Conferences

SPME '14: Proceedings of the ACM MobiCom workshop on Security and privacy in mobile environments

September 2014

48 pages

ISBN:9781450330756

DOI:10.1145/2646584

General Chairs:
Ersin Uzun
PARC, USA
,
Mohamed Ali Kafaar
NICTA, Australia
,
Program Chairs:
Ersin Uzun
PARC, USA
,
Mohamed Ali Kafaar
NICTA, Australia

Copyright © 2014 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]

Sponsors

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: 11 September 2014

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Research-article

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MobiCom'14

Sponsor:

SIGMOBILE

MobiCom'14: The 20th Annual International Conference on Mobile Computing and Networking

September 11, 2014

Hawaii, Maui, USA

Acceptance Rates

SPME '14 Paper Acceptance Rate 7 of 12 submissions, 58%;

Overall Acceptance Rate 7 of 12 submissions, 58%

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Citations

Cited By

Motsakou Gandze HWang PHu YYang JCheng K(2024)Which Store Should I Choose? A Comparative Study of Third-Party Mobile App Store Based on Quality EvaluationAdvanced Data Mining and Applications10.1007/978-981-96-0811-9_24(345-360)Online publication date: 13-Dec-2024
https://doi.org/10.1007/978-981-96-0811-9_24
Ahmed MAhmed N(2022)Exploring Unique App Signature of the Depressed and Non-depressed Through Their Fingerprints on AppsPervasive Computing Technologies for Healthcare10.1007/978-3-030-99194-4_15(218-239)Online publication date: 23-Mar-2022
https://doi.org/10.1007/978-3-030-99194-4_15
Neal TWoodard D(2019)You Are Not Acting Like Yourself: A Study on Soft Biometric Classification, Person Identification, and Mobile Device UseIEEE Transactions on Biometrics, Behavior, and Identity Science10.1109/TBIOM.2019.29058681:2(109-122)Online publication date: Apr-2019
https://doi.org/10.1109/TBIOM.2019.2905868
Ren YTomko MSalim FChan JSanderson M(2018)Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spacesEPJ Data Science10.1140/epjds/s13688-017-0128-27:1Online publication date: 3-Jan-2018
https://doi.org/10.1140/epjds/s13688-017-0128-2
Neal TWoodard D(2018)On the Use of Mobile Calling Patterns for Soft Biometric Classification2018 IEEE 9th International Conference on Biometrics Theory, Applications and Systems (BTAS)10.1109/BTAS.2018.8698591(1-6)Online publication date: 22-Oct-2018
https://dl.acm.org/doi/10.1109/BTAS.2018.8698591
Atkinson JMitchell JRio MMatich G(2018)Your WiFi is leakingFuture Generation Computer Systems10.1016/j.future.2016.05.03080:C(546-557)Online publication date: 1-Mar-2018
https://dl.acm.org/doi/10.1016/j.future.2016.05.030
Wang CChu J(2018)Privacy-Preserved Prediction for Mobile Application AdoptionCloud Computing and Security10.1007/978-3-030-00012-7_17(184-194)Online publication date: 13-Sep-2018
https://doi.org/10.1007/978-3-030-00012-7_17
Unal PTemizel TEren P(2017)What installed mobile applications tell about their owners and how they affect users download behaviorTelematics and Informatics10.1016/j.tele.2017.05.00534:7(1153-1165)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1016/j.tele.2017.05.005
Ünal PTemizel TEren P(2016)Impact of Individual Differences on the Use of Mobile Phones and ApplicationsMobile Web and Intelligent Information Systems10.1007/978-3-319-44215-0_32(379-392)Online publication date: 11-Aug-2016
https://doi.org/10.1007/978-3-319-44215-0_32
Hazan IShabtai AAbadi ADig DDubinsky Y(2015)Noise reduction of mobile sensors data in the prediction of demographic attributesProceedings of the Second ACM International Conference on Mobile Software Engineering and Systems10.5555/2825041.2825062(117-120)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2825041.2825062
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