TouchTrack

How unique are your touch gestures?

Rahat Masood, Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Mohamed Ali Kaafar

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

This paper studies a privacy threat induced by the collection and monitoring of a user's touch gestures on touchscreen devices. The threat is a new form of persistent tracking which we refer to as touch-based trackingž. It goes beyond tracking of virtual identities and has the potential for cross-device tracking as well as identifying multiple users using the same device. To demonstrate the likelihood of touch-based tracking, we propose an information theoretic method that quantiies the amount of information revealed by individual features of gestures, samples of gestures as well as samples of gesture combinations, when modelled as feature vectors. We have also developed a purpose-built app, named TouchTrackž that collects data from users and informs them on how unique they are when interacting with their touch devices. Our results from 89 diferent users indicate that writing samples and left swipes can reveal 73.7% and 68.6% of user information, respectively. Combining diferent combinations of gestures results in higher uniqueness, with the combination of keystrokes, swipes and writing revealing up to 98.5% of information about users. We correctly re-identify returning users with a success rate of more than 90%.

Original languageEnglish
Title of host publicationCCS 2017
Subtitle of host publicationProceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery
Pages2555-2557
Number of pages3
ISBN (Electronic)9781450349468
DOIs
Publication statusPublished - 30 Oct 2017
Externally publishedYes
Event24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017 - Dallas, United States
Duration: 30 Oct 20173 Nov 2017

Publication series

NameProceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)1543-7221

Conference

Conference24th ACM SIGSAC Conference on Computer and Communications Security, CCS 2017
CountryUnited States
CityDallas
Period30/10/173/11/17

Keywords

  • Behavioural Biometrics
  • Mobile Privacy
  • Touch Gestures
  • Touch-based Tracking

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  • Cite this

    Masood, R., Zhao, B. Z. H., Asghar, H. J., & Kaafar, M. A. (2017). TouchTrack: How unique are your touch gestures? In CCS 2017: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security (pp. 2555-2557). (Proceedings of the ACM Conference on Computer and Communications Security). Association for Computing Machinery. https://doi.org/10.1145/3133956.3138850