Recognizing Your Touch: Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration

Pin Shen The, Ning Zhang, Andrew Beng Jin Teoh, Ke Chen

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

7 Citations (Scopus)

Abstract

Mobile devices have become an integral part of our routine activities. Some of the activities involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.). These mobile electronic services (e-Services) typically require a method to securely identify and authenticate a claimed identity. Currently, e-Services typically use a knowledgebased authentication method by demonstrating the knowledge of secret (e.g. password), but it is vulnerable to a number of security attacks, e.g. shoulder spoofing and brute force attacks. To thwart the attacks and to make the authentication method more secure, this paper describes our efforts in investigating the benefits of integrating touch dynamics biometrics, into a PIN-based authentication method. It reports the collection of a comprehensive reference dataset from 150 subjects, the extraction of feature data from the dataset, and the classifications and the use of the feature data to identify a user. Experimental results show that, even when the PIN is exposed, 9 out of 10 impersonation attempts can be successfully detected.

Original languageEnglish
Title of host publication13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings
EditorsIsmail Khalil, Matthias Steinbauer, Liming Chen, Gabriele Anderst-Kotsis
PublisherAssociation for Computing Machinery, Inc
Pages108-116
Number of pages9
ISBN (Electronic)9781450334938
DOIs
Publication statusPublished - 2015 Dec 11
Event13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Brussels, Belgium
Duration: 2015 Dec 112015 Dec 13

Publication series

Name13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings

Other

Other13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015
CountryBelgium
CityBrussels
Period15/12/1115/12/13

Fingerprint

Mobile devices
Authentication
Biometrics

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications

Cite this

The, P. S., Zhang, N., Teoh, A. B. J., & Chen, K. (2015). Recognizing Your Touch: Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration. In I. Khalil, M. Steinbauer, L. Chen, & G. Anderst-Kotsis (Eds.), 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings (pp. 108-116). (13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings). Association for Computing Machinery, Inc. https://doi.org/10.1145/2837126.2837127
The, Pin Shen ; Zhang, Ning ; Teoh, Andrew Beng Jin ; Chen, Ke. / Recognizing Your Touch : Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration. 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. editor / Ismail Khalil ; Matthias Steinbauer ; Liming Chen ; Gabriele Anderst-Kotsis. Association for Computing Machinery, Inc, 2015. pp. 108-116 (13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings).
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abstract = "Mobile devices have become an integral part of our routine activities. Some of the activities involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.). These mobile electronic services (e-Services) typically require a method to securely identify and authenticate a claimed identity. Currently, e-Services typically use a knowledgebased authentication method by demonstrating the knowledge of secret (e.g. password), but it is vulnerable to a number of security attacks, e.g. shoulder spoofing and brute force attacks. To thwart the attacks and to make the authentication method more secure, this paper describes our efforts in investigating the benefits of integrating touch dynamics biometrics, into a PIN-based authentication method. It reports the collection of a comprehensive reference dataset from 150 subjects, the extraction of feature data from the dataset, and the classifications and the use of the feature data to identify a user. Experimental results show that, even when the PIN is exposed, 9 out of 10 impersonation attempts can be successfully detected.",
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The, PS, Zhang, N, Teoh, ABJ & Chen, K 2015, Recognizing Your Touch: Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration. in I Khalil, M Steinbauer, L Chen & G Anderst-Kotsis (eds), 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings, Association for Computing Machinery, Inc, pp. 108-116, 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015, Brussels, Belgium, 15/12/11. https://doi.org/10.1145/2837126.2837127

Recognizing Your Touch : Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration. / The, Pin Shen; Zhang, Ning; Teoh, Andrew Beng Jin; Chen, Ke.

13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. ed. / Ismail Khalil; Matthias Steinbauer; Liming Chen; Gabriele Anderst-Kotsis. Association for Computing Machinery, Inc, 2015. p. 108-116 (13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings).

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

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AU - Zhang, Ning

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N2 - Mobile devices have become an integral part of our routine activities. Some of the activities involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.). These mobile electronic services (e-Services) typically require a method to securely identify and authenticate a claimed identity. Currently, e-Services typically use a knowledgebased authentication method by demonstrating the knowledge of secret (e.g. password), but it is vulnerable to a number of security attacks, e.g. shoulder spoofing and brute force attacks. To thwart the attacks and to make the authentication method more secure, this paper describes our efforts in investigating the benefits of integrating touch dynamics biometrics, into a PIN-based authentication method. It reports the collection of a comprehensive reference dataset from 150 subjects, the extraction of feature data from the dataset, and the classifications and the use of the feature data to identify a user. Experimental results show that, even when the PIN is exposed, 9 out of 10 impersonation attempts can be successfully detected.

AB - Mobile devices have become an integral part of our routine activities. Some of the activities involve the storage or access of sensitive data (e.g. on-line banking, paperless prescription services, etc.). These mobile electronic services (e-Services) typically require a method to securely identify and authenticate a claimed identity. Currently, e-Services typically use a knowledgebased authentication method by demonstrating the knowledge of secret (e.g. password), but it is vulnerable to a number of security attacks, e.g. shoulder spoofing and brute force attacks. To thwart the attacks and to make the authentication method more secure, this paper describes our efforts in investigating the benefits of integrating touch dynamics biometrics, into a PIN-based authentication method. It reports the collection of a comprehensive reference dataset from 150 subjects, the extraction of feature data from the dataset, and the classifications and the use of the feature data to identify a user. Experimental results show that, even when the PIN is exposed, 9 out of 10 impersonation attempts can be successfully detected.

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The PS, Zhang N, Teoh ABJ, Chen K. Recognizing Your Touch: Towards Strengthening Mobile Device Authentication via Touch Dynamics Integration. In Khalil I, Steinbauer M, Chen L, Anderst-Kotsis G, editors, 13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings. Association for Computing Machinery, Inc. 2015. p. 108-116. (13th International Conference on Advances in Mobile Computing and Multimedia, MoMM 2015 - Proceedings). https://doi.org/10.1145/2837126.2837127