Investigation of touch-based user authentication features using android smartphone

Ala Abdulhakim Alariki; Azizah Abdul Manaf

doi:10.1007/978-3-319-13461-1_14

Investigation of touch-based user authentication features using android smartphone

Ala Abdulhakim Alariki, Azizah Abdul Manaf

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

1 Citation (Scopus)

Abstract

Currently most mobile phones use touch screen, In addition the behavior of user's touch gesture is significantly important in interaction with the phone. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on this touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the Android operation system. Several touch dynamics features are examined to explore the efficiency of feature and each category (similar processing and representation form). Also, the impact of normalization and seven feature selection algorithms are examined. After applying Exhaustive Search reduction technique to the observation vectors composed of all 12 extracted features, nine features are retained.

Original language	English
Title of host publication	Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings
Editors	Aboul Ella Hassanien, Mohamed Fahmy Tolba, Ahmad Taher Azar
Place of Publication	Switzerland
Publisher	Springer
Pages	135-144
Number of pages	10
ISBN (Electronic)	9783319134611
ISBN (Print)	9783319134604
DOIs	https://doi.org/10.1007/978-3-319-13461-1_14
Publication status	Published - 2014
Externally published	Yes
Event	International Conference on Advanced Machine Learning Technologies and Applications - Cairo, Egypt Duration: 28 Nov 2014 → 30 Nov 2014 Conference number: 2nd

Publication series

Name	Communications in Computer and Information Science
Volume	488
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	International Conference on Advanced Machine Learning Technologies and Applications
Abbreviated title	AMLTA
Country/Territory	Egypt
City	Cairo
Period	28/11/14 → 30/11/14

Keywords

Android
Touch gesture authentication
User authentication

Access to Document

10.1007/978-3-319-13461-1_14

Cite this

Alariki, A. A., & Manaf, A. A. (2014). Investigation of touch-based user authentication features using android smartphone. In A. E. Hassanien, M. F. Tolba, & A. T. Azar (Eds.), Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings (pp. 135-144). (Communications in Computer and Information Science; Vol. 488). Springer. https://doi.org/10.1007/978-3-319-13461-1_14

Alariki, Ala Abdulhakim ; Manaf, Azizah Abdul. / Investigation of touch-based user authentication features using android smartphone. Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings. editor / Aboul Ella Hassanien ; Mohamed Fahmy Tolba ; Ahmad Taher Azar. Switzerland : Springer, 2014. pp. 135-144 (Communications in Computer and Information Science).

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title = "Investigation of touch-based user authentication features using android smartphone",

abstract = "Currently most mobile phones use touch screen, In addition the behavior of user's touch gesture is significantly important in interaction with the phone. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on this touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the Android operation system. Several touch dynamics features are examined to explore the efficiency of feature and each category (similar processing and representation form). Also, the impact of normalization and seven feature selection algorithms are examined. After applying Exhaustive Search reduction technique to the observation vectors composed of all 12 extracted features, nine features are retained.",

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booktitle = "Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings",

note = "International Conference on Advanced Machine Learning Technologies and Applications, AMLTA ; Conference date: 28-11-2014 Through 30-11-2014",

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Alariki, AA & Manaf, AA 2014, Investigation of touch-based user authentication features using android smartphone. in AE Hassanien, MF Tolba & AT Azar (eds), Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings. Communications in Computer and Information Science, vol. 488, Springer, Switzerland, pp. 135-144, International Conference on Advanced Machine Learning Technologies and Applications, Cairo, Egypt, 28/11/14. https://doi.org/10.1007/978-3-319-13461-1_14

Investigation of touch-based user authentication features using android smartphone. / Alariki, Ala Abdulhakim; Manaf, Azizah Abdul.
Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings. ed. / Aboul Ella Hassanien; Mohamed Fahmy Tolba; Ahmad Taher Azar. Switzerland: Springer, 2014. p. 135-144 (Communications in Computer and Information Science; Vol. 488).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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AU - Alariki, Ala Abdulhakim

AU - Manaf, Azizah Abdul

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N2 - Currently most mobile phones use touch screen, In addition the behavior of user's touch gesture is significantly important in interaction with the phone. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on this touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the Android operation system. Several touch dynamics features are examined to explore the efficiency of feature and each category (similar processing and representation form). Also, the impact of normalization and seven feature selection algorithms are examined. After applying Exhaustive Search reduction technique to the observation vectors composed of all 12 extracted features, nine features are retained.

AB - Currently most mobile phones use touch screen, In addition the behavior of user's touch gesture is significantly important in interaction with the phone. Due to increasing demand for safer access in touch screen mobile phones, old strategies like pins, tokens, or passwords have failed to stay abreast of the challenges. However, we study user authentication scheme based on this touch dynamics features for accurate user authentication. We developed the software needed to collect readings from touch screen of mobile phone running the Android operation system. Several touch dynamics features are examined to explore the efficiency of feature and each category (similar processing and representation form). Also, the impact of normalization and seven feature selection algorithms are examined. After applying Exhaustive Search reduction technique to the observation vectors composed of all 12 extracted features, nine features are retained.

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Alariki AA, Manaf AA. Investigation of touch-based user authentication features using android smartphone. In Hassanien AE, Tolba MF, Azar AT, editors, Advanced Machine Learning Technologies and Applications: Second International Conference, AMLTA 2014, Proceedings. Switzerland: Springer. 2014. p. 135-144. (Communications in Computer and Information Science). doi: 10.1007/978-3-319-13461-1_14

Investigation of touch-based user authentication features using android smartphone

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Keywords

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