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Personal Identification Based on Mobile-Based Keystroke Dynamics

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018 (AISI 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 845))

Abstract

This paper is addressing the personal identification problem by using mobile-based keystroke dynamics of touch mobile phone. The proposed approach consists of two main phases, namely feature selection and classification. The most important features are selected using Genetic Algorithm (GA). Moreover, Bagging classifier used the selected features to identify persons by matching the features of the unknown person with the labeled features. The outputs of all Bagging classifiers are fused to determine the final decision. In this experiment, a keystroke dynamics database for touch mobile phones is used. The database, which consists of four sets of features, is collected from 51 individuals and consists of 985 samples collected from males and females with different ages. The results of the proposed model conclude that the third subset of features achieved the best accuracy while the second subset achieved the worst accuracy. Moreover, the fusion of all classifiers of all ensembles will improve the accuracy and achieved results better than the individual classifiers and individual ensembles.

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Author information

Authors and Affiliations

  1. Faculty of Engineering, Suez Canal University, Ismailia, Egypt

    Alaa Tharwat

  2. Faculty of Computer Science and Engineering, Frankfurt University of Applied Sciences, 60318, Frankfurt am Main, Germany

    Alaa Tharwat

  3. Faculty of Engineering, Mansoura University, Mansoura, Egypt

    Abdelhameed Ibrahim

  4. Faculty of Computers and Informatics, Suez Canal University, Ismailia, Egypt

    Tarek Gaber

  5. Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  6. Scientific Research Group in Egypt (SRGE), Giza, Egypt

    Alaa Tharwat, Abdelhameed Ibrahim, Tarek Gaber & Aboul Ella Hassanien

Authors
  1. Alaa Tharwat
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  2. Abdelhameed Ibrahim
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  3. Tarek Gaber
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  4. Aboul Ella Hassanien
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Corresponding author

Correspondence to Alaa Tharwat .

Editor information

Editors and Affiliations

  1. Information Technology Department, Faculty of Computers and Information, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. Ain Shams University, Cairo, Egypt

    Mohamed F. Tolba

  3. Dubai International Academic City, The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  4. Faculty of Computers and Information, Benha University, Benha, Egypt

    Ahmad Taher Azar

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Tharwat, A., Ibrahim, A., Gaber, T., Hassanien, A.E. (2019). Personal Identification Based on Mobile-Based Keystroke Dynamics. In: Hassanien, A., Tolba, M., Shaalan, K., Azar, A. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2018. AISI 2018. Advances in Intelligent Systems and Computing, vol 845. Springer, Cham. https://doi.org/10.1007/978-3-319-99010-1_42

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