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User Authentication from Mouse Movement Data Using Multiple Classifiers

Published: 24 February 2017 Publication History

Abstract

The biometric authentication is becoming very familiar due to its unique characteristics. This paper presents a user authentication system using mouse movement data. The mouse movement data are captured using an existing tool named Jitbit macro recorder. The acquired data are preprocessed and sampled into N blocks based on specific number of actions and stored in database. From each block twelve features are generated: Number of Points in the trajectory, Delay Time, Number of Delay, Number of Action, STDEV of Trajectory Length, Total Length of Trajectory, STDEV of Slope, STDEV of Slope to Slope Difference, Number of Curvatures, Curvature of Trajectory, Number of Changes in Horizontal Position and Number of Changes in Vertical Position. This system uses three separate classifiers: SVM, K-Nearest Neighbor and Naive Bayes to recognize the user. The system is trained and tested using a benchmark data. The experimental result shows that K-nearest Neighbor has the lowest error rate.

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Cited By

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  • (2024)Support vector machine analysis in mouse dynamic authentication classificationPROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON GREEN CIVIL AND ENVIRONMENTAL ENGINEERING (GCEE 2023)10.1063/5.0193407(060024)Online publication date: 2024
  • (2023)User Classification Based On Mouse Dynamic Authentication Using K-Nearest NeighborMakara Journal of Technology10.7454/mst.v27i1.155727:1(33-40)Online publication date: 28-Apr-2023
  • (2022)EMPIRICAL EVALUATION OF MACHINE LEARNING METHODS IN ONLINE AUTHENTICATION PROBLEMSVestnik komp'iuternykh i informatsionnykh tekhnologii10.14489/vkit.2022.08.pp.049-057(49-57)Online publication date: Aug-2022
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cover image ACM Other conferences
ICMLC '17: Proceedings of the 9th International Conference on Machine Learning and Computing
February 2017
545 pages
ISBN:9781450348171
DOI:10.1145/3055635
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]

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  • Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 February 2017

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Author Tags

  1. Biometric system
  2. Naive Bayes
  3. SVM
  4. behavioral authentication
  5. k nearest neighbor
  6. mouse dynamic
  7. verification

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  • Refereed limited

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Cited By

View all
  • (2024)Support vector machine analysis in mouse dynamic authentication classificationPROCEEDINGS OF THE 4TH INTERNATIONAL CONFERENCE ON GREEN CIVIL AND ENVIRONMENTAL ENGINEERING (GCEE 2023)10.1063/5.0193407(060024)Online publication date: 2024
  • (2023)User Classification Based On Mouse Dynamic Authentication Using K-Nearest NeighborMakara Journal of Technology10.7454/mst.v27i1.155727:1(33-40)Online publication date: 28-Apr-2023
  • (2022)EMPIRICAL EVALUATION OF MACHINE LEARNING METHODS IN ONLINE AUTHENTICATION PROBLEMSVestnik komp'iuternykh i informatsionnykh tekhnologii10.14489/vkit.2022.08.pp.049-057(49-57)Online publication date: Aug-2022
  • (2021)An Efficient Man-Machine Recognition Method Based On Mouse Trajectory Feature De-redundancyProceedings of the 37th Annual Computer Security Applications Conference10.1145/3485832.3485895(365-374)Online publication date: 6-Dec-2021
  • (2021)Identifying User Authentication and Most Frequently Used Region Based on Mouse Movement Data: A Machine Learning Approach2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)10.1109/CCWC51732.2021.9376087(1245-1250)Online publication date: 27-Jan-2021
  • (2019)State of the art and perspectives on traditional and emerging biometricsSecurity and Privacy10.1002/spy2.441:6Online publication date: 1-Jan-2019
  • (2018)Implementation and user testing of personal authentication having shoulder surfing resistance with mouse operationsIEICE Communications Express10.1587/comex.2017XBL01707:3(77-82)Online publication date: 2018
  • (2018)Evaluation of Mouse Operation Authentication Method Having Shoulder Surfing ResistanceAdvances in Internet, Data & Web Technologies10.1007/978-3-319-75928-9_90(978-989)Online publication date: 24-Feb-2018

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