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Human-Computer Interaction

  • Benjamin S. RigganEmail author
  • Wesley E. Snyder
  • Cliff Wang
Chapter
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Abstract

The main objective of this chapter is to summarize the authors’ recent work which studied the human-computer interaction for sketch-based passwords. However, before discussing the previous results, the features used specifically for implementation of SKS are discussed, and an overview of the database used for the HCI study (and some experiments and results in the subsequent chapter) is provided. The features used for the application of sketch-based passwords incorporates four fundamental properties: (1) shape, (2) direction, (3) order, and (4) pressure, which comprise a local 5D feature descriptor at every sketch sample point. The database used for this HCI study was constructed by the authors in (Riggan et al., A human factors study of graphical passwords using biometrics. Proc. of the 36th German Conf. on Pattern Recognition, 2014). This database considers a sufficiently large and complete set of users and many variations of sketch-based passwords. The previous HCI is useful to understand the connection between human perception and certain similarity measures, specifically for sketch-based authentication.

Keywords

BioSketch database HCI Variability analysis 

References

  1. 1.
    P. K. Agarwal, H. K. Avraham, H. Kaplan, and M. Sharir. Computing the discrete freéchet distance in subquadratic time. Proc. of the 24th Annual ACM-SIAM Symposium on Discrete Algorithms, pages 156–167, 2013.Google Scholar
  2. 2.
    H. Alt and H. Godau. Computing the fréchet distance between two polygonal curves. Int’l Journal of Computational Geometry and Applications, 5(1–2):75–91, 1995.CrossRefzbMATHMathSciNetGoogle Scholar
  3. 3.
    M. Martinez-Diaz, J. Fierrez, C. Martin-Diaz, and J. Ortega-Garcia. DooDB: A Graphical Password Database Containing Doodles and Pseudo-Signatures. 12th Int’l. Conf. on Frontiers in Handwriting Recognition, pages 339–344, 2010.Google Scholar
  4. 4.
    M. Martinez-Diaz, J. Fierrez, and J. Galbally. The DooDB Graphical Password Database: Data Analysis and Benchmark Results. IEEE Access, 1:596–605, 2013.CrossRefGoogle Scholar
  5. 5.
    B. S. Riggan, W. E. Snyder, X. Wang, and J Feng. A human factors study of graphical passwords using biometrics. Proc. of the 36th German Conf. on Pattern Recognition, 2014.Google Scholar
  6. 6.
    B. S. Riggan, W. E. Snyder, X. Wang, and L. K. Norris. A sketch-based authentication system with biometrics: security and usability analysis. Pattern Recognition (Under Review), 2014.Google Scholar

Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Benjamin S. Riggan
    • 1
    Email author
  • Wesley E. Snyder
    • 1
  • Cliff Wang
    • 2
  1. 1.Department of Electrical and Computer EngineeringNorth Carolina State UniversityRaleighUSA
  2. 2.US Army Research OfficeDurhamUSA

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