Skip to main content

Keystroke Dynamics for User Verification

  • Conference paper
  • First Online:
Evolutionary Computing and Mobile Sustainable Networks

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 53))

  • 1042 Accesses

Abstract

With the evolution of internet, the dependency of humans on them has increased. This has led to an increase in attacks, forgery, impersonation and so on, which require that a user and his privacy be maintained. Thus the need to protect a user has increased intensifying protection, authentication and verification methods of a user. There are many methods of authenticating a user, which include traditional methods of authentication such as passwords, personal identification numbers and so on, However, these methods have their drawbacks and hence biometrics have replaced these methods in some cases and in some cases biometrics has turned out be an additional layer of security, therefore providing better security. In this paper we propose one of the behavioral methods of biometric authentication called keystroke dynamics which uses a user’s typing rhythm to verify a user. One of the most common examples of this method is the verification of user using CAPTCHA, where the user is asked to type the letters to be verified as a genuine user and thus the user’s typing rhythm is captured based on which a match is generated and the user is verified. This method is most commonly used in applications such as online banking, email verifications and other such areas. This method acts as an additional layer of security to an existing system and helps protect the sensitive information of the user.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Killourhy KS, Maxion RA (2009) Comparing anomaly-detection algorithms for keystroke dynamics. In: 2009 IEEE/IFIP International conference on dependable systems & networks. https://doi.org/10.1109/dsn.2009.5270346

  2. Sulavko AE, Eremenko AV, Fedotov AA (2017) Users’ identification through keystroke dynamics based on vibration parameters and keyboard pressure. In: 2017 IEEE dynamics of systems, mechanisms and machines (dynamics) (Omsk, Russia) 14 Nov–16. https://doi.org/10.1109/dynamics.2017.8239514

  3. Abdullah A, Frans C, Danushka B (2016) Towards keystroke continuous authentication using time series analytics, Springer International Publishing AG 2016 M. Bramer and M. Petridis (eds.), Research and Development in Intelligent Systems XXXIII, https://doi.org/10.1007/978-3-319-47175-4_24

  4. SoumenRoy,Utpal Roy, D. D. Sinha, September 2014. Enhanced Knowledge- Based User Authentication Technique via Keystroke Dynamics. International Journal of Engineering Science Invention ISSN (Online): 2319 – 6734, ISSN (Print): 2319 – 6726 www.ijesi.org Volume 3 Issue 9 ǁ September 2014 ǁ PP.41–48.33

  5. Lu X, Zhang S, Yi S (2018) Continuous authentication by free-text keystroke based on CNN plus RNN. In: 2018 International Conference on Identification, Information and Knowledge in the Internet of Things, IIKI 2018, 147, pp 314–318, https://doi.org/10.1016/j.procs.2019.01.270

  6. Venugopalan S, Juefei-Xu F, Cowley B, Savvides M (2015) Electromyograph and keystroke dynamics for spoof-resistant biometric authentication. In: 2015 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). https://doi.org/10.1109/cvprw.2015.7301326

  7. Saket M, Vikram P (2016) Mining keystroke timing pattern for user authentication, Springer International Publishing AG 2017 A. Appice et al. (Eds.): NFMCP 2016, LNAI 10312, pp 213–227. https://doi.org/10.1007/978-3-319-61461-814

  8. Obaidat MS, Macchairolo DT (1994) A multilayer neural network system for computer access security. IEEE Trans Syst Man Cybernet 24(5):806–813. https://doi.org/10.1109/21.293498

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ashwini Sridhar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sridhar, A., Mamatha, H.R. (2021). Keystroke Dynamics for User Verification. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 53. Springer, Singapore. https://doi.org/10.1007/978-981-15-5258-8_14

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-5258-8_14

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-5257-1

  • Online ISBN: 978-981-15-5258-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics