Keystroke Dynamics Authentication Using a Small Number of Samples

dc.contributor.authorČapek, Jan
dc.contributor.authorHub, Miloslav
dc.contributor.otherEkonomická fakultacs
dc.date.accessioned2020-11-25T08:54:55Z
dc.date.available2020-11-25T08:54:55Z
dc.description.abstractThe verification of a person’s identity is very important in today’s information society, especially in e-commerce systems and directly affects user account management and administration. Although present e-commerce systems use many modern sophisticated methods of authentication, large numbers of e-commerce systems use passwords for this purpose incessantly. However, passwords are not considered be too secure because users usually do not adhere to security policies for creating and managing theirs passwords. This problem can be solved by security policies that require the user to change the password frequently, select a completely new password, and structure the password, which places additional demands on the user. The solution is a two-factor authentication where a user needs to know the right password and at the same time, he must write this password in the correct way. Indeed, many different methods for keystroke dynamics authentication exist nowadays, but unfortunately, many of them need a large number of samples to create a stable template and therefore it is impossible use them in systems whose security policy requires frequent password change. The authors suggest a completely new method for these purposes that is enough stable even with a small number of measurements to create a template. This proposed method of keystroke dynamics authentication is validated and results are compared with existing methods both over the own dataset and the existing reference datasets. The authors believe that the proposed method will simplify the management and administration of user accounts as well as their security.en
dc.formattext
dc.identifier.doi10.15240/tul/001/2020-4-014
dc.identifier.eissn2336-5604
dc.identifier.issn1212-3609
dc.identifier.urihttps://dspace.tul.cz/handle/15240/158183
dc.language.isoen
dc.publisherTechnická Univerzita v Libercics
dc.publisherTechnical university of Liberec, Czech Republicen
dc.publisher.abbreviationTUL
dc.relation.isbasedonAllen, J. D. (2010). An analysis of pressure-based keystroke dynamics algorithms (Master Thesis). Dallas, TX: Southern Methodist University.
dc.relation.isbasedonBanerjee, S. P., & Woodard, D. L. (2012). Biometric Authentication and Identification Using Keystroke Dynamics: A Survey. Journal of Pattern Recognition Research, 7(1), 116–139. https://doi.org/10.13176/11.427
dc.relation.isbasedonBello, L., Bertacchini, M., Benitez, C., Pizzoni, J. C., & Cipriano, M. (2010). Collection and publication of a fixed text keystroke dynamics dataset. In XVI Congreso Argentino de Ciencias de la Computacion (CACIC 2010) (pp. 822–831). https://doi.org/10.13140/2.1.4572.4960
dc.relation.isbasedonBhatt, S., & Santhanam, T. (2013). Keystroke Dynamics for Biometric Authentication – A Survey. In Proceedings of the 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering (PRIME), February 21–22, 2013, Salem, India (pp. 17–23). https://doi.org/10.1109/ICPRIME.2013.6496441
dc.relation.isbasedonChang, T. Y. (2012). Dynamically generate a long-lived private key based on password keystroke features and neural network. Information Sciences, 211, 36–47. https://doi.org/10.1016/j.ins.2012.04.009
dc.relation.isbasedonGunetti, D., & Picardi, C. (2005). Keystroke Analysis of Free Text. ACM Transactions of Information and System Security, 8(3), 312–347. https://doi.org/10.1145/1085126.1085129
dc.relation.isbasedonHaller, N., Metz, C., Nesser, P., & Straw, M. (1998). A One-Time Password System. RFC 2289.
dc.relation.isbasedonHoque, N., Bhuyana, M. H., Baishyaa, R. C., Bhattacharyyaa, D. K., & Kalitab, J. K. (2014). Network attacks: Taxonomy, tools and systems. Journal of Network and Computer Applications, 40, 307–324. https://doi.org/10.1016/j.jnca.2013.08.001
dc.relation.isbasedonHub, M. (2003). Strategie výběru identifikačních znaků ve vícefaktorové autentizace. E&M Economics and Management, 6(4), 147–150.
dc.relation.isbasedonKang, P., & Cho, S. (2015). Keystroke dynamics-based user authentication using long and free text strings from various input devices. Information Sciences, 308, 72–93. https://doi.org/10.1016/j.ins.2014.08.070
dc.relation.isbasedonKanimozhi, M., & Kanimozhi, A. (2015). Implementing Neural Network in Keystroke Dynamics for a Better Biometric Authentication System. International Journal on Applications in Information and Communication Engineering, 1(3), 44–49.
dc.relation.isbasedonKarnan, M., & Akila, M. (2009). Personal Authentication Based on Keystroke Dynamics Using Ant Colony Optimization and Back Propagation Neural Network. International Journal of Communications, Network and System Sciences, 1(2).
dc.relation.isbasedonKarnan, M., & Akila, M. (2010). Personal Authentication based on Keystroke Dynamics using Soft Computing Techniques. In Second International Conference on Communication Software and Networks. Singapore, Singapore. https://doi.org/10.1109/ICCSN.2010.50
dc.relation.isbasedonKarnan, M., Akila, M., & Krishnaraj, N. (2011). Biometric personal authentication using keystroke dynamics: A review. Applied Soft Computing, 11(2), 1565–1573. https://doi.org/10.1016/j.asoc.2010.08.003
dc.relation.isbasedonKillourhy, K. S., & Maxion, R. A. (2009). Comparing Anomaly Detectors for Keystroke Dynamics. In Proceedings of the 39th Annual International Conference on Dependable Systems and Networks (DSN-2009) (pp. 125–134). Lisbon, Portugal. https://doi.org/10.1109/DSN.2009.5270346
dc.relation.isbasedonLegget, J., Williams, G., Usnick, M., & Longnecker, M. (1990). Dynamic identity verification via keystroke characteristics. International Journal of Man-Machine Studies, 35(6), 859–870. https://doi.org/10.1016/S0020-7373(05)80165-8
dc.relation.isbasedonLiu, C.-L., Tsai, C.-J., Chang, T.-Y., Tsa, W.-J., & Zhong, P.-K. (2015). Implementing multiple biometric features for a recall-based graphical keystroke dynamics authentication system on a smart phone. Journal of Network and Computer Applications, 53, 128–139. https://doi.org/10.1016/j.jnca.2015.03.006
dc.relation.isbasedonMatsubara, Y., Samura, T., & Nishimura, H. (2015). Keyboard Dependency of Personal Identification Performance by Keystroke Dynamics in Free Text Typing. Journal of Information Security, 6(3), 229–240. https://doi.org/10.4236/jis.2015.63023
dc.relation.isbasedonRoth, J., Liu, X., Ross, A., & Metaxas, D. (2013). Biometric Authentication via Keystroke Sound. In 2013 International Conference on Biometrics (ICB). Madrid, Spain. https://doi.org/10.1109/ICB.2013.6613015
dc.relation.isbasedonSoh, B., & Joy, A. (2003). A Novel Web Security Evaluation Model for a One-Time-Password System. In Proceedings of the IEEE/WIC International Conference on Web Intelligence (WI’03) (pp. 413–416).
dc.relation.isbasedonStallings, W. (2012). Network security essentials: Applications and standards. Upper Saddle River, NJ: Prentice Hall.
dc.relation.isbasedonTappert, C. C., Cha, S. H., Villani, M., & Zack, R. S. (2009). Keystroke Biometric System for Long-Text Input. International Journal of Information Security and Privacy, 4(1), 32–60. https://doi.org/10.4018/jisp.2010010103
dc.relation.isbasedonTeh, P. S., Beng Jin Teoh, A., & Yue, S. (2013). A Survey of Keystroke Dynamics Biometrics. The Scientific World Journal, 4, 408280. https://doi.org/10.1155/2013/408280
dc.relation.ispartofEkonomie a Managementcs
dc.relation.ispartofEconomics and Managementen
dc.relation.isrefereedtrue
dc.rightsCC BY-NC
dc.subjectaccount managementen
dc.subjectaccount administrationen
dc.subjectauthenticationen
dc.subjectbiometricen
dc.subjectkeystroke dynamicsen
dc.subjectpassworden
dc.subject.classificationC38
dc.subject.classificationC60
dc.subject.classificationC88
dc.titleKeystroke Dynamics Authentication Using a Small Number of Samplesen
dc.typeArticleen
local.accessopen
local.citation.epage226
local.citation.spage215
local.facultyFaculty of Economics
local.filenameEM_4_2020_14
local.fulltextyes
local.relation.abbreviationE+Mcs
local.relation.abbreviationE&Men
local.relation.issue4
local.relation.volume23
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
EM_4_2020_14.pdf
Size:
995.62 KB
Format:
Adobe Portable Document Format
Description:
článek
Collections