TITLE

Multimodel Biometric Authentication Based on Finger Print and Keystroke Dynamics Using Fuzzy Set

AUTHOR(S)
Chandrasekar, V.; Shanmugavalli, V.; Sankar, P. Krishna
PUB. DATE
May 2014
SOURCE
Australian Journal of Basic & Applied Sciences;May2014, Vol. 8 Issue 7, p99
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background:Biometrics is providing more security since it is used to uniquely identify individuals by their physical characteristics or personal behavior traits. Proposed approach is a multimodal biometric authentication system, since it is based on physical and behavioral characteristics. We are using keystroke dynamics as behavioral traits and used fuzzy set approach for classification. Advantage of this approach is not using the sharp cut off values of user password entry timing information instead it is using the Minimum and Maximum range values time as keystroke feature. Objective: To provide user authentication based on Keystroke dynamics by using fuzzy set approach in order to avoid unauthorized user access of the system. Results:We have used duration and latency time as keystroke features and fuzzy set approach is used for classification. By using this approach will reduce the error rate for incorrectly identifying the wrong user. Based on this approach the accuracy level will be improved. Conclusion: We have proposed a novel approach for user authentication based on Fingerprint, User login credential, and keystroke dynamics of password entry. The security will be more accurate than the existing system because we are implementing three way securities. Proposed system is based on two phases they are Enrollment and Verification for Finger prints and Keystroke dynamics So that we can collect the data samples easily and verify particular user with an effective manner.
ACCESSION #
96583857

 

Related Articles

  • Preface. Yu Zhong; Yunbin Deng // Gate to Computer Science & Research;2015, Vol. 2, piii 

    An introduction is presented in which the editor discusses topics within the issue including behavioral biometrics for user authentication, survey of datasets regarding keystroke dynamics and importance of ubiquitous mobile devices.

  • Correlation Keystroke Verification Scheme for User Access Control in Cloud Computing Environment. Xi, Kai; Tang, Yan; Hu, Jiankun // Computer Journal;Oct2011, Vol. 54 Issue 10, p1632 

    Cloud security is a major concern that may delay its widespread adoption. User access control (UAC) is the core component of security in cloud computing environment, aiming to ensure that stored data are allowed to be accessed only by authenticated/authorized users. As a typical behavioural...

  • A Study on Recent Advancements in Bio-Metric Identity Verification. Sandhya, V.; Archana, M.; Leela, Sai; Kumar R., Sampath // International Journal of Advanced Research in Computer Science;Apr2014 Special Issue, Vol. 5 Issue 4, p154 

    Security plays an important role in day to day life of a human being. Bio-Metric is the study of identification of persons based on his physical or behavioural characteristic. The different methods for verifying identity of a person ranges from finger prints to heart beats. The input taken from...

  • Dynamic Free Text Keystroke Biometrics System for Simultaneous Authentication and Adaptation to User's Typing Pattern. King, Alex; Wahjudi, Paulus // Journal of Management & Engineering Integration;Winter2013, Vol. 6 Issue 2, p86 

    This paper describes a new algorithm for free text keystroke authentication and its implementation. Recent research describes an implementation of the Scaled Manhattan distance for continuous authentication. This paper expands upon that research by describing a modified method for keystroke...

  • Scan-Based Evaluation of Continuous Keystroke Authentication Systems. Serwadda, Abdul; Wang, Zibo; Koch, Patrick; Govindarajan, Sathya; Pokala, Raviteja; Goodkind, Adam; Brizan, David-Guy; Rosenberg, Andrew; Phoha, Vir V.; Balagani, Kiran // IT Professional;Jul/Aug2013, Vol. 15 Issue 4, p20 

    For biometric modalities in which error rates are typically high--including behavioral biometrics, such as keystroke dynamics--temporal information associated with the occurrence of errors might help answer questions regarding performance evaluation.

  • Capturing Cognitive Fingerprints from Keystroke Dynamics. Chang, J. Morris; Fang, Chi-Chen; Ho, Kuan-Hsing; Kelly, Norene; Wu, Pei-Yuan; Ding, Yixiao; Chu, Chris; Gilbert, Stephen; Kamal, Amed E.; Kung, Sun-Yuan // IT Professional;Jul/Aug2013, Vol. 15 Issue 4, p24 

    Conventional authentication systems identify a user only at the entry point. Keystroke dynamics can continuously authenticate users by their typing rhythms without extra devices. This article presents a new feature called cognitive typing rhythm (CTR) to continuously verify the identities of...

  • Authenticating mobile phone users using keystroke analysis. Clarke, N.; Furnell, S. // International Journal of Information Security;Jan2007, Vol. 6 Issue 1, p1 

    Mobile handsets have found an important place in modern society, with hundreds of millions currently in use. The majority of these devices use inherently weak authentication mechanisms, based upon passwords and PINs. This paper presents a feasibility study into a biometric-based technique, known...

  • Intention to Use Biometric Systems. Ngugi, Benjamin; Kamis, Arnold; Tremaine, Marilyn // e-Service Journal;Summer2011, Vol. 7 Issue 3, p20 

    This study set out to investigate the critical factors that determine user intention to use a biometric system. We integrated previous research in the technology acceptance and biometric engineering literatures and identified six important factors: Perceived System Security, Perceived False...

  • A Novel Approach for Keyboard Dynamics Authentication based on Fusion of Stochastic Classifiers. Rezaei, A.; Mirzakochaki, S. // International Journal of Computer Science & Network Security;Aug2012, Vol. 12 Issue 8, p60 

    Computer security is one of most important issues around the world. Most computer systems are using passwords for their own authentication or verification mechanisms. A robust and efficacious approach for classification of 24 persons who their typing patterns were collected introduced. A linear...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics