Optimum Feature Selection Using Firefly Algorithm for Keystroke Dynamics

  • Akila Muthuramalingam
  • Jenifa Gnanamanickam
  • Ramzan Muhammad
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 736)

Abstract

Keystroke dynamics, an automated method and promising biometric technique, is used to recognize an individual, based on an analysis of user’s typing patterns. The processing steps involved in keystroke dynamics are data collection, feature extraction and feature selection. Initially the statistical measures of feature characteristics like latency, duration and digraph are computed during feature extraction. Various advanced optimization techniques are applied by researchers to mimic the behavioral pattern of key stroke dynamics. In this study, Firefly algorithm (FA) is proposed for feature selection. The performance efficiency of FA is computed and compared with existing techniques and found that the convergence rate and iteration generations to reach the optimum solution is 41% and 18% less respectively, as compared to those by other algorithms.

Keywords

Keystroke dynamics Duration Latency Digraph Feature extraction Feature selection Firefly algorithm 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Akila Muthuramalingam
    • 3
  • Jenifa Gnanamanickam
    • 1
  • Ramzan Muhammad
    • 2
  1. 1.KPR Institute of Engineering and TechnologyCoimbatoreIndia
  2. 2.Maulana Mukhtar Ahmad Nadvi Technical CampusMalegaon, NashikIndia
  3. 3.PGP College of Engineering and TechnologyNamakkalIndia

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