@article{MAKHILLIJSC20127421084,
    title = {Keystroke Dynamics: A Met Heuristic Approach},
    journal = {International Journal of Soft Computing},
    volume = {7},
    number = {4},
    pages = {169-180},
    year = {2012},
    issn = {1816-9503},
    doi = {ijscomp.2012.169.180},
    url = {https://makhillpublications.co/view-article.php?issn=1816-9503&doi=ijscomp.2012.169.180},
    author = {M.,R.P. and},
    keywords = {Feature extraction,feature subset selection,mean and standard deviation,Ant Colony Optimization Algorithm (ACO)},
    abstract = {The need to secure sensitive data and computer systems from 
  intruders while allowing ease of access for authenticates users is one of the 
  main problems in computer security. Traditionally, passwords have been the usual 
  method for controlling access to computer systems but this approach has many 
  inherent flaws. Keystroke dynamics is a relatively new method of biometric identification 
  and provides a comparatively inexpensive and low profile method of hardening 
  the normal login and password process. This study presents the feature subset 
  selection in Keystroke dynamics for identity verification and it reports the 
  results of experimenting Ant Colony Optimization (ACO) technique on keystroke 
  duration, latency and digraph for feature subset selection. Here, the Ant Colony 
  Optimization is used to reduce the redundant feature values and minimize the 
  search space. Optimum feature subset is obtained using keystroke duration values 
  when compared with the other two feature values.}
    }