Mini-Batch Ensemble Method on Keystroke Dynamics based User Authentication

  • Ho, Jiacang (Department of Ubiquitous IT, Graduate School, Dongseo University) ;
  • Kang, Dae-Ki (Department of Computer & Information Engineering, Dongseo University)
  • Received : 2016.07.17
  • Accepted : 2016.08.05
  • Published : 2016.09.30


The internet allows the information to flow at anywhere in anytime easily. Unfortunately, the network also becomes a great tool for the criminals to operate cybercrimes such as identity theft. To prevent the issue, using a very complex password is not a very encouraging method. Alternatively, keystroke dynamics helps the user to solve the problem. Keystroke dynamics is the information of timing details when a user presses a key or releases a key. A machine can learn a user typing behavior from the information integrate with a proper machine learning algorithm. In this paper, we have proposed mini-batch ensemble (MIBE) method which does the preprocessing on the original dataset and then produces multiple mini batches in the end. The mini batches are then trained by a machine learning algorithm. From the experimental result, we have shown the improvement of the performance for each base algorithm.


Supported by : National Research Foundation of Korea (NRF)


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