LAMARCKIAN EVOLUTION OF NEURAL NETWORKS APPLIED TO KEYSTROKE DYNAMICS

Paulo Henrique Pisani, Silvio do Lago Pereira

2010

Abstract

The pace of computing and communications development has contributed to an increased data exposure and, consequently, to the rise of an issue known as identity theft. By applying user profiling, which analyzes the user behavior in order to perform a continuous authentication, protection of digital identities can be enhanced. Among the possible features to be analyzed, this paper focuses on keystroke dynamics, something that cannot be easily stolen. As keystroke dynamics involves dealing with noisy data, it was chosen a neural network to perform the pattern recognition task. However, traditional neural network training algorithms are bound to get trapped in local minimum, reducing the learning ability. This work draws a comparison between backpropagation and two hybrid approaches based on evolutionary training, for the task of keystroke dynamics. Differently from most evolutionary algorithms based on Darwinism, this work also studies Lamarckian evolutionary algorithms that, although not being biologically plausible, attained promising results in the tests.

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Paper Citation


in Harvard Style

Pisani P. and do Lago Pereira S. (2010). LAMARCKIAN EVOLUTION OF NEURAL NETWORKS APPLIED TO KEYSTROKE DYNAMICS . In Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010) ISBN 978-989-8425-31-7, pages 358-364. DOI: 10.5220/0003084503580364


in Bibtex Style

@conference{icec10,
author={Paulo Henrique Pisani and Silvio do Lago Pereira},
title={LAMARCKIAN EVOLUTION OF NEURAL NETWORKS APPLIED TO KEYSTROKE DYNAMICS},
booktitle={Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)},
year={2010},
pages={358-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003084503580364},
isbn={978-989-8425-31-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Evolutionary Computation - Volume 1: ICEC, (IJCCI 2010)
TI - LAMARCKIAN EVOLUTION OF NEURAL NETWORKS APPLIED TO KEYSTROKE DYNAMICS
SN - 978-989-8425-31-7
AU - Pisani P.
AU - do Lago Pereira S.
PY - 2010
SP - 358
EP - 364
DO - 10.5220/0003084503580364