Browse

A hybrid novelty score and its use in keystroke dynamics-based user authentication

Cited 12 time in Web of Science Cited 16 time in Scopus
Authors
Kang, Pilsung; Cho, Sungzoon
Issue Date
2009-11-01
Publisher
ELSEVIER SCI LTD
Citation
PATTERN RECOGNITION; Vol.42 11; 3115-3127
Keywords
Novelty detectionIncremental learningKeystroke dynamics-based user authenticationNearest-neighbor learningTopological relation
Abstract
The purpose of novelty detection is to detect (novel) patterns that are not generated by the identical distribution of the normal class. A distance-based novelty detector classifies a new data pattern as "novel" if its distance from "normal" patterns is large. It is intuitive, easy to implement, and fits naturally With incremental learning. Its performance is limited, however, because it relies only on distance. In this paper, we propose considering topological relations as well. We compare our proposed method with 13 other novelty detectors based on 21 benchmark data sets from two sources. We then apply our method to a real-world application in which incremental learning is necessary: keystroke dynamics-based user authentication. The experimental results are promising. Not only does our method improve the performance of distance-based novelty detectors, but it also outperforms the other non-distance-based algorithms. Our method also allows efficient model updates. (C) 2009 Elsevier Ltd. All rights reserved.
ISSN
0031-3203
Language
English
URI
http://hdl.handle.net/10371/75357
DOI
https://doi.org/10.1016/j.patcog.2009.04.009
Files in This Item:
There are no files associated with this item.
Appears in Collections:
College of Engineering/Engineering Practice School (공과대학/대학원)Dept. of Industrial Engineering (산업공학과)Journal Papers (저널논문_산업공학과)
  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse