|
ИСТИНА |
Войти в систему Регистрация |
Интеллектуальная Система Тематического Исследования НАукометрических данных |
||
One-Class Models for Continuous Authentication Based on Keystroke Dynamicsстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 15 ноября 2018 г.
- Авторы: Maria Kazachuk, Alexander Kovalchuk, Igor Mashechkin, Igor Orpanen, Mikhail Petrovskiy, Ivan Popov, Roman Zakliakov
- Журнал: Lecture Notes in Computer Science
- Том: 9937
- Год издания: 2016
- Первая страница: 416
- Последняя страница: 425
- DOI: 10.1007/978-3-319-46257-8
- Аннотация: In this paper we discuss an applied problem of continuous user authentication based on keystroke dynamics. It is important for a user model to discover new intruders. That means we don’t have the keystroke samples of such intruders on the training phase. It leads us to the necessity of using one-class models. In the paper we review some popular feature extraction, preprocessing and one-class classification methods for this problem. We propose a new approach to reduce dimensionality of a feature space based on two-sample Kolmogorov-Smirnov test and investigate how the quantile-based discretization technique can improve the one-class models’ performance. We present two algorithms, which have not been used for keystroke dynamics before: Fuzzy kernel-based classifier and Random Forest Regression classifier. We conduct experimental evaluation of the proposed approach.
- Добавил в систему: Петровский Михаил Игоревич