On Continuous User Authentication via Hidden Free-Text Based Monitoring; Advances in Intelligent Systems and Computing; Vol. 875 : Intelligent Information Technologies for Industry (IITI’18)

Библиографические подробности
Источник:Advances in Intelligent Systems and Computing
Vol. 875 : Intelligent Information Technologies for Industry (IITI’18).— 2018.— [P. 66-75]
Главный автор: Kochegurova E. A. Elena Alekseevna
Автор-организация: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Другие авторы: Luneva E. E. Elena Evgenievna, Gorokhova E. S. Ekaterina Sergeevna
Примечания:Title screen
This paper investigates the stages and specific features of continuous user authentication by hidden monitoring of keystroke dynamics when creating a free text. The stages include extraction of informative characteristics of keyboard rhythm, creation and update of user profiles and identification of efficiency criteria. A software application was developed for the project. The authors further analyzed existing algorithms for user identification based in metric distances. Previously proved features of keystroke dynamics were scaled with regard to frequency of use of Russian and English letters in free texts.
Режим доступа: по договору с организацией-держателем ресурса
Язык:английский
Опубликовано: 2018
Серии:Advances in Intelligent Systems and Computing book series
Предметы:
Online-ссылка:https://doi.org/10.1007/978-3-030-01821-4_8
Формат: Электронный ресурс Статья
Запись в KOHA:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=659708
Описание
Примечания:Title screen
This paper investigates the stages and specific features of continuous user authentication by hidden monitoring of keystroke dynamics when creating a free text. The stages include extraction of informative characteristics of keyboard rhythm, creation and update of user profiles and identification of efficiency criteria. A software application was developed for the project. The authors further analyzed existing algorithms for user identification based in metric distances. Previously proved features of keystroke dynamics were scaled with regard to frequency of use of Russian and English letters in free texts.
Режим доступа: по договору с организацией-держателем ресурса
DOI:10.1007/978-3-030-01821-4_8