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)

Opis bibliograficzny
Parent link:Advances in Intelligent Systems and Computing
Vol. 875 : Intelligent Information Technologies for Industry (IITI’18).— 2018.— [P. 66-75]
1. autor: Kochegurova E. A. Elena Alekseevna
Korporacja: Национальный исследовательский Томский политехнический университет Инженерная школа информационных технологий и робототехники Отделение информационных технологий
Kolejni autorzy: Luneva E. E. Elena Evgenievna, Gorokhova E. S. Ekaterina Sergeevna
Streszczenie: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
Język:angielski
Wydane: 2018
Seria:Advances in Intelligent Systems and Computing book series
Hasła przedmiotowe:
Dostęp online:https://doi.org/10.1007/978-3-030-01821-4_8
Format: Elektroniczne Rozdział
KOHA link:https://koha.lib.tpu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=659708
Opis
Streszczenie: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