On Continuous User Authentication via Hidden Free-Text Based Monitoring / E. A. Kochegurova, E. E. Luneva, E. S. Gorokhova

Уровень набора: Advances in Intelligent Systems and ComputingОсновной Автор-лицо: Kochegurova, E. A., specialist in the field of Informatics and computer engineering, associate Professor of Tomsk Polytechnic University, candidate of technical Sciences, 1958-, Elena AlekseevnaАльтернативный автор-лицо: Luneva, E. E., specialist in the field of informatics and computer technology, Associate Professor of Tomsk Polytechnic University, Candidate of technical sciences, Leading programmer, 1981-, Elena Evgenievna;Gorokhova, E. S., Ekaterina SergeevnaКоллективный автор (вторичный): Национальный исследовательский Томский политехнический университет, Инженерная школа информационных технологий и робототехники, Отделение информационных технологийЯзык: английский.Серия: Advances in Intelligent Systems and Computing book seriesРезюме или реферат: 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..Примечания о наличии в документе библиографии/указателя: [References: 21 tit.].Аудитория: .Тематика: электронный ресурс | труды учёных ТПУ | динамика | аутентификация | биометрия | классификации Ресурсы он-лайн:Щелкните здесь для доступа в онлайн
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[References: 21 tit.]

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.

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