USING DECISION TREE AND MACHINE LEARNING TO RECOGNIZE USERS BY THEIR BEHAVIOUR

被引：0

作者：

Zamfiroiu, Alin ^{[1
]}

Boncea, Radu ^{[2
]}

机构：

[1] Bucharest Univ Econ Studies, Natl Inst Res & Dev Informat, Bucharest, Romania

[2] Natl Inst Res & Dev Informat, Bucharest, Romania

来源：

PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON INFORMATICS IN ECONOMY (IE 2017): EDUCATION, RESEARCH & BUSINESS TECHNOLOGIES | 2017年

关键词：

decision tree; mobile applications; model; TensorFlow; user behaviour; CLASSIFICATION;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This research proposes a complementary method for authenticating users on mobile applications. The method uses decision trees to recognize user behaviour based on specific measurable properties such as the speed of text typing, the preferred zoom factor, the reading and writing mode or the preferred mode of closing the keyboard. By continuously doing measurements on these properties every time the user is using the application, a user profile can be generated, stored and used by the application to authenticate the rightful owner. This functionality can be further extended using Machine Learning algorithms such as Sofimax Regression to recognize a specific user from a given group.

引用

页码：90 / 95

页数：6

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