Offensive Security of Keyboard Data Using Machine Learning for Password Authentication in IoT

Offensive Security of Keyboard Data Using Machine Learning for Password Authentication in IoT

In this paper, to increase the attack success rate, we analyzed the distribution of all collected keyboard data based on the distance of time and keyboard scancode data, which presents the crucial data from the previous study. To achieve this, we derived time-distance based features that have higher...

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Bibliographic Details
Main Authors: Kyungroul Lee, Jaehyuk Lee, Chang Choi, Kangbin Yim
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Offensive security
vulnerability analysis
password authentication
user authentication
machine learning
Online Access:https://ieeexplore.ieee.org/document/9317787/

Internet

https://ieeexplore.ieee.org/document/9317787/

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