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2020 | OriginalPaper | Chapter

Fingerprinting of URL Logs: Continuous User Authentication from Behavioural Patterns

Authors : Jakub Nowak, Taras Holotyak, Marcin Korytkowski, Rafał Scherer, Slava Voloshynovskiy

Published in: Computational Science – ICCS 2020

Publisher: Springer International Publishing

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Abstract

Security of computer systems is now a critical and evolving issue. Current trends try to use behavioural biometrics for continuous authorization. Our work is intended to strengthen network user authentication by a software interaction analysis. In our research, we use HTTP request (URLs) logs that network administrators collect. We use a set of full-convolutional autoencoders and one authentication (one-class) convolutional neural network. The proposed method copes with extensive data from many users and allows to add new users in the future. Moreover, the system works in a real-time manner, and the proposed deep learning framework can use other user behaviour- and software interaction-related features.

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Metadata
Title
Fingerprinting of URL Logs: Continuous User Authentication from Behavioural Patterns
Authors
Jakub Nowak
Taras Holotyak
Marcin Korytkowski
Rafał Scherer
Slava Voloshynovskiy
Copyright Year
2020
Book
Computational Science – ICCS 2020

Print ISBN: 978-3-030-50422-9

Electronic ISBN: 978-3-030-50423-6

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-50423-6_14