Plascua: Programming Language Support for Continuous User Authentication
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Date
2022
Journal Title
Journal ISSN
Volume Title
Publisher
SN Computer Science
Abstract
Compared to traditional user authentication methods, continuous user authentication (CUA) provide enhanced protection,
guarantees against unauthorized access and improved user experience. However, developing effective continuous user
authentication applications using the current programming languages is a daunting task mainly because of lack of abstraction
methods that support continuous user authentication. Using the available language abstractions developers have to write the
CUA concerns (e.g., extraction of behavioural patterns and manual checks of user authentication) from scratch resulting
in unnecessary software complexity and are prone to error. In this paper, we propose new language features that support
the development of applications enhanced with continuous user authentication. We develop Plascua, a continuous user
authentication language extension for event detection of user bio-metrics, extracting of user patterns and modelling using
machine learning and building user authentication profiles. We validate the proposed language abstractions through implementation
of example case studies for CUA.
Description
Keywords
Continuous user authentication (CUA), Explicit user authentication (EUA), Language abstractions, Machine learning
Citation
Muganji, J., & Bainomugisha, E. (2022). Plascua: Programming Language Support for Continuous User Authentication. SN Computer Science, 3(6), 450. https://doi.org/10.1007/s42979-022-01293-9