Red Light/Green Light: A Lightweight Algorithm for, Possibly, Fraudulent Online Behavior Change Detection

Conference Paper (2022)
Author(s)

V. Herrera Semenets (Advanced Technologies Application Center)

Raudel Hernández-León (Advanced Technologies Application Center)

Lázaro Bustio-Martínez (Universidad Iberoamericana)

Jan van den Berg (TU Delft - Cyber Security)

Research Group
Cyber Security
Copyright
© 2022 V. Herrera Semenets, Raudel Hernández-León, Lázaro Bustio-Martínez, Jan van den Berg
DOI related publication
https://doi.org/10.1007/978-3-031-19496-2_24
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 V. Herrera Semenets, Raudel Hernández-León, Lázaro Bustio-Martínez, Jan van den Berg
Research Group
Cyber Security
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
316-327
ISBN (electronic)
978-3-031-19496-2
Reuse Rights

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Abstract

Telecommunications services have become a constant in people’s lives. This has inspired fraudsters to carry out malicious activities causing economic losses to people and companies. Early detection of signs that suggest the possible occurrence of malicious activity would allow analysts to act in time and avoid unintended consequences. Modeling the behavior of users could identify when a significant change takes place. Following this idea, an algorithm for online behavior change detection in telecommunication services is proposed in this paper. The experimental results show that the new algorithm can identify behavioral changes related to unforeseen events.

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