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

Conference paper (2022)

Authors

V. Herrera Semenets Advanced Technologies Application Center
Raudel Hernández-León Advanced Technologies Application Center
Lázaro Bustio-Martínez Universidad Iberoamericana
Jan van den Berg Cyber Security - EEMCS
Research Group
Cyber Security (EEMCS) (TU Delft)
Copyright: © 2022 V. Herrera Semenets, Raudel Hernández-León, Lázaro Bustio-Martínez, Jan van den Berg
DOI
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https://doi.org/10.1007/978-3-031-19496-2_24
Cybersecurity Anomaly detection Concept drift Online data processing Behavior changes Multimodal data analysis
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Published Date

2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Cyber Security

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.