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

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.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.Cyber Securit

A data reduction strategy and its application on scan and backscatter detection using rule-based classifiers

In the last few years, the telecommunications scenario has experienced an increase in the volume of information generated, as well as in the execution of malicious activities. In order to complement Intrusion Detection Systems (IDSs), data mining techniques have begun to play a fundamental role in data analysis. On the other hand, the presence of useless information and the amount of data generated by telecommunication services (leading to a huge dimensional problem), can affect the performance of traditional IDSs. In this sense, a data preprocessing strategy is necessary to reduce data, but reducing data without affecting the accuracy of IDSs represents a challenge. In this paper, we propose a new data preprocessing strategy which reduces the number of features and instances in the training collection without greatly affecting the achieved accuracy of IDSs. Finally, our proposal is evaluated using four different rule-based classifiers, which are tested on real scan and backscatter data collected by a network telescope.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.Information and Communication TechnologyCyber Securit