Abstract
Security Information and Event Management (SIEM) systems are largely used to process logs generated by both hardware and software devices to assess the security level of service infrastructures. This log-based security analysis consists in correlating massive amounts of information in order to detect attacks and intrusions. In order to make this analysis more accurate and effective we propose an approach based on the Dempster-Shafer theory, that allows for combining evidence from multiple and heterogeneous data sources and get to a degree of belief that takes into account all the available evidence. The proposed approach has been validated with the respect to a challenging demonstration case, namely the detection of frauds performed against a Mobile Money Transfer service. An extensive simulation campaign has been executed to assess the performance of the proposed approach and the experimental results are presented in this paper.
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Coppolino, L., D’Antonio, S., Formicola, V., Massei, C., Romano, L. (2015). Use of the Dempster-Shafer Theory for Fraud Detection: The Mobile Money Transfer Case Study. In: Camacho, D., Braubach, L., Venticinque, S., Badica, C. (eds) Intelligent Distributed Computing VIII. Studies in Computational Intelligence, vol 570. Springer, Cham. https://doi.org/10.1007/978-3-319-10422-5_48
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DOI: https://doi.org/10.1007/978-3-319-10422-5_48
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10421-8
Online ISBN: 978-3-319-10422-5
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