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Anomaly detection from call data records

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2009) 5909 LNCS 237-242
DOI: 10.1007/978-3-642-11164-8_38
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Abstract

In this paper, we propose an efficient algorithm for anomaly detection from call data records. Anomalous users are detected based on fuzzy attribute values derived from their communication patterns. A clustering based algorithm is proposed to generate explanations to assist human analysts in validating the results. © 2009 Springer-Verlag Berlin Heidelberg.

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Nithi, & Dey, L. (2009). Anomaly detection from call data records. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5909 LNCS, pp. 237–242). https://doi.org/10.1007/978-3-642-11164-8_38

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