Abstract
In this paper we show how social networks, implicitly built from communication data, can serve as a basis for suspicious behavior detection from large communications data (landlines and mobile phone calls) provided by communication services providers for criminal investigators following two procedures: lawful interception and data retention. We propose the following contributions: (i) a data model and a set of operators for querying this data in order to extract suspicious behavior and (ii) a user friendly and easy-to-navigate visual representation for communication data with a prototype implementation.
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Bennamane, A., Hacid, H., Ansiaux, A., Cagnati, A. (2011). Visual Analysis of Implicit Social Networks for Suspicious Behavior Detection. In: Yu, J.X., Kim, M.H., Unland, R. (eds) Database Systems for Advanced Applications. DASFAA 2011. Lecture Notes in Computer Science, vol 6588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20152-3_29
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DOI: https://doi.org/10.1007/978-3-642-20152-3_29
Publisher Name: Springer, Berlin, Heidelberg
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