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Fraud Detection Using Social Network Analysis, A Case Study

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Synonyms

Auction fraud; Belief propagation; Guilt by association; Money laundering; Pattern mining; Reputation systems; Subgraph matching; User-centered pattern detection

Glossary

Network or Graph :

A collection of entities (e.g., people, bank accounts) and the edges connecting the entities, each edge represents an interaction (e.g., friendship, bank transaction)

Social Network :

A specific type of network where the edges represent social interactions between entities that are people or organizations

Social Network Analysis (SNA) :

The study of networks of social relationships, typically to extract useful information, such as patterns and anomalies

Belief Propagation :

An inference algorithm that finds the marginal distribution of every unobserved variable, conditioned on all observed ones, in a probabilistic graphical model

Definition

Committing fraud means deceiving someone for financial or personal gain. Frauds happen online (e.g., electronic auction) and off-line (e.g., check...

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References

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Acknowledgments

Duen Horng (Polo) Chau was supported by Symantec Research Labs Fellowship. This material is based upon the work supported by the National Science Foundation: IIS-0705359, IIS-0326322, CNS-0721736, and IIS-0534205; the Lawrence Livermore National Laboratory: DE-AC52-07NA27344; an IBM Faculty Award; and a Yahoo Research Alliance Gift, with additional funding from Intel, NTT, and Hewlett-Packard. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or other parties.

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Correspondence to Duen Horng Chau .

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Chau, D.H., Faloutsos, C. (2016). Fraud Detection Using Social Network Analysis, A Case Study. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_284-1

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  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_284-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7163-9

  • Online ISBN: 978-1-4614-7163-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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