Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/100607
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Type: Journal article
Title: Privacy-preserving fraud detection across multiple phone record databases
Author: Henecka, W.
Roughan, M.
Citation: IEEE Transactions on Dependable and Secure Computing, 2015; 12(6):640-651
Publisher: IEEE
Issue Date: 2015
ISSN: 1545-5971
1941-0018
Statement of
Responsibility: 
Wilko Henecka, and Matthew Roughan
Abstract: Subscription fraud, i.e., customers signing up to a service with no intent to pay, causes significant losses in the telecommunication industry. Telecom operators have developed strategies to identify those fraudsters, but fraudsters tend to migrate from one carrier to another. Data sharing between telecoms would increase fraud detection rates, but phone records are protected by law and telecom operators might be reluctant to share information about fraudsters because they see it as giving a competitive advantage. We propose several protocols to enable fraud detection across multiple databases without revealing additional information. We also propose a model to generate phone records, with which we evaluate how the choice of parameters affects detection performance. We show feasibility, performance and costs with implementations of our protocols.
Keywords: Graph matching; secure multiparty computation; privacy-preserving fraud detection; call pattern synthesis
Description: Date of Publication : 18 December 2014
Rights: © 2014 IEEE.
RMID: 0030042119
DOI: 10.1109/TDSC.2014.2382573
Grant ID: http://purl.org/au-research/grants/arc/DP0985063
Appears in Collections:Mathematical Sciences publications

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