TY - GEN
T1 - Analysis and detection of SIMbox fraud in mobility networks
AU - Murynets, Ilona
AU - Zabarankin, Michael
AU - Jover, Roger Piqueras
AU - Panagia, Adam
PY - 2014
Y1 - 2014
N2 - Voice traffic termination fraud, often referred to as Subscriber Identity Module box (SIMbox) fraud, is a common illegal practice on mobile networks. As a result, cellular operators around the globe lose billions annually. Moreover, SIMboxes compromise the cellular network infrastructure by overloading local base stations serving these devices. This paper analyzes the fraudulent traffic from SIMboxes operating with a large number of SIM cards. It processes hundreds of millions of anonymized voice call detail records (CDRs) from one of the main cellular operators in the United States. In addition to overloading voice traffic, fraudulent SIMboxes are observed to have static physical locations and to generate disproportionately large volume of outgoing calls. Based on these observations, novel classifiers for fraudulent SIMbox detection in mobility networks are proposed. Their outputs are optimally fused to increase the detection rate. The operator's fraud department confirmed that the algorithm succeeds in detecting new fraudulent SIMboxes.
AB - Voice traffic termination fraud, often referred to as Subscriber Identity Module box (SIMbox) fraud, is a common illegal practice on mobile networks. As a result, cellular operators around the globe lose billions annually. Moreover, SIMboxes compromise the cellular network infrastructure by overloading local base stations serving these devices. This paper analyzes the fraudulent traffic from SIMboxes operating with a large number of SIM cards. It processes hundreds of millions of anonymized voice call detail records (CDRs) from one of the main cellular operators in the United States. In addition to overloading voice traffic, fraudulent SIMboxes are observed to have static physical locations and to generate disproportionately large volume of outgoing calls. Based on these observations, novel classifiers for fraudulent SIMbox detection in mobility networks are proposed. Their outputs are optimally fused to increase the detection rate. The operator's fraud department confirmed that the algorithm succeeds in detecting new fraudulent SIMboxes.
UR - http://www.scopus.com/inward/record.url?scp=84904438188&partnerID=8YFLogxK
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U2 - 10.1109/INFOCOM.2014.6848087
DO - 10.1109/INFOCOM.2014.6848087
M3 - Conference contribution
AN - SCOPUS:84904438188
SN - 9781479933600
T3 - Proceedings - IEEE INFOCOM
SP - 1519
EP - 1526
BT - IEEE INFOCOM 2014 - IEEE Conference on Computer Communications
T2 - 33rd IEEE Conference on Computer Communications, IEEE INFOCOM 2014
Y2 - 27 April 2014 through 2 May 2014
ER -