Predictive analytics to prevent voice over ip international revenue sharing fraud

Yoram J. Meijaard, Bram C.M. Cappers, Josh G.M. Mengerink, Nicola Zannone

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

Samenvatting

International Revenue Sharing Fraud (IRSF) is the most persistent type of fraud in the telco industry. Hackers try to gain access to an operator’s network in order to make expensive unauthorized phone calls on behalf of someone else. This results in massive phone bills that victims have to pay while number owners earn the money. Current anti-fraud solutions enable the detection of IRSF afterwards by detecting deviations in the overall caller’s expenses and block phone devices to prevent attack escalation. These solutions suffer from two main drawbacks: (i) they act only when financial damage is done and (ii) they offer no protection against future attacks. In this paper, we demonstrate how unsupervised machine learning can be used to discover fraudulent calls at the moment of their establishment, thereby preventing IRSF from happening. Specifically, we investigate the use of Isolation Forests for the detection of frauds before calls are initiated and compare the results to an existing industrial post-mortem anti-fraud solution.

Originele taal-2Engels
TitelData and Applications Security and Privacy - 34th Annual IFIP WG 11.3 Conference, DBSec 2020, Proceedings
RedacteurenAnoop Singhal, Jaideep Vaidya
UitgeverijSpringer
Pagina's241-260
Aantal pagina's20
ISBN van geprinte versie9783030496685
DOI's
StatusGepubliceerd - 2020
Evenement34th Annual IFIP WG11.3 Conference on Data and Applications Security and Privacy, DBSec 2020 - Regensburg, Duitsland
Duur: 25 jun 202026 jun 2020

Publicatie series

NaamLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12122 LNCS
ISSN van geprinte versie0302-9743
ISSN van elektronische versie1611-3349

Congres

Congres34th Annual IFIP WG11.3 Conference on Data and Applications Security and Privacy, DBSec 2020
Land/RegioDuitsland
StadRegensburg
Periode25/06/2026/06/20

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