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Trends in online consumer fraud: A data science perspective

Soldner, Felix; Kleinberg, Bennett; Johnson, Shane; (2022) Trends in online consumer fraud: A data science perspective. In: A Fresh Look at Fraud. (pp. 167-191). Routledge: London, UK. Green open access

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Abstract

Following the advent of the Internet, the interaction between sellers and consumers is increasingly shifting from a face-to-face towards an online environment. This chapter examines what online consumer fraud is, revisiting the definition and common fraud schemes. It reviews some of the current approaches non-governmental and commercial institutions take to detect and prevent online consumer fraud. The chapter discusses darknet markets – internet platforms that, amongst other things, sell both legal and illicit goods while providing anonymity – and how they facilitating online consumer fraud. It closes with a discussion of how methods from data science can be applied to support the detection and prevention of online consumer fraud. The dark web represents a small portion of the deep web, on which users and hosts are anonymized.

Type: Book chapter
Title: Trends in online consumer fraud: A data science perspective
ISBN-13: 9781003017189
Open access status: An open access version is available from UCL Discovery
DOI: 10.4324/9781003017189-9
Publisher version: https://doi.org/10.4324/9781003017189-9
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Security and Crime Science
URI: https://discovery.ucl.ac.uk/id/eprint/10162652
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