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.
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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 |
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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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