Sänger, J;
Hänsch, N;
Glass, B;
Benenson, Z;
Landwirth, R;
Sasse, MA;
(2016)
Look Before You Leap: Improving the Users' Ability to Detect Fraud in Electronic Marketplaces.
In: Kaye, J and Druin, A and Lampe, C and Morris, D and Hourcade, JP, (eds.)
CHI '16: Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems.
(pp. pp. 3870-3882).
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Reputation systems in current electronic marketplaces can easily be manipulated by malicious sellers in order to appear more reputable than appropriate. We conducted a controlled experiment with 40 UK and 41 German participants on their ability to detect malicious behavior by means of an eBay-like feedback profile versus a novel interface involving an interactive visualization of reputation data. The results show that participants using the new interface could better detect and understand malicious behavior in three out of four attacks (the overall detection accuracy 77% in the new vs. 56% in the old interface). Moreover, with the new interface, only 7% of the users decided to buy from the malicious seller (the options being to buy from one of the available sellers or to abstain from buying), as opposed to 30% in the old interface condition.
Type: | Proceedings paper |
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Title: | Look Before You Leap: Improving the Users' Ability to Detect Fraud in Electronic Marketplaces |
Event: | 2016 CHI Conference on Human Factors in Computing Systems (CHI '16) |
ISBN-13: | 9781450333627 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1145/2858036.2858555 |
Publisher version: | http://dx.doi.org/10.1145/2858036.2858555 |
Language: | English |
Keywords: | trust; reputation systems; fraud detection; context-based attacks; visual analytic |
UCL classification: | UCL UCL > Provost and Vice Provost Offices 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 Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/1495950 |
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