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Title: A user behavior based cheat detection mechanism for crowdtesting
Authors: Mok, RKP
Li, W 
Chang, RKC 
Keywords: Cheat-detection
Cursor submovement
Issue Date: 2015
Publisher: Association for Computing Machinary
Source: Computer communication review, 2015, v. 44, no. 4, p. 123-124 How to cite?
Journal: Computer communication review 
Abstract: Crowdtesting is increasingly popular among researchers to carry out subjective assessments of different services. Experimenters can easily assess to a huge pool of human subjects through crowdsourcing platforms. The workers are usually anonymous, and they participate in the experiments independently. Therefore, a fundamental problem threatening the integrity of these platforms is to detect various types of cheating from the workers. In this poster, we propose cheat-detection mechanism based on an analysis of the workers' mouse cursor trajectories. It provides a jQuery-based library to record browser events. We compute a set of metrics from the cursor traces to identify cheaters. We deploy our mechanism to the survey pages for our video quality assessment tasks published on Amazon Mechanical Turk. Our results show that cheaters' cursor movement is usually more direct and contains less pauses.
Description: ACM SIGCOMM 2014 Conference, Chicago, 17-22 August 2014
ISSN: 0146-4833 (print)
DOI: 10.1145/2619239.2631447
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