Publication | Open Access
My Mouse, My Rules
19
Citations
72
References
2021
Year
Unknown Venue
Natural User InterfacePrivacy ProtectionEngineeringMachine LearningInformation SecurityHuman-machine InteractionComputational Social ScienceData ScienceAdversarial Machine LearningDisconcerting Privacy IssueStatisticsWeb BrowsingPrivacy Enhancing TechnologyMultimodal Human Computer InterfacePredictive AnalyticsUser ProfilingData PrivacyComputer ScienceMy RulesPrivacyData SecuritySocial ComputingRecurrent Neural NetHuman-computer Interaction
This paper aims to stir debate about a disconcerting privacy issue on web browsing that could easily emerge because of unethical practices and uncontrolled use of technology. We demonstrate how straightforward is to capture behavioral data about the users at scale, by unobtrusively tracking their mouse cursor movements, and predict user's demographics information with reasonable accuracy using five lines of code. Based on our results, we propose an adversarial method to mitigate user profiling techniques that make use of mouse cursor tracking, such as the recurrent neural net we analyze in this paper. We also release our data and a web browser extension that implements our adversarial method, so that others can benefit from this work in practice.
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