  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.
