| Mobile devices have become an indispensable part of everyday life for most people and have improved our lives in many ways, offering a multitude of possibilities through the various available applications. On one hand, the risks around information privacy on mobile devices become more and more challenging. On the other hand, users are called to analyse and take plenty of complex privacy decisions. There have been many attempts to overcome this burden from users by automating the process of granting permissions to ap-plications. This study provides a literature review on works for predicting users' privacy decisions in application requests. Our research aims to shed light on the different factors that have been identified in the literature as important predictors of users’ decisions on app requests, as well as the methods that have been used, focusing on machine learning approaches and building user privacy profiles. |
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