Proactive Privacy Risk Assessment for Android Applications: A Machine Learning Based-Approach

Mobile devices have become ubiquitous, collecting vast amounts of personal data through granted permissions.Privacy concerns arise when personal information is leaked to third parties without the user's awareness or consent.To address this issue, we propose a proactive approach based on a Machine Learning model to predict privacy risk scores for Android applications.These scores are based on the requested permissions and allow the users to be aware of the potential leakage of sensitive information before installing an application.Experimental evaluations demonstrate the competitive performance of our model against existing state-of-the-art methods.