A Self–learning Personal Privacy Assistant

Abstract

Defining and determining personal privacy is difficult; people jeopardize their personal lives and careers due to a lack of discernment. In this paper we propose an automated self-learning privacy assistant without a central entity determining the privacy and without pre-determined or labelled privacy data. We use the web as a data trove to determine privacy based on unsupervised learning. Experiments demonstrate the validity of our approach.