Mobile apps have become an integral part of our daily lives in that they can be used for accessing a variety of services everywhere, being smart IoT one of the most important domain. However, despite the many benefits that the use of mobile apps provide, there are also risks related to the usage of personal information. Understanding the privacy implications of installing an app could be very difficult, especially for non skilled users. To cope with this issue, in this paper, we provide a risk estimation approach based on apps' static analysis. The output of the static analysis is then used to determine how much the personal data usage pattern of an app diverges from that of apps with the same purpose and this is in turn used to determine the app privacy risk. To prove that the proposed risk estimation measure is effective, we run several experiments with the involvement of different groups of participants, obtaining an accuracy varying from 79% to 82%.
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