FAIR: Fuzzy Alarming Index Rule for Privacy Analysis in Smartphone Apps

  • Majid HatamianEmail author
  • Jetzabel Serna
  • Kai Rannenberg
  • Bodo Igler
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10442)


In this paper, we introduce an approach that aims at increasing individuals’ privacy awareness. We perform a privacy risk assessment of the smartphone applications (apps) installed on a user’s device. We implemented an app behaviour monitoring tool that collects information about access to sensitive resources by each installed app. We then calculate a privacy risk score using a fuzzy logic based approach that considers type, number and frequency of access on resources. The combination of these two concepts provides the user with information about the privacy invasiveness level of the monitored apps. Our approach enables users to make informed privacy decisions, i.e. restrict permissions or report an app based on resource access events. We evaluate our approach by analysing the behaviour of selected apps and calculating their associated privacy score. Initial results demonstrate the applicability of our approach, which allows the comparison of apps by reporting to the user the detected events and the resulting privacy risk score.


Smartphone apps Privacy Usability Beacon alarming Privacy risk score Fuzzy logic 



The authors would like to thank: A. Paterno, D. Mattes, D. Wowniuk, M. Duchmann, M. Krapp, and R. Dieges for providing the app. This research work has received funding from the H2020 Marie Skłodowska-Curie EU project “Privacy&Us” under the grant agreement No. 675730.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Majid Hatamian
    • 1
    Email author
  • Jetzabel Serna
    • 1
  • Kai Rannenberg
    • 1
  • Bodo Igler
    • 2
  1. 1.Chair of Mobile Business and Multilateral SecurityGoethe University FrankfurtFrankfurt am MainGermany
  2. 2.RheinMain University of Applied SciencesWiesbadenGermany

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