Conference paper Open Access

A Multilateral Privacy Impact Analysis Method for Android Apps

Hatamian, Majid; Momen, Nurul; Fritsch, Lothar; Rannenberg, Kai


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  <identifier identifierType="URL">https://zenodo.org/record/3248889</identifier>
  <creators>
    <creator>
      <creatorName>Hatamian, Majid</creatorName>
      <givenName>Majid</givenName>
      <familyName>Hatamian</familyName>
      <affiliation>Goethe University Frankfurt</affiliation>
    </creator>
    <creator>
      <creatorName>Momen, Nurul</creatorName>
      <givenName>Nurul</givenName>
      <familyName>Momen</familyName>
      <affiliation>Karlstad University</affiliation>
    </creator>
    <creator>
      <creatorName>Fritsch, Lothar</creatorName>
      <givenName>Lothar</givenName>
      <familyName>Fritsch</familyName>
      <affiliation>Karlstad University</affiliation>
    </creator>
    <creator>
      <creatorName>Rannenberg, Kai</creatorName>
      <givenName>Kai</givenName>
      <familyName>Rannenberg</familyName>
      <affiliation>Goethe University Frankfurt</affiliation>
    </creator>
  </creators>
  <titles>
    <title>A Multilateral Privacy Impact Analysis Method for Android Apps</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-06-08</date>
  </dates>
  <language>en</language>
  <resourceType resourceTypeGeneral="ConferencePaper"/>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3248889</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.1007/978-3-030-21752-5_7</relatedIdentifier>
  </relatedIdentifiers>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;Smartphone apps have the power to monitor most of people&amp;rsquo;s private lives. Apps can permeate private spaces, access and map social relationships, monitor whereabouts and chart people&amp;rsquo;s activities in digital and/or real world. We are therefore interested in how much information a particular app can and intends to retrieve in a smartphone. Privacy-friendliness of smartphone apps is typically measured based on single-source analyses, which in turn, does not provide a comprehensive measurement regarding the actual privacy risks of apps. This paper presents a multi-source method for privacy analysis and data extraction transparency of Android apps. We describe how we generate several data sets derived from privacy policies, app manifestos, user reviews and actual app profiling at run time. To evaluate our method, we present results from a case study carried out on ten popular fitness and exercise apps. Our results revealed interesting differences concerning the potential privacy impact of apps, with some of the apps in the test set violating critical privacy principles. The result of the case study shows large differences that can help make relevant app choices.&lt;/p&gt;</description>
  </descriptions>
  <fundingReferences>
    <fundingReference>
      <funderName>European Commission</funderName>
      <funderIdentifier funderIdentifierType="Crossref Funder ID">10.13039/501100000780</funderIdentifier>
      <awardNumber awardURI="info:eu-repo/grantAgreement/EC/H2020/675730/">675730</awardNumber>
      <awardTitle>Privacy and Usabiliy</awardTitle>
    </fundingReference>
  </fundingReferences>
</resource>
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