Protecting Private Attributes in App Based Mobile User Profiling
<p dir="ltr">The Analytics companies enable successful targeted advertising via user profiles, derived from the mobile apps installed by specific users, and hence have become an integral part of the mobile advertising industry. This threatens the users' privacy, when profiling i...
محفوظ في:
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| مؤلفون آخرون: | , , , , |
| منشور في: |
2020
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إضافة وسم
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| _version_ | 1864513505262043136 |
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| author | Imdad Ullah (18372291) |
| author2 | Roksana Boreli (19672726) Salil S. Kanhere (19672729) Sanjay Chawla (4254202) Tariq Ahamed Ahanger (19672732) Usman Tariq (12573403) |
| author2_role | author author author author author |
| author_facet | Imdad Ullah (18372291) Roksana Boreli (19672726) Salil S. Kanhere (19672729) Sanjay Chawla (4254202) Tariq Ahamed Ahanger (19672732) Usman Tariq (12573403) |
| author_role | author |
| dc.creator.none.fl_str_mv | Imdad Ullah (18372291) Roksana Boreli (19672726) Salil S. Kanhere (19672729) Sanjay Chawla (4254202) Tariq Ahamed Ahanger (19672732) Usman Tariq (12573403) |
| dc.date.none.fl_str_mv | 2020-08-05T06:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2020.3014424 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Protecting_Private_Attributes_in_App_Based_Mobile_User_Profiling/27021697 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Information and computing sciences Cybersecurity and privacy Human-centred computing Privacy targeted ads mobile apps obfuscation user experience Advertising Ecosystems Servers Companies Mobile handsets |
| dc.title.none.fl_str_mv | Protecting Private Attributes in App Based Mobile User Profiling |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The Analytics companies enable successful targeted advertising via user profiles, derived from the mobile apps installed by specific users, and hence have become an integral part of the mobile advertising industry. This threatens the users' privacy, when profiling is based on apps representing sensitive information, e.g., gambling problems indicated by a game app. In this work, we propose an app-based profile obfuscation mechanism, ProfileGuard, with the objective of eliminating the dominance of private interest categories (i.e. the prevailing private interest categories present in a user profile). We demonstrate, based on wide-range experimental evaluation of Android apps in a nine month test campaign, that the proposed obfuscation mechanism based on similarity with user's existing apps (ensuring that selected obfuscating apps belong to non-private categories) can achieve a good trade-off between efforts required by the obfuscating system and the resulting privacy protection. We also show how the bespoke (customised to profile obfuscation) and bespoke++ (resource-aware) strategies can deliver significant improvements in the level of obfuscation and (particularly bespoke++) in the use of mobile resources, making the latter a good candidate strategy in resource-constrained scenarios e.g., for fixed data use mobile plans. We also implement a POC ProfileGuard app to demonstrate the feasibility of an automated obfuscation mechanism. Furthermore, we provide insights to Google AdMob profiling rules, such as showing how individual apps map to user's interests within their profile in a deterministic way and that AdMob requires a certain level of activity to build a stable user profile.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2020.3014424" target="_blank">https://dx.doi.org/10.1109/access.2020.3014424</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_aacb67bfc09663f484be791146f147dd |
| identifier_str_mv | 10.1109/access.2020.3014424 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/27021697 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Protecting Private Attributes in App Based Mobile User ProfilingImdad Ullah (18372291)Roksana Boreli (19672726)Salil S. Kanhere (19672729)Sanjay Chawla (4254202)Tariq Ahamed Ahanger (19672732)Usman Tariq (12573403)Information and computing sciencesCybersecurity and privacyHuman-centred computingPrivacytargeted adsmobile appsobfuscationuser experienceAdvertisingGoogleEcosystemsServersCompaniesMobile handsets<p dir="ltr">The Analytics companies enable successful targeted advertising via user profiles, derived from the mobile apps installed by specific users, and hence have become an integral part of the mobile advertising industry. This threatens the users' privacy, when profiling is based on apps representing sensitive information, e.g., gambling problems indicated by a game app. In this work, we propose an app-based profile obfuscation mechanism, ProfileGuard, with the objective of eliminating the dominance of private interest categories (i.e. the prevailing private interest categories present in a user profile). We demonstrate, based on wide-range experimental evaluation of Android apps in a nine month test campaign, that the proposed obfuscation mechanism based on similarity with user's existing apps (ensuring that selected obfuscating apps belong to non-private categories) can achieve a good trade-off between efforts required by the obfuscating system and the resulting privacy protection. We also show how the bespoke (customised to profile obfuscation) and bespoke++ (resource-aware) strategies can deliver significant improvements in the level of obfuscation and (particularly bespoke++) in the use of mobile resources, making the latter a good candidate strategy in resource-constrained scenarios e.g., for fixed data use mobile plans. We also implement a POC ProfileGuard app to demonstrate the feasibility of an automated obfuscation mechanism. Furthermore, we provide insights to Google AdMob profiling rules, such as showing how individual apps map to user's interests within their profile in a deterministic way and that AdMob requires a certain level of activity to build a stable user profile.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2020.3014424" target="_blank">https://dx.doi.org/10.1109/access.2020.3014424</a></p>2020-08-05T06:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2020.3014424https://figshare.com/articles/journal_contribution/Protecting_Private_Attributes_in_App_Based_Mobile_User_Profiling/27021697CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/270216972020-08-05T06:00:00Z |
| spellingShingle | Protecting Private Attributes in App Based Mobile User Profiling Imdad Ullah (18372291) Information and computing sciences Cybersecurity and privacy Human-centred computing Privacy targeted ads mobile apps obfuscation user experience Advertising Ecosystems Servers Companies Mobile handsets |
| status_str | publishedVersion |
| title | Protecting Private Attributes in App Based Mobile User Profiling |
| title_full | Protecting Private Attributes in App Based Mobile User Profiling |
| title_fullStr | Protecting Private Attributes in App Based Mobile User Profiling |
| title_full_unstemmed | Protecting Private Attributes in App Based Mobile User Profiling |
| title_short | Protecting Private Attributes in App Based Mobile User Profiling |
| title_sort | Protecting Private Attributes in App Based Mobile User Profiling |
| topic | Information and computing sciences Cybersecurity and privacy Human-centred computing Privacy targeted ads mobile apps obfuscation user experience Advertising Ecosystems Servers Companies Mobile handsets |