Abstract
Web users want to protect their privacy while sharing content online. This can be done through automated privacy assistants that are capable of taking actions by detecting privacy violations and recommending privacy settings for content that the user intends to share. While these approaches are promising in terms of the accuracy of their privacy decisions, they lack the ability to explain to the end user why certain decisions are being made. In this work, we study how privacy assistants can be enhanced through explanations generated in the context of privacy decisions for the user content. We outline a methodology to create explanations of privacy decisions, discuss core challenges, and show example explanations that are generated by our approach.
| Original language | English |
|---|---|
| Pages (from-to) | 75-80 |
| Number of pages | 6 |
| Journal | IEEE Internet Computing |
| Volume | 27 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1 Jul 2023 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Funding
The first author is supported by the Scientific and Technological Research Council of Turkey (TUBITAK) and Turkish Directorate of Strategy and Budget under the TAM Project number 2007K12 - 873. This research was partially funded by the Hybrid Intelligence Center, a 10-year program funded by the Dutch Ministry of Education, Culture, and Science through the Netherlands Organization for Scientific Research. This work does not relate to Şensoy's position at Amazon.
| Funders | Funder number |
|---|---|
| Dutch Ministry of Education, Culture, and Science | |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | |
| Türkiye Bilimsel ve Teknolojik Araştırma Kurumu | 2007K12 - 873 |
Keywords
- Content management
- Internet
- Privacy