Name
Abstract | ||
|---|---|---|
Nowadays, the concern about privacy in online social networks has increased. However, the definition of an appropriate privacy policy might be a complex task, especially when several users are involved and have different privacy preferences. This problem usually appears when a user publishes a photo. In this paper, we propose a tool to automatically define the audience of a photo based on a trust metric. This metric uses a set of features (i.e., distance between users, number of people, emotions, etc.) obtained by the image analysis provided by IBM Cloud Visual Recognition Service. In a preliminary experiment considering 40 photos of 4 users, the results show that the proposed trust metric approximates the real trust relationships between users. We plan to integrate the tool into a real online social network. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00524-5_1 | DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE |
Keywords | Field | DocType |
Image analysis,Privacy negotiation,Social networks,Trust | World Wide Web,IBM,Social network,Trust metric,Computer science,Privacy policy,Visual recognition,Cloud computing,Distributed computing | Conference |
Volume | ISSN | Citations |
802 | 2194-5357 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joaquín Taverner | 1 | 0 | 1.01 |
| Ramon Ruiz | 2 | 0 | 0.34 |
| Elena del Val | 3 | 38 | 10.80 |
| Carlos Diez | 4 | 0 | 0.34 |
| J. Alemany | 5 | 5 | 3.88 |