Relationship privacy preservation in photo sharing

Abstract

In recent years, Online Social Networks (OSN) have become popular content-sharing environments. With the emergence of smartphones with high-quality cameras, people like to share photos of their life moments on OSNs. The photos, however, often contain private information that people do not intend to share with others (e.g., their sensitive relationship). Solely relying on OSN users to manually process photos to protect their relationship can be tedious and error-prone. Therefore, we designed a system to automatically discover sensitive relations in a photo to be shared online and preserve the relations by face blocking techniques. We first used the Decision Tree model to learn sensitive relations from the photos labeled private or public by OSN users. Then we defined a face blocking problem to handle the trade-off between preserving relationship privacy and maintaining the photo utility. To cope with the problem, we developed Greedy and Linear Programming based face blocking technologies. In this paper, we generated synthetic data and used it to evaluate our system performance in terms of privacy protection and photo utility loss.