Online social networking has become the predominant activity in the digital world thanks to multimedia data (mainly photos) sharing (e.g., photos now represent 93% of the top posts on Facebook). Discovering events where users are involved using their own posts and those shared by their friends would be of great importance. In this paper, we address this issue by providing an original approach able to detect, enrich and also link user's events using photos shared within his online social networks. Using metadata, our approach provides a multidimensional gathering of similar photos using their temporal, geographical, and social facets. To validate our approach, we implemented a prototype called Foto2Events and conducted a set of experiments on real and generated data. Results show that our approach works well for various metadata distributions.
Outsourcing social multimedia documents is a growing practice among several companies in a way to shift their business globally. It is a cost-effective process where those companies tend to gain more profits disregarding eventual privacy risks. In fact, several case studies have showed that adversaries are capable of identifying individuals, whose identities need to be kept private, using the content of their multimedia documents. In this paper, we propose de-linkability, a privacy-preserving constraint to bound the amount of information outsourced that can be used to re-identify the individual. We also provide a sanitizing MD * -algorithm to enforce de-linkability and present a set of experiments to demonstrate its efficiency.
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