Secrecy of Uploaded Images on Locates Using A3P Algorithm

Abstract

With increasing volume of images users share through social sites, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users individually shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. We examine the role of social context, image content and metadata as possible indicators of user’s privacy preferences. We propose a two-level framework which according to the user’s available history on the site, determines the best available privacy policy for the user’s images being uploaded. Our solution relies on an image classification framework for images categories which may be associated with similar policies on a policy prediction algorithm to automatically generate a policy for each newly uploaded image and also according to user’s social features. Over time, generated policies will follow the evolution of user’s privacy attitude.