Content Sharing Sites Used For Privacy Policy Inferences of User Uploaded Images

BODA SUNITHA, K REKHA DEVI

Abstract


With the increase in the volume of images shared by users on social sites, privacy has become a major problem, as evidenced by a recent wave of high profile incidents in which users inadvertently shared personal information. In light of these incidents, the need for tools to help users control access to their shared content is obvious. To meet this need, we provide an adaptive Privacy Policy (Adaptive Privacy Policy) to help users set up privacy settings for their images. We examine the role of the social context, the content of the image and the metadata as possible indicators of the privacy preferences of the users. We propose a two-level framework that, depending on the user's history on the site, determines the best privacy policy available for the images uploaded by the user. Our solution is based on an image classification framework for image categories that can be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly loaded image, also depending on the characteristics. users Over time, the generated policies will follow the evolution of the user's privacy attitude. We provide the results of our in-depth evaluation of more than 5,000 sources, which demonstrate the effectiveness of our system, with prediction accuracies over 90%.


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