Survey on Privacy Policy Specification System for User Uploaded Images Over Popular Content Sharing Sites

Abstract

The regular use of social networking websites and application encompasses the collection and retention of personal and very often sensitive information about users. This information needs to remain private and each social network owns a privacy policy that describes in-depth how user's information is managed and published. As there is increasing use of images for sharing through social sites, maintaining privacy has become a major problem. In light of these incidents, the need of tools to aid users control access to their shared content is necessary. This problem can be proposed by using an Privacy Policy Prediction system to help users compose privacy settings for their shared images. To examine the indicators of users privacy preferences one can use the role of social context, image content, and metadata as possible according to information available. Our solution relies on 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. We propose a two-level image classification framework to obtain image categories which may be associated with similar policies. Then, we develop a policy prediction algorithm to automatically generate a policy for each newly uploaded image. This will generate policies that will follow the evolution of user's privacy according to his requirement.