Hyrarchical Classification of Images to Predict Privacy Policy to Uploaded Images on Content Sharing Site

Social Network is an e-service which is booming for sharing contents. Reliable communication is done with social networking sites. Though these sites are a new attacking area for hackers for hacking, they are able to misuse the data through these sites. Some users over CSS affect users privacy on their personal contents, where some users keep on sending unwanted comments and messages by taking advantage of the users inherent trust in their relationship network. Towards addressing this need, we propose a Content-Predicated Relegation system to avail users to get automatically set privacy of their images. We examine the role of gregarious context, image content, and metadata as possible bespeakers of users privacy predilections. Our solution relies on an image relegation framework for image categories which may be associated with homogeneous policies and on a policy presage algorithm to automatically engender a policy for each incipiently uploaded image.