Privacy policy inference of multiple user-uploaded images on social context websites (Automated generation of privacy policy)

Social networking websites are the most active websites on the Internet and millions of people use them every day to engage and connect with other people. Twitter, Facebook, LinkedIn and Google Plus seems to be the most popular Social networking websites on the Internet. In this manner, recommendation policy is required which supply client with an adaptable help for organizing security settings in much easier way. Images are shared extensively now days on social sharing sites. Sharing takes place between friends and acquaintances on a daily basis. In this thesis, we are implementing an Adaptive Privacy Policy Prediction (A3P) system which will provide users a disturbance free privacy settings experience by automatically generating personalized policies.

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