A different approach for improved Privacy of User Data and Images on Content Sharing Sites using (A3P)

Hoora Mohammed, Md. Amanatulla

Abstract


Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. Social networking sites such as Facebook, LinkedIn, etc give opportunities to share large amount of personal information. People upload their photos to these sites to gain public attention for social purposes, and thus many public consumer photographs are available online. The proliferation of personal data leads to privacy violation .Risks such as identify theft, embarrassment, and blackmail are faced by user’s .In order to overcome these risks flexible privacy mechanisms need to be considered. The main aim of this survey is to provide a review on different privacy policy approaches to enhance the security of personal information shared in the online social networking sites. A number of researchers have studied the social uses and privacy issues of online photo sharing or content sharing sites , but less have explored the privacy issues of photo sharing in social networks. Users of social-networking services share abundant information with numerous “friends.” This improved technology causes to privacy violation where the users are sharing the enormous volumes of images across more number of peoples. This privacy need to be taken care in order to make better the user satisfaction level. 


References


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