• P.Mounika

As users share through social networking sites, the number of images is increasing, privacy remains a major issue, since some users inadvertently participate in a recent public act, such as this is shown by personal information. In the light of these events, we need tools to help users control access to shared content. To meet this need, an adaptive prediction privacy policy (A3P) is proposed to help users create their image privacy settings. We have examined the role of social origin, the content of the image and the metadata, as possible indicators of user privacy preferences. We propose a two-stage framework, based on the user history available on the site to determine the best user privacy policy available for the image being uploaded. Our solution is based on a similar strategy can be associated with a picture box image classification categories, as well as in accordance with the prediction algorithm of the user's social strategy automatically for each image has A new generation strategy has risen.

Adaptive Privacy Policy Prediction (A3P), A3P-Core

"Privacy Preserving for User-Uploaded Images on Content Sharing Sites", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 9, page no.252-257, September-2018, Available :http://www.jetir.org/papers/JETIRE006042.pdf

"Privacy Preserving for User-Uploaded Images on Content Sharing Sites", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 9, page no. pp252-257, September-2018, Available at : http://www.jetir.org/papers/JETIRE006042.pdf