• SNEHA BANKAR
• M. M. Ambekar

Images today are increasingly shared online on social networking sites such as Facebook, Flickr, and Instagram. Image sharing occurs not only within a group of friends but also more and more outside a user’s social circles for purposes of social discovery. Despite that current social networking sites allow users to change their privacy preferences, this is often a cumbersome task for the vast majority of users on theWeb, who face difficulties in assigning andmanaging privacy settings. When these privacy settings are used inappropriately, online image sharing can potentially lead to unwanted disclosures and privacy violations. Thus, automatically predicting images’ privacy to warn users about private or sensitive content before uploading these images on social networking sites has become a necessity in our current interconnected world.

Machine Learning, Social Media, Python, security and privacy, online information services.

"Security Control for Client Transfer Pictures On Social Locales", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.e86-e89, October-2021, Available :http://www.jetir.org/papers/JETIR2110426.pdf

"Security Control for Client Transfer Pictures On Social Locales", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppe86-e89, October-2021, Available at : http://www.jetir.org/papers/JETIR2110426.pdf