My Privacy My Decision: Control of Photo Sharing on Online Social Networks



My Privacy My Decision: Control of Photo Sharing on Online Social Networks
Abstract
—Photo sharing is an attractive feature which popularizes Online Social Networks (OSNs). Unfortunately, it may leak users’ privacy if they are allowed to post, comment, and tag a photo freely. In this paper, we attempt to address this issue and study the scenario when a user shares a photo containing individuals other than himself/herself (termed co-photo for short). To prevent possible privacy leakage of a photo, we design a mechanism to enable each individual in a photo be aware of the posting activity and participate in the decision making on the photo posting. For this purpose, we need an efficient facial recognition (FR) system that can recognize everyone in the photo. However, more demanding privacy setting may limit the number of the photos publicly available to train the FR system. To deal with this dilemma, our mechanism attempts to utilize users’ private photos to design a personalized FR system specifically trained to differentiate possible photo co-owners without leaking their privacy. We also develop a distributed consensus- based method to reduce the computational complexity and protect the private training set. We show that our system is superior to other possible approaches in terms of recognition ratio and efficiency. Our mechanism is implemented as a proof of concept Android
application on Facebook’s platform.

Existing System
An FR engine for a large-scale social network may require discriminating millions of individuals. It seems to be a daunting task that could never be accoplished. However, when we decompose it into several personal FR engines, the situation will change for better. Social contexts contains a large amount of useful informa- tion which could be utilized as a priori knowledge to help the facial recognition[19]. In [12], Mavridis, Kazmi and Toulis develop a three-realm model to study facial recognition problems on OSN photos. The three realms include a social realm, in which identities are entities and friendship a relation; a visual sensory realm, of which faces are entities and occurrence in images a relation; and a physical realm, in which bodies belong, with physical proximity being a relation. It is shown that the relationship in the social realm and physical realm are highly correlated with the relationship in the visual sensory realm. In this manner, we can use the social context to construct a priori distribution . With this priori distribution, while trying to recognize people on the co-photos, the FR engine could focus on a small portion of “close” friends (friends who are geographically close and interacting frequently with user ).

Proposed System
1) In our paper, the potential owners of shared items (photos) can be automatically identified with/without user-generated tags.
2) We propose to use private photos in a privacy-preserving manner and social contexts to
derive a personal FR engine for any particular user.

Software Requirements: -
Operating System       :    Android OS
Front-End                    :    HTML, CSS, and JS
Back-End                     :    Angular JS, PHP, MYSQL
Tool                             :    Cordova

Android Projects 
codeshoppy.com
http://codeshoppy.com/android-ieee-projects-titles-2017-2018.html
Android Youtube Channel
arudhrainnovations.com

contact@codeshoppy.com
9790675343

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