Evaluating Secure Methodology for Photo Sharing in Online Social Networks

Abstract

Social media has now become a part of people’s lives. That is, today people interact on social media in a way that never happened before, and its important feature is to share photos and events with friends and family. However, there are risks associated with posting pictures on social media by unauthorized users. One of these risks is the privacy violation, where the published pictures can reveal more details and personal information. Since this issue has not yet investigated, this paper thus evaluates a methodology to address this issue, which is a precedent of its kind. In particular, our methodology relies on effective systems for detecting faces and recognizing faces in published images using facial recognition techniques. To evaluate the proposed idea, we developed an application using convolutional neural network (CNN) and the results showed that the proposed methodology can protect privacy and reduce its violation on online social networks.

Keywords

• online social networking
• protecting privacy
• facial recognition
• convolutional neural network
• photo sharing
• machine learning