A Privacy Measurement Framework for Multiple Online Social Networks against Social Identity Linkage

Abstract

Recently, the number of people who are members of multiple online social networks simultaneously has increased. However, if these people share everything with others, they risk their privacy. Users may be unaware of the privacy risks involved with sharing their sensitive information on a network. Currently, there are many research efforts focused on social identity linkage (SIL) on multiple online social networks for commercial services, which exacerbates privacy issues. Many existing studies consider methods of encrypting or deleting sensitive information without considering if this is unreasonable for social networks. Meanwhile, these studies ignore privacy awareness, which is rudimentary and critical. To enhance privacy awareness, we discuss a user privacy exposure measure for users who are members of multiple online social networks. With this measure, users can be aware of the state of their privacy and their position on a privacy measurement scale. Additionally, we propose a straightforward method through our framework to reduce information loss and foster user privacy awareness by using spurious content for required fields.

Keywords

• multiple social networks
• privacy security
• measurement
• profile
• social identity linkage
• attribute content