Privometer: Privacy protection in social networks

Abstract

Abstract-The increasing popularity of social networks, such as Facebook and Orkut, has raised several privacy concerns. Traditional ways of safeguarding privacy of personal information by hiding sensitive attributes are no longer adequate. Research shows that probabilistic classification techniques can effectively infer such private information. The disclosed sensitive information of friends, group affiliations and even participation in activities, such as tagging and commenting, are considered background knowledge in this process. In this paper, we present a privacy protection tool, called Privometer, that measures the amount of sensitive information leakage in a user profile and suggests selfsanitization actions to regulate the amount of leakage. In contrast to previous research, where inference techniques use publicly available profile information, we consider an augmented model where a potentially malicious application installed in the user's friend profiles can access substantially more information. In our model, merely hiding the sensitive information is not sufficient to protect the user privacy. We present an implementation of Privometer in Facebook.

Danger Theory-based Privacy Protection Model for Social Networks

“…User-related privacy issues are generally caused by limited or lack of privacy control functionality support from service providers of SNS for their users [2], [3]. When SNS services provide a convenient platform for users to freely share information, individual user's sensitive information may be revealed by a user itself and freely accessed by other SNS users or even anonymous attackers.…”

“…According to Ho et al [1], SNS is a website that provides a virtual community for people with similar interests in particular subject, or just to "hangout" together. Based on the definition of SNS, people can use SNS services to share information, thoughts and feelings, chat with other users, play online games with other users, and even promote their own businesses to other users [2]- [5]. The rapid growth and huge amount of service usage of SNS show that SNS has taken a significant role on communication media and culture among people in modern societies.…”

“…Facebook provides a set of rules to protect its user's privacy [2], and it allows its users to determine who can access and see information shared by individual user. However, these rules cannot protect sensitive information shown within shared messages.…”

Detecting and resolving privacy conflicts for collaborative data sharing in online social networks

“…Measuring privacy risk in OSNs has been addressed recently by several work [6,20,23]. Becker et al [6] presented PrivAware, a tool to detect and report unintended information loss through quantifying privacy risk associated with friend relationship in OSNs.…”

“…Becker et al [6] presented PrivAware, a tool to detect and report unintended information loss through quantifying privacy risk associated with friend relationship in OSNs. In [23], Talukder et al discussed a privacy protection tool, called Privometer, which can measure the risk of potential privacy leakage cased by malicious applications installed in the user's friend profiles and suggest self-sanitization actions to lessen this leakage accordingly. Liu et al [20] proposed a framework to compute the privacy score of a user, indicating the user's potential risk caused by her/his participation in OSNs.…”