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Online social network users share their information in different social sites to establish connections with individuals with whom they want to be a friend. While users share all their information to connect to other individuals, they need to hide the information that can bring about privacy risks for them. As user participation in social networking sites rises, the possibility of sharing information with unknown users increases, and the probability of privacy breaches for the user mounts. This work addresses the challenges of sharing information in a safe manner with unknown individuals. Currently, there are a number of available methods for preserving privacy in order to friending (the act of adding someone as a friend), but they only consider a single source of data and are more focused on users’ security rather than privacy. Consequently, a privacy-preserving friending mechanism should be considered for information shared in multiple online social network sites. In this paper, we propose a new privacy-preserving friending method that helps users decide what to share with other individuals with the reduced risk of being exploited or re-identified. In this regard, the first step is to calculate the sensitivity score for individuals using Bernstein’s polynomial theorem to understand what sort of information can influence a user’s privacy. Next, a new model is applied to anonymise the data of users who participate in multiple social networks. Anonymisation helps to understand to what extent a piece of information can be shared, which allows information sharing with reduced risks in privacy. Evaluation indicates that measuring the sensitivity of information besides anonymisation provides a more accurate outcome for the purpose of friending, in a computationally efficient manner.

Item Type:	Refereed Article
Keywords:	online privacy, social networks, sensitivity measurement, privacy risk, friending, information sharing
Research Division:	Information and Computing Sciences
Research Group:	Information systems
Research Field:	Information systems not elsewhere classified
Objective Division:	Health
Objective Group:	Evaluation of health and support services
Objective Field:	Health policy evaluation
UTAS Author:	Aghasian, E (Mr Erfan Aghasian)
UTAS Author:	Garg, S (Dr Saurabh Garg)
UTAS Author:	Montgomery, J (Dr James Montgomery)
ID Code:	127764
Year Published:	2018
Web of Science® Times Cited:	3
Deposited By:	Information and Communication Technology
Deposited On:	2018-08-14
Last Modified:	2019-02-26
Downloads:	87 View Download Statistics