Social network privacy measurement and simulation

• Published in: 2014 International Conference on Computing, Networking and Communications (ICNC) pp. 802 - 806
• Main Authors: Yong Wang, Nepali, Raj Kumar, Nikolai, Jason
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.02.2014
• Subjects: Data privacy; Indexes; Numerical models; Privacy; privacy index; privacy measurement; Sensitivity; simulation; Social network services; social networks; SONET
• DOI: 10.1109/ICCNC.2014.6785440

Privacy has become an important concern in online social networks. One of the fundamental challenging issues is privacy measurement. Without a practical and effective way to quantify, measure and evaluate privacy, it is hard for social networking sites and users to make and adjust privacy settings to protect privacy. In this paper, we introduce a practical and effective approach for privacy measurement in social networks. We use Privacy Index (PIDX) to measure a user's privacy exposure in a social network. PIDX is a numerical value between 0 and 100. High PIDX value indicates high privacy risk in social networks. A privacy index function PIDX(i, j) is proposed to evaluate actor A j 's privacy exposure to actor A j . Using this model, it is convenient to evaluate any users' privacy exposure to their friends, friends of friends, and public. We further develop a social network privacy simulation tool, OSNPIDX, to verify the effectiveness of our approach.