ZTE

ZTE Communications ›› 2016, Vol. 14 ›› Issue (S0): 2-9.doi: 10.3969/j.issn.1673-5188.2016.S0.001

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Attacks and Countermeasures in Social Network Data Publishing

YANG Mengmeng, ZHU Tianqing, ZHOU Wanlei, XIANG Yang   

  1. School of Information Technology,Deakin University,Burwood,VIC 3125,Australia
  • Received:2016-02-17 Online:2016-06-01 Published:2019-11-29
  • About author:YANG Mengmeng (ymengm@deakin.edu.au) received her BE from Qingdao Agricultural University, China in 2007, and M.Eng from Shenyang Normal University, China in 2014. She is currently a PhD candidate in the School of Information Technology, Deakin University, Australia. Her research interests include privacy preserving, network security and machine learning.
    ZHU Tianqing (t.zhu@deakin.edu.au) received her BE and ME degrees fromWuhan University, China, in 2000 and 2004, respectively, and a PhD degree from Deakin University in Computer Science, Australia, in 2014. She is currently a continuing teaching scholar in the School of Information Technology, Deakin University, Australia. Her research interests include privacy preserving, data mining and network security. She has won the best student paper award in PAKDD 2014.
    ZHOU Wanlei (wanlei.zhou@deakin.edu.au) received his BE and ME degrees from Harbin Institute of Technology, China in 1982 and 1984, respectively, and a PhD degree from The Australian National University, Australia, in 1991, all in Computer Science and Engineering. He also received a DSc degree from Deakin University in 2002. He is currently the Alfred Deakin Professor and Chair Professor in Information Technology, School of Information Technology, Deakin University. His research interests include distributed systems, network security, bioinformatics, and e?learning. Professor Zhou has published more than 300 papers in refereed international journals and refereed international conferences proceedings, including over 30 articles in IEEE journal in the last 5 years.
    XIANG Yang (yang.xiang@deakin.edu.au) received his PhD in Computer Science from Deakin University, Australia. He is the Director of Centre for Cyber Security Research, Deakin University. He is the Chief Investigator of several projects in network and system security, funded by the Australian Research Council (ARC). His research interests include network and system security, data analytics, distributed systems, and networking. He has published more than 200 research papers in many international journals and conferences. Two of his papers were selected as the featured articles in the April 2009 and the July 2013 issues of IEEE Transactions on Parallel and Distributed Systems. Two of his papers were selected as the featured articles in the Jul/Aug 2014 and the Nov/Dec 2014 issues of IEEE Transactions on Dependable and Secure Computing.

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Abstract: With the increasing prevalence of social networks, more and more social network data are published for many applications, such as social network analysis and data mining. However, this brings privacy problems. For example, adversaries can get sensitive information of some individuals easily with little background knowledge. How to publish social network data for analysis purpose while preserving the privacy of individuals has raised many concerns. Many algorithms have been proposed to address this issue. In this paper, we discuss this privacy problem from two aspects: attack models and countermeasures. We analyse privacy concerns, model the background knowledge that adversary may utilize and review the recently developed attack models. We then survey the state-of-the-art privacy preserving methods in two categories: anonymization methods and differential privacy methods. We also provide research directions in this area.

Key words: social network, data publishing, attack model, privacy preserving