Networks entail vulnerable and sensitive information that pose serious privacy threats. In this paper, we introduce, k-core attack, a new attack model which stems from the k-core decomposition principle. K-core attack undermines the privacy of some state-of-the-art techniques. We propose a novel structural anonymization technique called (k, δ)-Core Anonymity, which harnesses the k-core attack and structurally anonymizes small and large networks. In addition, although real-world social networks are massive in nature, most existing works focus on the anonymization of networks with less than one hundred thousand nodes. (k, δ)-Core Anonymity is tailored for massive networks. To the best of our knowledge, this is the first technique that provides empirical studies on structural network anonymization for massive networks. Using three real and two synthetic datasets, we demonstrate the effectiveness of our technique on small and large networks with up to 1.7 million nodes and 17.8 million edges. Our experiments reveal that our approach outperforms a state-of-the-art work in several aspects.
|Title of host publication||Conference on Scientific and Statistical Database Management, SSDBM '14, Aalborg, Denmark, June 30 - July 02, 2014|
|Publication status||Published - 2014|
|Event||Conference on Scientific and Statistical Database Management, SSDBM '14, Aalborg, Denmark, June 30 - July 02, 2014 - Aalborg, Denmark|
Duration: 30 Jun 2014 → 2 Jul 2014
|Conference||Conference on Scientific and Statistical Database Management, SSDBM '14, Aalborg, Denmark, June 30 - July 02, 2014|
|Period||30/06/14 → 2/07/14|