A User-Centric Mechanism for Sequentially Releasing Graph Datasets under Blowfish Privacy

Elie Chicha, Bechara Al Bouna, Mohamed Nassar, Richard Chbeir, Ramzi A. Haraty, Mourad Oussalah, Djamal Benslimane, Mansour Naser Alraja

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


In this article, we present a privacy-preserving technique for user-centric multi-release graphs. Our technique consists of sequentially releasing anonymized versions of these graphs under Blowfish Privacy. To do so, we introduce a graph model that is augmented with a time dimension and sampled at discrete time steps. We show that the direct application of state-of-the-art privacy-preserving Differential Private techniques is weak against background knowledge attacker models. We present different scenarios where randomizing separate releases independently is vulnerable to correlation attacks. Our method is inspired by Differential Privacy (DP) and its extension Blowfish Privacy (BP). To validate it, we show its effectiveness as well as its utility by experimental simulations.

Original languageEnglish
Article number20
Pages (from-to)1-25
Number of pages25
JournalACM Transactions on Internet Technology
Issue number1
Publication statusPublished - 17 Feb 2021
Externally publishedYes

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