VIP Blowfish Privacy in Communication Graphs

Nassar, Mohamed; Chicha, Elie; Bouna, Béchara Al; Chbeir, Richard

doi:10.5220/0009875704590467

Proceedings of the 17th International Joint Conference on E-Business and Telecommunications 2020

DOI: 10.5220/0009875704590467

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VIP Blowfish Privacy in Communication Graphs

Mohamed Nassar

Elie Chicha

Béchara Al Bouna

et al.

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2021

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“…Thus, the BP mechanism returns a noisy data set instead of a query result. The BP mechanism will generate the noisy version of the released graphs [41] under a privacy guarantee called (ϵ, δ )-BP.…”

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confidence: 99%

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

Chicha

Bouna

Nassar

et al. 2021

ACM Trans. Internet Technol.

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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.

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confidence: 99%

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

Chicha

Bouna

Nassar

et al. 2021

ACM Trans. Internet Technol.

Self Cite

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Exposing safe correlations in transactional datasets

Chicha

Bouna

Wünsche

et al. 2021

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VIP Blowfish Privacy in Communication Graphs

Cited by 2 publications

References 0 publications

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

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

Exposing safe correlations in transactional datasets

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