VIP Blowfish Privacy in Communication Graphs

Mohamed Nassar, Elie Chicha, Bechara Al Bouna, Richard Chbeir


Communication patterns analysis is becoming crucial for global health security especially with the spread of epidemics such as COVID-19 by the means of social contact. At the same time, personal privacy is considered an essential human right. Privacy-preserving frameworks enable communication graph analysis within formal privacy guarantees. In this paper, we present a summary of Blowfish privacy and explore the possibility of applying it in the context of undirected communication graphs. Communication graphs represent social contact or call detail records databases. We define the notions of neighborhood, discriminative secrets, and policies for these graphs. We study several examples of queries and compute their sensitivity. Even though not addressed in the original Blowfish privacy paper, we explore the idea of having a discriminative secret graph per individual. This allows us to treat some persons as VIP and put their privacy on top priority, where other persons can have lower privacy constraints. This may help to offer privacy as a service and increase the utility of the anonymized communication graph to an appropriate level.


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