Protecting privacy against bribery/coercion is a necessary requirement in electronic services, like e-voting, e-auction and e-health. Domain-specific privacy properties have been proposed to capture this. We generalise these properties as enforced privacy: a system enforces a user's privacy even when the user collaborates with the adversary. In addition, we account for the influence of third parties on a user's privacy. Third parties can help to break privacy by collaborating with the adversary, or can help to protect privacy by cooperating with the target user. We propose independency of privacy to capture the negative privacy impact that third parties can have, and coalition privacy to capture their positive privacy impact. We formally define these privacy notions in the applied pi calculus and build a hierarchy showing their relations. © 2013 Springer-Verlag.
CITATION STYLE
Dong, N., Jonker, H., & Pang, J. (2013). Enforcing privacy in the presence of others: Notions, formalisations and relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8134 LNCS, pp. 499–516). https://doi.org/10.1007/978-3-642-40203-6_28
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