Abstract
We consider scenarios in which two parties, each in possession of a graph, wish to compute some algorithm on their joint graph in a privacy-preserving manner, that is, without leaking any information about their inputs except that revealed by the algorithm’s output.
Working in the standard secure multi-party computation paradigm, we present new algorithms for privacy-preserving computation of APSD (all pairs shortest distance) and SSSD (single source shortest distance), as well as two new algorithms for privacy-preserving set union. Our algorithms are significantly more efficient than generic constructions. As in previous work on privacy-preserving data mining, we prove that our algorithms are secure provided the participants are “honest, but curious.”
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Brickell, J., Shmatikov, V. (2005). Privacy-Preserving Graph Algorithms in the Semi-honest Model. In: Roy, B. (eds) Advances in Cryptology - ASIACRYPT 2005. ASIACRYPT 2005. Lecture Notes in Computer Science, vol 3788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11593447_13
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DOI: https://doi.org/10.1007/11593447_13
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