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Notes on Privacy-preserving Distributed Mining and Hamiltonian Cycles

Distributed storage and retrieval of data is both the norm and a necessity in today’s computing environment. However, sharing and dissemination of this data is subject to privacy concerns. This paper addresses the role of graph theory, especially Hamiltonian cycles, on privacy preserving algorithms for mining distributed data. We propose a new heuristic algorithm for discovering disjoint Hamiltonian cycles in the underlying network. Disjoint Hamiltonian cycles are useful in a number of applications; for example, to ensure that someone’s private data remains private even when others collude to discover the data.