Data-Oblivious Graph Algorithms in Outsourced External Memory
Michael T. Goodrich, Joseph A. Simons

TL;DR
This paper develops new data-oblivious algorithms for fundamental graph problems in outsourced external memory, enhancing privacy by hiding data access patterns without relying on random oracles.
Contribution
It introduces efficient data-oblivious algorithms for graph problems in outsourced external memory, addressing privacy concerns in data outsourcing scenarios.
Findings
New algorithms for minimum spanning trees in data-oblivious external memory
Efficient data-oblivious algorithms for tree traversals and LCA queries
Algorithms do not rely on constant-time random oracles
Abstract
Motivated by privacy preservation for outsourced data, data-oblivious external memory is a computational framework where a client performs computations on data stored at a semi-trusted server in a way that does not reveal her data to the server. This approach facilitates collaboration and reliability over traditional frameworks, and it provides privacy protection, even though the server has full access to the data and he can monitor how it is accessed by the client. The challenge is that even if data is encrypted, the server can learn information based on the client data access pattern; hence, access patterns must also be obfuscated. We investigate privacy-preserving algorithms for outsourced external memory that are based on the use of data-oblivious algorithms, that is, algorithms where each possible sequence of data accesses is independent of the data values. We give new efficient…
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Taxonomy
TopicsCryptography and Data Security · Privacy-Preserving Technologies in Data · Complexity and Algorithms in Graphs
