Abstract
In the last decade, cloud infrastructures such as Google Cloud and Amazon AWS have grown vastly in scale and utilization. Therefore, research into the security and confidentiality of sensitive data passed through these infrastructures is of great importance. We present SecureMCMR, a system that utilizes two public clouds for privacy preserving computation outsourcing for MapReduce applications. We also present analysis of 87 MapReduce applications and the operations they use. Our results on three MapReduce applications show overhead of 160%, 254%, and 380% over plaintext execution.
Cite
CITATION STYLE
Kennard, L., & Milanova, A. (2020). SecureMCMR: Computation Outsourcing for MapReduce Applications. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12161 LNCS, pp. 143–166). Springer. https://doi.org/10.1007/978-3-030-49785-9_10
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