OpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems

Enrico Fabiano, Mookwon Seo, Xiaoban Wu, Craig Douglas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations


The OpenDBDDAS Toolkit is a software framework to provide support for more easily creating and expanding dynamic big data-driven application systems (DBDDAS) that are common in environmental systems, many engineering applications, disaster management, traffic management, and manufacturing. In this paper, we describe key features needed to implement a secure MapReduce and Hadoop-like system for high performance clusters that guarantees a certain level of privacy of data from other concurrent users of the system. We also provide examples of a secure MapReduce prototype and compare it to another high performance MapReduce, MR-MPI.
Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier BV
Number of pages10
StatePublished - Jun 1 2015

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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