OpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems

Handle URI:
http://hdl.handle.net/10754/556722
Title:
OpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems
Authors:
Fabiano, Enrico; Seo, Mookwon; Wu, Xiaoban; Douglas, Craig C.
Abstract:
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.
KAUST Department:
SRI-Center for Numerical Porous Media
Citation:
OpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems 2015, 51:1675 Procedia Computer Science
Journal:
Procedia Computer Science
Issue Date:
1-Jun-2015
DOI:
10.1016/j.procs.2015.05.302
Type:
Article
ISSN:
18770509
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S1877050915011102
Appears in Collections:
Articles; Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorFabiano, Enricoen
dc.contributor.authorSeo, Mookwonen
dc.contributor.authorWu, Xiaobanen
dc.contributor.authorDouglas, Craig C.en
dc.date.accessioned2015-06-10T18:39:59Zen
dc.date.available2015-06-10T18:39:59Zen
dc.date.issued2015-06-01en
dc.identifier.citationOpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systems 2015, 51:1675 Procedia Computer Scienceen
dc.identifier.issn18770509en
dc.identifier.doi10.1016/j.procs.2015.05.302en
dc.identifier.urihttp://hdl.handle.net/10754/556722en
dc.description.abstractThe 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.en
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1877050915011102en
dc.rightsArchived with thanks to Procedia Computer Science, Under a Creative Commons license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectBig dataen
dc.subjectDDDASen
dc.subjectDynamic data driven applicationsen
dc.subjectDynamic data driven applicationsen
dc.subjectHPCen
dc.subjectOpen source softwareen
dc.subjectCybersecurityen
dc.subjectHIPAAen
dc.titleOpenDBDDAS Toolkit: Secure MapReduce and Hadoop-like Systemsen
dc.typeArticleen
dc.contributor.departmentSRI-Center for Numerical Porous Mediaen
dc.identifier.journalProcedia Computer Scienceen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionUniversity of Wyoming, Laramie, WY, U.S.A.en
kaust.authorDouglas, Craig C.en
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