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dc.contributor.advisorKragh, Frank E.
dc.contributor.advisorScrofani, James W.
dc.contributor.authorBrida, Benjamin J.
dc.date.accessioned2018-08-24T22:34:47Z
dc.date.available2018-08-24T22:34:47Z
dc.date.issued2018-06
dc.identifier.urihttp://hdl.handle.net/10945/59618
dc.descriptionApproved for public release. distribution is unlimiteden_US
dc.description.abstractConventional single node packet analyzers are unable to monitor network traffic at scale. In this thesis, elements of the Apache Hadoop ecosystem, including HBase, Spark, and MapReduce, are employed to conduct network traffic analysis on a large collection of network traffic. Limited analysis is conducted directly on packet capture next generation (pcapng) files on the Hadoop Distributed File System (HDFS) using MapReduce. Next, to allow for repeated analysis on the same dataset without reading all source files in their entirety for every calculation, pcapng files are parsed and relevant meta-data is bulk loaded into HBase, a Not Only Structured Query Language (NoSQL) database employing the HDFS for parallelization. This NoSQL database is then accessed via Apache Spark where pertinent data is loaded into DataFrames and additional analysis on the network traffic takes place. This research demonstrates the viability of custom, modular, automated analytics, employing open-source software to enable parallelization, to conduct traffic analysis at scale.en_US
dc.publisherMonterey, CA; Naval Postgraduate Schoolen_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleCLUSTER COMPUTING FOR AUTOMATED NETWORK ANALYSIS AT SCALEen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineering (ECE)
dc.subject.authorbig dataen_US
dc.subject.authorMapReduceen_US
dc.subject.authorHadoopen_US
dc.subject.authorpacket captureen_US
dc.subject.authortraffic analysisen_US
dc.subject.authornetwork analysisen_US
dc.subject.authorSparken_US
dc.subject.authorHBaseen_US
dc.description.serviceCaptain, United States Marine Corpsen_US
etd.thesisdegree.nameMaster of Science in Electrical Engineeringen_US
etd.thesisdegree.levelMastersen_US
etd.thesisdegree.disciplineElectrical Engineeringen_US
etd.thesisdegree.grantorNaval Postgraduate Schoolen_US
dc.identifier.thesisid29276


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