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Cyber Attacks on MapReduce Computation Time in a Hadoop Cluster

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Big Data Concepts, Theories, and Applications

Abstract

In this chapter, we addressed the security issue in a Hadoop cluster when some nodes are compromised. We investigated the impact of attacks on the completion time of a MapReduce job when a node is compromised in a Hadoop cluster. We studied three attack methods: (1) blocking all incoming data from the master node except for the special messages that relay the status of the slave node, (2) delaying the delivery of packets that are sent to the master node, and performing an attack such as denial-of-service attack against the master node. To understand the impact of these attacks, we implemented them on different cluster settings that consist of three, six, and nine slave nodes and a single mater node in our testbed. Our data shows these attacks can affect the performance of MapReduce by increasing the computing time of MapReduce jobs.

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Acknowledgement

This work was also supported in part by US National Science Foundation (NSF) under grants: CNS 1117175 and 1350145. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.

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Authors and Affiliations

  1. Department of Computer and Information Sciences, Towson University, Towson, MD, 21252, USA

    William Glenn & Wei Yu

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  1. William Glenn
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  2. Wei Yu
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Correspondence to Wei Yu .

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Editors and Affiliations

  1. School of Information Technology, Deakin University, Burwood, Victoria, Australia

    Shui Yu

  2. Schl of Comp Science & Engg, The Univ of Aizu, Aizu-Wakamatsu City, Japan

    Song Guo

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Glenn, W., Yu, W. (2016). Cyber Attacks on MapReduce Computation Time in a Hadoop Cluster. In: Yu, S., Guo, S. (eds) Big Data Concepts, Theories, and Applications . Springer, Cham. https://doi.org/10.1007/978-3-319-27763-9_7

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  • DOI: https://doi.org/10.1007/978-3-319-27763-9_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27761-5

  • Online ISBN: 978-3-319-27763-9

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