Denial-of-service threat to hadoop/YARN clusters with multi-tenancy

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

Abstract

This paper studies the vulnerability of unconstrained computing resources in Hadoop and the threat of denial-of-service to a Hadoop cluster with multitenancy. We model the problem of how many nodes in a Hadoop cluster can be invaded by a malicious user with given allocated capacity as a k-ping-pong balls to n-boxes problem, and solve the problem by simulation. We construct a discrete event simulation model to estimate MapReduce job completion time in a Hadoop cluster under a DoS attack. Our study shows that even a small amount of compromised capacity may be used to launch a DoS attack and cause significant impacts on the performance of a Hadoop/YARN cluster.

Original languageEnglish (US)
Title of host publicationProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014
EditorsPeter Chen, Peter Chen, Hemant Jain
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages48-55
Number of pages8
ISBN (Electronic)9781479950577
DOIs
StatePublished - Sep 22 2014
Event3rd IEEE International Congress on Big Data, BigData Congress 2014 - Anchorage, United States
Duration: Jun 27 2014Jul 2 2014

Publication series

NameProceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014

Other

Other3rd IEEE International Congress on Big Data, BigData Congress 2014
CountryUnited States
CityAnchorage
Period6/27/147/2/14

Keywords

  • Big Data
  • Hadoop
  • MapReduce
  • YARN
  • denial-of-service attacks
  • multitenancy
  • security

ASJC Scopus subject areas

  • Computer Science Applications

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  • Cite this

    Huang, J., Nicol, D. M., & Campbell, R. H. (2014). Denial-of-service threat to hadoop/YARN clusters with multi-tenancy. In P. Chen, P. Chen, & H. Jain (Eds.), Proceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014 (pp. 48-55). [6906760] (Proceedings - 2014 IEEE International Congress on Big Data, BigData Congress 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.Congress.2014.17