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Blockchain based approach to enhance big data authentication in distributed environment
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.
2017 (English)In: 2017 Ninth International Conference on Ubiquitous and Future Networks (ICUFN), IEEE Computer Society, 2017, p. 887-892Conference paper, Published paper (Refereed)
Abstract [en]

Existing authentication protocols for Big Data system such as Apache Hadoop is based on Kerberos. In the Kerberos protocol, there are numerous security issues that have remained unsolved; replay attacks, DDoS and single point of failure are some examples. These indicate potential security vulnerabilities and Big Data risks in using Hadoop. This paper presents drawbacks of Kerberos implementations and identifies authentication requirements that can enhance the security of Big Data in distributed environments. The enhancement proposed is based on the rising technology of blockchain that overcomes shortcomings of Kerberos.

Place, publisher, year, edition, pages
IEEE Computer Society, 2017. p. 887-892
Series
International Conference on Ubiquitous and Future Networks, ICUFN, ISSN 2165-8528
Keywords [en]
Authentication, Big Data, Blockchain, Distributed Network, Hadoop, Security
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kth:diva-213523DOI: 10.1109/ICUFN.2017.7993927ISI: 000425924400193Scopus ID: 2-s2.0-85028031113ISBN: 9781509047499 (print)OAI: oai:DiVA.org:kth-213523DiVA, id: diva2:1138001
Conference
9th International Conference on Ubiquitous and Future Networks, ICUFN 2017, Milan, Italy, 4 July 2017 through 7 July 2017
Note

QC 20170904

Available from: 2017-09-04 Created: 2017-09-04 Last updated: 2024-03-15Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf