A security framework in G-Hadoop for big data computing across distributed Cloud data centres
Date
2014
Authors
Zhao, Jiaqi
Wang, Lizhe
Tao, Jie
Chen, Jinjun
Sun, Weiye
Ranjan, Rajiv
Kolodziej, Joanna
Streit, Achim
Georgakopoulos, Dimitrios
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Academic Press
Abstract
MapReduce is regarded as an adequate programming model for large-scale data-intensive applications. The Hadoop framework is a well-known MapReduce implementation that runs the MapReduce tasks on a cluster system. G-Hadoop is an extension of the Hadoop MapReduce framework with the functionality of allowing the MapReduce tasks to run on multiple clusters. However, G-Hadoop simply reuses the user authentication and job submission mechanism of Hadoop, which is designed for a single cluster. This work proposes a new security model for G-Hadoop. The security model is based on several security solutions such as public key cryptography and the SSL protocol, and is dedicatedly designed for distributed environments. This security framework simplifies the users authentication and job submission process of the current G-Hadoop implementation with a single-sign-on approach. In addition, the designed security framework provides a number of different security mechanisms to protect the G-Hadoop system from traditional attacks.
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Journal of Computer and System Sciences
Type
Journal article
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2037-12-31