Policy Driven Node Selection in Mapreduce
Abstract
The MapReduce framework has been widely adopted for processing Big Data in the cloud. While efficient, MapReduce offers very complicated (if any) means for users to request nodes that satisfy certain security and privacy requirements to process their data. In this paper, we propose a novel approach to seamlessly integrate node selection control to the MapReduce framework for increasing data security. We define a succinct yet expressive policy language for MapReduce environments, according to which users can specify their security and privacy concerns over their data. Then, we propose corresponding data preprocessing techniques and node verification protocols to achieve strong policy enforcement. Our experimental study demonstrates that, compared to the traditional MapReduce framework, our policy control mechanism allows to achieve data privacy without introducing significant overhead.
Recommended Citation
A. C. Squicciarini et al., "Policy Driven Node Selection in Mapreduce," Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 152, pp. 55 - 72, Springer, Jan 2015.
The definitive version is available at https://doi.org/10.1007/978-3-319-23829-6_5
Department(s)
Computer Science
Keywords and Phrases
Access control; MapReduce; Node selection
International Standard Serial Number (ISSN)
1867-8211
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Jan 2015
Comments
National Science Foundation, Grant 1250319