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.
| Original language | English (US) |
|---|---|
| Title of host publication | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST |
| Publisher | Springer Verlag |
| Pages | 55-72 |
| Number of pages | 18 |
| DOIs | |
| State | Published - Jan 1 2015 |
Publication series
| Name | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST |
|---|---|
| Volume | 152 |
| ISSN (Print) | 1867-8211 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
Cite this
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Policy driven node selection in mapreduce. / Squicciarini, Anna C.; Lin, Dan; Sundareswaran, Smitha; Li, Jingwei.
Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST. Springer Verlag, 2015. p. 55-72 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 152).Research output: Chapter in Book/Report/Conference proceeding › Chapter
TY - CHAP
T1 - Policy driven node selection in mapreduce
AU - Squicciarini, Anna C.
AU - Lin, Dan
AU - Sundareswaran, Smitha
AU - Li, Jingwei
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84948174821&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84948174821&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-23829-6_5
DO - 10.1007/978-3-319-23829-6_5
M3 - Chapter
AN - SCOPUS:84948174821
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 55
EP - 72
BT - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
PB - Springer Verlag
ER -