DocumentCode
3039033
Title
Preserving Privacy in MapReduce Based Clouds: Insight into Frameworks and Approaches
Author
Al-Aqeeli, Shaden ; Alnifie, Ghada
Author_Institution
Dept. of Comput. Sci., King Saud Univ., Riyadh, Saudi Arabia
fYear
2015
fDate
26-29 April 2015
Firstpage
1
Lastpage
7
Abstract
The massive increase in computational power and data storage capacity provided by Cloud Computing as well as the vast amount of data generated each day have provided many organizations, businesses and authorities with more opportunities due to the advancement in data analysis and mining techniques. A serious problem is that Big Data includes sensitive user information that cannot be released to the cloud without proper protection because of multi-tenancy issues and threats. Privacy preservation of big data has been under intensive investigation with many different approaches proposed. In this paper, we focus on the research challenges of the privacy-preserving problem in the context of cloud computing and we survey existing solution approaches. Furthermore, a review of different existing MapReduce based frameworks will be presented and investigated against the research challenges identified in this paper.
Keywords
Big Data; cloud computing; data analysis; data mining; data privacy; Big Data privacy preservation; MapReduce based cloud computing; data analysis; data mining techniques; multitenancy issues; Big data; Cloud computing; Computational modeling; Data privacy; Organizations; Privacy;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing (ICCC), 2015 International Conference on
Conference_Location
Riyadh
Print_ISBN
978-1-4673-6617-5
Type
conf
DOI
10.1109/CLOUDCOMP.2015.7149652
Filename
7149652
Link To Document