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Multilevel Threshold Secret Sharing Scheme to Secure MapReduce Computations in Cloud Computing Environment


Affiliations
1 School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India
 

Objectives: Cloud computing has evolved in recent days and is applied in various fields for effective resources and infrastructure in a distributed environment. Data analysis is the core functionality in cloud computing where large amount of data called Big Data is processed over clusters. Methods: MapReduce is one of the solutions for handling big data in the cloud environment because of its scalability and fault tolerance in a phased manner. Multiple data sets are joined to do complex data analysis for computation on certain aggregates. A common problem is whether MapReduce could be customized to get a scalable system, when the jobs are split and reduced. Also most of the systems do not consider the issue of security in MapReduce phases. Findings: The proposed solution uses multilevel threshold secret sharing to perform MapReduce operations providing secure processing. The solution extends MapReduce framework to improve security and also results in higher efficiency. The mechanism presents lower overhead costs when compared to the existing ones and has essential application in Big Data cloud environment. Applications: These approaches are lower cost and higher efficiency in cloud environment.

Keywords

Big Data, Cloud Computing, MapReduce, Security.
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  • Multilevel Threshold Secret Sharing Scheme to Secure MapReduce Computations in Cloud Computing Environment

Abstract Views: 186  |  PDF Views: 0

Authors

M. Eyalarasi
School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India
P. Shanthi
School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India
A. Umamakeswari
School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India

Abstract


Objectives: Cloud computing has evolved in recent days and is applied in various fields for effective resources and infrastructure in a distributed environment. Data analysis is the core functionality in cloud computing where large amount of data called Big Data is processed over clusters. Methods: MapReduce is one of the solutions for handling big data in the cloud environment because of its scalability and fault tolerance in a phased manner. Multiple data sets are joined to do complex data analysis for computation on certain aggregates. A common problem is whether MapReduce could be customized to get a scalable system, when the jobs are split and reduced. Also most of the systems do not consider the issue of security in MapReduce phases. Findings: The proposed solution uses multilevel threshold secret sharing to perform MapReduce operations providing secure processing. The solution extends MapReduce framework to improve security and also results in higher efficiency. The mechanism presents lower overhead costs when compared to the existing ones and has essential application in Big Data cloud environment. Applications: These approaches are lower cost and higher efficiency in cloud environment.

Keywords


Big Data, Cloud Computing, MapReduce, Security.



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i48%2F138487