SecSVA: Secure Storage, Verification, and Auditing of Big Data in the Cloud Environment
Aujla, G.
; Chaudhary, R.
; Kumar, N. K.
; Das, A. D.
;
Rodrigues, J. R.
IEEE Communications Magazine Vol. 56, Nº 1, pp. 78 - 85, January, 2018.
ISSN (print): 0163-6804
ISSN (online): 1558-1896
Scimago Journal Ranking: 2,37 (in 2018)
Digital Object Identifier: 10.1109/MCOM.2018.1700379
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Abstract
With the widespread popularity of Internet-enabled devices, there is an exponential increase in the information sharing among different geographically located smart devices. These smart devices may be heterogeneous in nature and may use different communication protocols for information sharing among themselves. Moreover, the data shared may also change with respect to var- ious Vs (volume, velocity, variety, and value) to categorize it as big data. However, as these devic- es communicate with each other using an open channel, the Internet, there is a higher chance of information leakage during communication. Most of the existing solutions reported in the literature ignore these facts. Keeping focus on these points, in this article, we propose secure storage, verification, and auditing (SecSVA) of big data in cloud environment. SecSVA includes the following modules: an attribute-based secure data deduplication framework for data storage on the cloud, Kerberos-based identity verification and authentication, and Merkle hash-tree-based trusted third-party auditing on cloud. From the analysis, it is clear that SecSVA can provide secure third party auditing with integrity preservation across multiple domains in the cloud environment.