Paper Info
Title
An Integrated Methodology for Big Data Classification and Security for Improving Cloud Systems Data Mobility.
Abstract
The expand trend of cloud data mobility led to malicious data threats that necessitate using data protection techniques. Most cloud system applications contain valuable and confidential data, such as personal, trade, or health information. Threats on such data may put the cloud systems that hold these data at high risk. However, traditional security solutions are not capable of handling the security of big data mobility. The current security mechanisms are insufficient for big data due to their shortage of determining the data that should be protected or due to their intractable time complexity. Therefore, the demand for securing mobile big data has been increasing rapidly to avoid any potential risks. This paper proposes an integrated methodology to classify and secure big data before executing data mobility, duplication, and analysis. The necessity of securing big data mobility is determined by classifying the data according to the risk impact level of their contents into two categories; confidential and public. Based on the classification category, the impact of data security is studied and substantiated on the confidential data in the scope of Hadoop Distributed File System. It is revealed that the proposed approach can significantly improve the cloud systems data mobility.
Year
DOI
Venue
2019
10.1109/ACCESS.2018.2890099
IEEE ACCESS
Keywords
Field
DocType
TERMS Big data classification,data security,metadata,risk impact level,HDFS
Distributed File System,Metadata,Data security,Confidentiality,Computer science,Computer security,Data Protection Act 1998,Time complexity,Big data,Distributed computing,Cloud computing
Journal
Volume
ISSN
Citations 
7
2169-3536
1
PageRank 
References 
Authors
0.35
0
4
Name
Order
Citations
PageRank
Ismail Omar Hababeh1133.33
Ammar Gharaibeh2825.71
Samer Nofal3544.85
Issa Khalil456538.01