Review: An evaluation of major threats in cloud computing associated with big data

Research output: Book chapter/Published conference paperConference paperpeer-review

7 Citations (Scopus)

Abstract

In today's corporate society, the productivity, stability, and management of an organization relies upon the power of databases. Most organizations outsource their databases in the form of big data and then transfer it into cloud. Although cloud computing technology brings many benefits for an organization, their security risk factor still remains as a big barrier for its wide-spread adoption. Therefore, this problem poses a critical question such as: Is information secure in cloud? Due to this uncertainty, the primary aim of this study is to describe and identify most vulnerable aspects of security threats in cloud environment through content analysis and highlight and evaluate gaps in the literature to draw scholarly attention. This paper analyzed content to source data that helps to identify gaps in the literature. These gaps then have been identified and evaluated to answer questions with possible solutions. This research will help both vendors and users about security issues that have been heightened with recent population advancements and demands that have been pointed out for improvement. This study has reviewed literature in the field over the sp an of six years, and endeavors to seek answers for the question and cast solutions through thorough evaluation and analysis: the security related issues in cloud computing associated with big data must be taking into account by security practitioners when assessing the needs of service providers. This study has found that cloud environment is an innovation, and the blend of parallel computing and cloud computing can offer various advantages. It is ideal for different kinds of applications that can suit different needs if expenses of application modifications consolidate the cost of setup and maintenance of cloud computing. This study has analyzed content and has also found that management solution of only one big secure data after integrating it with cloud needs yet to be designed.
Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA 2017)
Place of PublicationUnited States
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages368-372
Number of pages5
ISBN (Electronic)9781509036196
ISBN (Print)9781509036189, 9781509036202
DOIs
Publication statusPublished - 23 Oct 2017
Event2nd IEEE International Conference on Big Data Analysis: ICBDA 2017 - Beijing Post Hotel, Beijing, China
Duration: 10 Mar 201712 Mar 2017
https://web.archive.org/web/20161110104944/http://www.icbda.org/index.html (Conference website)
http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8053962 (Conference proceedings)

Conference

Conference2nd IEEE International Conference on Big Data Analysis
CountryChina
CityBeijing
Period10/03/1712/03/17
OtherIn recent years, "Big Data" has become a new ubiquitous term. Big Data is transforming science, engineering, medicine, healthcare, finance, business, and ultimately society itself. The 2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA 2017) provides a leading forum for disseminating the latest research in Big Data Research, Development, and Application. ICBDA1017 is co-organized by IEEE and Research Institute of Big Data Analytics, Xi'an Jiaotong-Liverpool University, China. Assisted by University of Texas at Dallas, USA. Prof. Steven Guan (Xi'an Jiaotong-Liverpool University, China) and Prof. Kang Zhang (University of Texas at Dallas, USA) take charge of the Conference Co-chair.
Internet address

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