Analyzing and Evaluating Critical Challenges and Practices for Software Vendor Organizations to Secure Big Data on Cloud Computing: An AHP-Based Systematic Approach

Abudul Wahid Khan, Maseeh Ullah Khan, Javed Ali Khan, Arshad Ahmad, Khalil Khan, Muhammad Zamir, Wonjoon Kim, Muhammad Fazal Ijaz

Research output: Contribution to journalArticlepeer-review


Recently, its becomes easy to track down the data due to its availability in a large number. Although for data management, processing, and obtainability, cloud computing is considered a well-known approach for organizational development on the internet. Despite many advantages, cloud computing has still numerous security challenges that can affect the big-data usage on cloud computing. To find the security issues/challenges that are faced by software vendors' organizations we conducted a systematic literature review (SLR) through which we have find out 103 relevant research publications by developing a search string that is inspired by the research questions. This relevant data was comprised from different databases e.g. Google Scholar, IEEE Explore, ScienceDirect, ACM Digital Library, and SpringerLink. Furthermore, for the detailed literature review, we have accomplished all the steps in SLR, for example, development of SLR protocol, Initials and final assortment of the relevant data, data extraction, data quality assessment, and data synthesis. We identified fifteen (15) critical security challenges which are: data secrecy, geographical data location, unauthorized data access, lack of control, lack of data management, network-level issues, data integrity, data recovery, lack of trust, data sharing, data availability, asset issues, legal amenabilities, lack of quality, and lack of consistency. Furthermore, sixty four (64) standard practices are identified for these critical security challenges using the proposed SLR that could help vendor organizations to overcome the security challenges for big data. The findings of our research study demonstrate the resemblances and divergences in the identified security challenges in different periods, continents, databases, and methods. The proposed SLR will also support software vendor organizations for securing big data on the cloud computing platforms. This paper has the following content: in Section II, we have describe the Literature review; in Section III, research methodology is specified; in Section IV, the findings of the SLR and the analysis of result are discussed; in Section V, the limitations of this research are given; in Section VI, we discussed our conclusions and future work.

Original languageEnglish
Article number9496639
Pages (from-to)107309-107332
Number of pages24
JournalIEEE Access
Publication statusPublished - 2021
Externally publishedYes


  • big data
  • cloud computing
  • Security challenges
  • SLR
  • SPSS
  • vendor


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