Research on Cloud Computing and Network Security in Digital Manufacturing Platform

Chang, Zhen Yun; Zhao, Yu; Qian, Dong Mei; Wang, Ning

doi:10.4028/www.scientific.net/amm.484-485.219

Cited by 3 publications

(3 citation statements)

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“…We have found the key differences for the issues of 'Un-authorized data access issue', 'Legal Amenabilities', and 'Assets issues' across different databases. Below is the table for identified challenges through SLR across various databases [8,12,25,35,42,43].…”

Section: A) Practices To Enhance Data Secrecy Issuementioning

confidence: 99%

“…Trust issue: Cloud computing have a trust issue because the storage location of data not the same as that of customer, moreover customer has no idea of their critical data and its security. So that's why customer do not trust on cloud computing and refer to store their personal data on their own system at home instead of cloud environment [8,12,25,35,42,43]. Technical Network issue: In cloud computing data communication occur through unsecured network such as Internet, where every node can easily change data or inter node communication so that to breach the entire connection of the system [16,42,44,45].…”

Section: Introductionmentioning

confidence: 99%

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

Khan

et al. 2021

IEEE Access

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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.

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Section: A) Practices To Enhance Data Secrecy Issuementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Khan

et al. 2021

IEEE Access

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“…Data loss issue: When data loss occurred in a cloud environment due to any reason, then it is impossible to completely recover all the deleted data as some of the data will be eternally deleted, and also finding an exact node of data loss for retrieval is not an easy task in the cloud computing 15,26,31,36,37 …”

Section: Literature Reviewmentioning

confidence: 99%

Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach

Khan

et al. 2021

J Software Evolu Process

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Nowadays, data is increasing exponentially, although cloud computing is an eminent approach for the organization, processing, and availability of data for organizational growth over the internet. Besides, a lot of advantages of cloud computing, yet it is suffered from security challenges, which affect big data while using cloud services on the internet. For this purpose, we conducted a detailed systematic literature review (SLR) study, to identify and capture the security challenges of big data on the cloud computing platform. Our research findings determine and develop a taxonomy, based on the prioritization of the security challenges of big data on cloud computing. We identified a total of 15 critical security challenges using the proposed SLR, with the frequency of each challenge >25%, and are further validated by the industrial specialists using a questionnaire survey study. The identified security challenges are data secrecy issue, geographical data location issue, unauthorized data access issue, lack of control, lack of data management, network‐level issues, data integrity issue, data recovery issue, lack of trust, data sharing issue, data availability, asset issues, legal amenabilities, lack of quality issues, and lack of consistency. The security challenges identified and captured through the SLR study are categorized into four levels, namely, steadiness, management, control, and eminence. Conclusively, we applied the fuzzy‐TOPSIS approach to prioritize and identify the significance of each identified security challenge for the big data usage on cloud computing. Based on our proposed approach, the “data secrecy issue” has been identified as the most prominent security challenge with the captured value of “0.765.” The fuzzy TOPSIS is an effective and innovative research approach in the field of computer science. It has been applied positively to other research areas to address and identify the fuzziness and uncertainty of multiple decision‐making glitches. The findings of the research paper will assist the software vendor organization when using the cloud platform for big data security. Also, using the proposed approach, software vendors can prioritize and analyze the uncertainty and ambiguousness among these security challenges.

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Design and Application of Cloud Platform for Digital Party Building in Universities

Zhang

Honglian

2021

2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

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Research on Cloud Computing and Network Security in Digital Manufacturing Platform

Cited by 3 publications

References 0 publications

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

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

Identification and prioritization of security challenges of big data on cloud computing based on SLR: A fuzzy‐TOPSIS analysis approach

Design and Application of Cloud Platform for Digital Party Building in Universities

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