Challenges and Opportunities in Big Data and Cloud Computing

Hassan, Sohail; Zameer, Zeenia; Ahmed, Hafiz Farhan; Iqbal, Usama; Shah, Pir Amad Ali

doi:10.1007/978-3-319-51207-5_17

Cited by 3 publications

(4 citation statements)

References 6 publications

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“…That has led to the popularity of Analytics as a Service (AaaS) as a quicker and more effective method to connect, manipulate, and display various kinds of data. Data Analytics [11].…”

Section: Cloud Management For Massive Data Setsmentioning

confidence: 99%

Big Data in Cloud Computing: An Overview

Sharma¹,

Singh²,

Sharma³

et al. 2023

IJRASET

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Cloud computing is a potent tool for sophisticated and massive-scale computation. It removes the need for expensive hardware, specialized space, and software maintenance. It has been noticed that cloud computing has resulted in a massive increase in the volume of data, or big data. Managing massive amounts of data is a complex and time-consuming operation that requires an extensive computer infrastructure for effective data processing and analysis. Many industries, including minor and major organizations, healthcare, education, and many more, are attempting to harness the potential of big data. In healthcare, for example, big data is used to reduce treatment costs, predict pandemic outbreaks, and prevent infections, among other things. This article discusses comprehensive data processing strategies from system and application perspectives to offer an orderly picture of the issues that application developers and database management system (DBMS) designers face while designing and deploying internet-scale applications. While big data has various uses in various industries, it has challenges.

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“…That has led to the popularity of Analytics as a Service (AaaS) as a quicker and more effective method to connect, manipulate, and display various kinds of data. Data Analytics [11].…”

Section: Cloud Management For Massive Data Setsmentioning

confidence: 99%

Big Data in Cloud Computing: An Overview

Sharma¹,

Singh²,

Sharma³

et al. 2023

IJRASET

View full text Add to dashboard Cite

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“…Technical network‐level issue: Cloud computing used unsecured networks like the internet for data communication; due to this insecurity of computer networks, each node can freely alter or internode communication so that to break the whole connection of the system 14,32–34 …”

Section: Literature Reviewmentioning

confidence: 99%

“…Furthermore, the users do not know their critical data and their data security. That's why customers do not trust cloud computing services and prefer to store their critical data on their own IT system at home instead of the cloud 8,11,23,24,33,35 …”

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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“…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]. Un-controlled access of Data: In cloud computing all the nodes are inter linked with each other for data processing.…”

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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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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Challenges and Opportunities in Big Data and Cloud Computing

Cited by 3 publications

References 6 publications

Big Data in Cloud Computing: An Overview

Big Data in Cloud Computing: An Overview

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

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

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