Securing Bioinformatics Cloud for Big Data: Budding Buzzword or a Glance of the Future

Seth, Bijeta; Dalal, Surjeet; Kumar, Raman

doi:10.1007/978-3-030-12500-4_8

Cited by 4 publications

(3 citation statements)

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“…Unencrypted data: As cloud computing like Hadoop, NoSQL, and MapReduce are processed and store the critical data without encryption for better efficiency and performance, so due to this unencryption, the critical and pivotal data of each user is not protected, and everyone could effortlessly get access to the essential data 12,14,17,24,26–29 …”

Section: Literature Reviewmentioning

confidence: 99%

“…Cloud computing is the technology that provides IT services to the end users on the internet across the world to accomplish the customers' requirements and to be contingent on the delivery of cloud computing services, software, and other useful data over the internet instead of traditional IT systems with minimum cost and time 10,11,14–18 . To process a large volume of organizational data, a cloud computing network consists of a large group of servers connected, which can process the customer's data to a secret space and store it anywhere in the world on a secure storage address 19,20 …”

Section: Introductionmentioning

confidence: 99%

“…Cloud computing has usually offered three types of services, which are “Platform as a Service (PaaS),” “Software as a Service (SaaS),” and “Infrastructure as a Service (IaaS).” Cloud computing other examples are Gmail, Google Drive, Facebook, YouTube, Twitter, and Dropbox 1,10,12,16–18,21–23 . Nowadays, cloud computing has become very much helpful and popular for data management, data storage, and data processing with a lot of advantages, like resource sharing, multitenancy, data storing, and clear virtualization, but yet cloud computing has not free from security challenges that are discussed, 15,16,20,22 such as data confidentiality, data privacy, data integrity issue, data availability issue, lack of trust on third party, interoperability issue, malicious insider attack, and losing control over data.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%