Big Data Security Challenges and Preventive Solutions

Gupta, Nirmal Kumar; Rohil, Mukesh Kumar

doi:10.1007/978-981-32-9949-8_21

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…In fact, the sheer magnitude of the size of medical big data has increased to such a level that new storage technology systems have been developed to capture, manage, and process big data. However, issues with privacy control, technical vulnerabilities, security for authorization and verification, data management, and confidentiality still exist [6].…”

Section: Introductionmentioning

confidence: 99%

Veterinary Big Data: When Data Goes to the Dogs

Paynter

Dunbar

Creevy

et al. 2021

Animals

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Dogs provide an ideal model for study as they have the most phenotypic diversity and known naturally occurring diseases of all non-human land mammals. Thus, data related to dog health present many opportunities to discover insights into health and disease outcomes. Here, we describe several sources of veterinary medical big data that can be used in research. These sources include medical records from primary medical care centers or referral hospitals, medical claims data from animal insurance companies, and datasets constructed specifically for research purposes. No data source provides information that is without limitations, but large-scale, prospective, longitudinally collected data from dog populations are ideal for further research as they offer many advantages over other data sources.

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Section: Introductionmentioning

confidence: 99%

Veterinary Big Data: When Data Goes to the Dogs

Paynter

Dunbar

Creevy

et al. 2021

Animals

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“…Thirdly, it focuses on opportunities and challenges brought by the development of Big Data. For example, Ashabi et al (2020) conducted research on the current challenges and future development of Big Data; Gupta and Rohil (2020) pointed out that Big Data has hidden dangers such as privacy leakage, and he proposed some critical solutions to problems related to Big Data security and privacy. Fourthly, it focuses on standards and policymaking in the Big Data industry.…”

mentioning

confidence: 99%

Analyzing the interdisciplinarity of Big Data research

2022

DSI

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TechAmerica Foundation defines Big Data as: "Big Data is a term that describes a large number of high-speed, complex and variable data, which requires advanced technologies and processes to capture, store, distribute, manage and analyze information" (TechAmerica Foundation's Federal Big Data Commission, 2012). Big Data can also be defined as a vast data set with increasingly diverse and complex structures (Iqbal et al., 2020), characterized by mass, rapidity, diversification, and low-value density (Furht & Villanustre, 2016). However, the term has now been extended. Big Data is worthless in a vacuum, and its potential value will only be released when it is used to promote decision-making (Gandomi & Haider, 2015).

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