Analysis of big data security practices

Revathy, P.; Mukesh, Rajeswari

doi:10.1109/icatcct.2017.8389145

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…Table VII lists the tools cited more than once. Of all the tools, Apache Hadoop was the most mentioned, having 37 citations ( [1], [6], [8], [9], [12], [18], [23]- [25], [27], [28], [30], [31], [40], [42]- [44], [47], [48], [50], [52], [55], [61], [65], [67]- [71], [73], [76], [80], [82]- [86], [88]). Hadoop is a platform that allows distributed processing of large data sets in computer clusters.…”

Section: Resultsmentioning

confidence: 99%

“…Tableau is a software for interactive data visualization. [6], [9], [31], [47], [55], [68], [76], [82], [85] Apache Flume 7 [1], [6], [27], [52], [61], [70], [83] Apache Sqoop 5 [1], [27], [47], [52], [ [6], [21], [40], [41], [45] MongoDB 6 [16], [33], [35], [41], [43], [ [1], [6], [8], [9], [12], [18], [24], [27], [33], [35], [40], [42], [44], [47], [49], [51], [52], [55], [61], [68], [69], [71],…”

Section: Resultsmentioning

confidence: 99%

“…Initial Accepted Scopus 108 53 papers: [1]- [3], [5], [9], [10], [13]- [19], [23]- [29], [31]- [33], [37], [40], [45], [49], [50], [57], [60]- [66], [68], [70], [71], [73], [76]- [78], [81]- [84], [88], [90], [91], [93]- [95] Springer 222 20 papers: [4], [6], [12], [21], [30], [36], [38], [39], [41]- [43], [47], [51], [53], [69], [74], [79], [85], [86], [92] Google Scholar 197 6 papers:...…”

Section: Sourcementioning

confidence: 99%

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A Mapping Study about Data Lakes: An Improved Definition and Possible Architectures

Couto¹,

Borges²,

Ruiz³

et al. 2019

International Conferences on Software Engineering and Knowledge Engineering

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In the past few years, data lakes emerged as a trending topic in big data technologies. Although literature presents different points of view related to its functionalities, it serves mainly to store a variety of data in a big data context. In this paper, we aim to identify and analyze data lake definitions and possible architectures. Our methodology was composed of a systematic literature mapping based on PRISMA, software engineering best practices to perform reviews, and Kappa method to assess results' quality. We performed the search in eight different electronic databases to achieve a wide variety of publishers in Computer Science. We first identified 662 papers matching our search criteria; after filtering, we selected 87 papers for review. We found that the term data lakes was first defined by James Dixon in 2010. We also found that the term is often related to raw data repositories. From the identified definitions, we propose a new one as a means to better state what data lakes refer to and improve how the community use them. Moreover, we foind that Hadoop and its ecosystem compose the most used toolset to create data lakes, revealing that this is the mainstream in architectures for data lakes as of today's available technologies.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Sourcementioning

confidence: 99%

See 1 more Smart Citation

A Mapping Study about Data Lakes: An Improved Definition and Possible Architectures

Couto¹,

Borges²,

Ruiz³

et al. 2019

International Conferences on Software Engineering and Knowledge Engineering

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“…In any HC NameNode is not available user cannot access their data without metadata ultimately finally there is a scope for Hadoop crash. Hadoop does not have its own security mechanism and it depends on other instances like Kerberos [16] for authentication, Apache Knox [17] is single point authentication, Apache Ranger[18] and Ranger KMS[19] is used for Data encryption purposes. Based on above challenges, Hadoop Clusters required its own security protocol for increasing utilization Hadoop based SNC or MNC which increases in data security performance and decreases the operational, communicational cost for every organization.…”

mentioning

confidence: 99%

Designing Authentication for Hadoop Cluster using DNA Algorithm.

Balaraju*¹,

Rao²

2019

IJRTE

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Big Data (BD) generation are exponentially increased and it is necessarily required for modern society. Hadoop Clusters (HC) provides the facilities like Processing, storage and doesn’t have built-in security. But this feature is important as it increases the analysis speed, storage process. HC facilitates storage, processing of data, on the other hand processing of streaming data handled by the Apache Spark. However data storage, processing power, cluster management and data security in HC is not reached up to the mark with increased data. In such situations, HC are scaled out from small scale IT organization and it depends on public cloud centers with lack of data security, communication, computation and operational cost. On the other hand data security in HC is major issue and it uses a separat security mechanisms. This paper proposes New Algorithm Built in Authentication Based on Access (BABA) as a security instance integrated as Hadoop instance for securing data in HC from attackers along with metadata security for avoiding crashes Hadoop. This mechanism provides a secured HC without using other security configurations which will reduce operational cost, computational power, increases data security and providing a better solution for HC.

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