Big Data Service Architecture for E-portal

Chillal, Vaishnavi; Dalvi, Nikita; Nagapure, Bhagyashree; Naidu, Shamla; Bharati, Rajesh

doi:10.17148/ijarcce.2017.6490

Cited by 1 publication

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“…Vaishnavi Chillal et al [7] proposed framework that it is designed for distributed storage which is exceptionally useful for checking enormous information. This framework is supported for E-banking exchange operations.…”

Section: Literature Reviewmentioning

confidence: 99%

Hadoop Framework for Big Data Analytics to Analyze Attacks on Business Data

Reddy*¹,

Ramanadham²

2019

IJITEE

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Big Data consist large volumes of data sets with various formats i.e., structured, unstructured and semi structured. Big Data requires security because day by day attackers attack on it in different manner. Big Data Security Analytics analyses Big Data for finding various threats and complex attacks. By increasing the number of targeting attacks on data and one side rapid growing of data, it is too difficult to analyze accurately. The Security Analytics Systems are used the untrusted data. So, strong security analytical tools are required to analyze the data. The organizations and industries exchange the data through networks dynamically, so this may become more vulnerable for data misusing and theft. Attackers are more advanced in the attacking on data that the existing security mechanisms are not identified before damaging. At present, the collecting and analyzing various attacks is major challenging task for Security Analytics Systems, to take suitable decision. In this research paper, we have addressed about Hadoop tool that how it analyses Big Data and how Big Data Security Analytics is applied to analyze the various threats and securing the business data more accurately.

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Section: Literature Reviewmentioning

confidence: 99%