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Paper Title: Improving Big Data Secuirity and Services
Authors Name: Ayush Raju Gaikwad , Pankaj Subhash Chavan , Ashutosh Rajaram Barkade , Tejas Bharat Dhotre
Unique Id: IJSDR2212056
Published In: Volume 7 Issue 12, December-2022
Abstract: The paradigm of big data has been one of the most interesting concepts that have been evolving in the recent years. The big data is extremely difficult to analyze and effectively process to achieve insightful information. The security management of big data that has extremely high velocity and volume of data becomes a mammoth task. The mismanagement of this data can lead to the theft of confidential or sensitive information that can be highly problematic in the event of a data leak. A number of approaches has been designed to combat this effect but there has been a lack of efficiency in these approaches. Therefore an effective methodology has been implemented that it effectively classifies and partitions big data queries which are mapped for parallel computation on to a mongo DB database. The approach specified in this research article also utilizes the concept of bilinear pairing through implementation of hashing and the detection of avalanche effect for the purpose of tamper detection and the forensic analysis for effective security report generation.
Keywords: Big data, Parallel Computation, Bilinear Pairing, Avalanche effect, Data Mapping.
Cite Article: "Improving Big Data Secuirity and Services ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.7, Issue 12, page no.378 - 382, December-2022, Available :http://www.ijsdr.org/papers/IJSDR2212056.pdf
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Publication Details: Published Paper ID: IJSDR2212056
Registration ID:202853
Published In: Volume 7 Issue 12, December-2022
DOI (Digital Object Identifier):
Page No: 378 - 382
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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