eprintid: 14702
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/47/02
datestamp: 2023-11-10 03:29:17
lastmod: 2023-11-10 03:29:17
status_changed: 2023-11-10 01:57:35
type: conference_item
metadata_visibility: show
creators_name: Bhattacharjee, S.
creators_name: Rahim, L.B.A.
title: A Hadoop Allied Security Platform for Seismic Big Data Processing
ispublished: pub
keywords: Complex networks; Gas industry; Indexing (materials working); Petroleum industry; Petroleum prospecting; Public key cryptography; Security of data; Seismology, Avalanche effects; Data confidentiality; Elliptic Curve Cryptography(ECC); Integrated techniques; Parallel processing; Security algorithm; Time efficiencies; Unified solutions, Big data
note: cited By 2; Conference of 6th International Conference on Computer and Information Sciences, ICCOINS 2021 ; Conference Date: 13 July 2021 Through 15 July 2021; Conference Code:170762
abstract: The importance of seismic big data exploration, especially in gas and oil industries, is indispensable. The processing of such complex data becomes more critical when its size is extremely large. These days the dispose of seismic big data over the network is notably common. Hence, the security of this huge complex data is equally important during its transportation over an insecure channel. Consequently, the application of any security algorithm on complex big seismic data makes it impractical for adopting it in any industry. Numerous researches have been conducted to resolve these issues. However, any unified solution has not been proclaimed by the exiting related studies. Therefore, this research work affirms a unique unified platform that uses the integration of Hadoop and Hive for parallel processing and advanced indexing for faster execution of large complex data. At the same time, it uses a low complex elliptic curve cryptography (ECC) to ensure data security in terms of data confidentiality and integrity. The result shows that the proposed integrated technique offers higher time efficiency in terms of producing higher Throughput than other security combinations. It further shows it produces a low percentage of Data Loss and higher Entropy Value as well as Avalanche Effect which justifies its ability to offer higher data confidentiality and integrity. © 2021 IEEE.
date: 2021
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85112433671&doi=10.1109%2fICCOINS49721.2021.9497221&partnerID=40&md5=7c8076ee9b50b6d69e18eb3793b3f736
id_number: 10.1109/ICCOINS49721.2021.9497221
full_text_status: none
publication: Proceedings - International Conference on Computer and Information Sciences: Sustaining Tomorrow with Digital Innovation, ICCOINS 2021
pagerange: 372-377
refereed: TRUE
isbn: 9781728171517
citation:   Bhattacharjee, S. and Rahim, L.B.A.  (2021) A Hadoop Allied Security Platform for Seismic Big Data Processing.  In: UNSPECIFIED.