ISSN2456-3315
Impact Factor10.57
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CrossRefDOI
ESTD2016
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Paper Title
Improving Data Security System through Gaussian Windowing / Inverse Gaussian Windowing in PTS
Authors
MAMTA PANT , ARUNDHATI WALIA
Keywords
Partially Transmitted Sequences, Gaussian Windowing Method, Inverse Gaussian Windowing Method, Crest Factor.
Abstract
Data security is the process of protecting digital data from unwanted action of unauthorized access and data corruption throughout its life. Through such conditions as cyber-attacks or data breaches on any server or computer system slightly increase the rate of cybercrime. As per the McAfee Corp. report released on Dec. 7, 2020,the estimated annual loss in the global economy exceeded $1 Trillion which is 50 % more from 2018. And if we specifically talk about India, the extent of loss due to cybercrime has increased up to 63 crore in 2020 as compared to 2021 through ATM cards, credit cards, E-commerce, and internet banking.
Data security should have the ability to protect the confidential and personal data of the customer. In the current scenario, there are so many technologies available that provide the best data security. In this research paper we are working on Gaussian and Inverse Gaussian Windowing methods in the Partially Transmitted Sequence (PTS) technique.
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How To Cite
"Improving Data Security System through Gaussian Windowing / Inverse Gaussian Windowing in PTS", IJRTI - International Journal for Research Trends and Innovation (www.IJRTI.org), ISSN:2456-3315, Vol.7, Issue 7, page no.1475 - 1478, July-2022, Available :https://ijrti.org/papers/IJRTI2207258.pdf
Issue
Volume 7 Issue 7,
July-2022
Pages : 1475 - 1478
Other Publication Details
Paper Reg. ID: IJRTI_183338
Published Paper Id: IJRTI2207258
Downloads: 205,596
Research Area: Computer Science & TechnologyÂ
Country: GHAZIABAD, UTTAR PRADESH, India
Published Paper PDF: https://ijrti.org/papers/IJRTI2207258
Published Paper URL: https://ijrti.org/viewpaperforall?paper=IJRTI2207258
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ISSN: 2456-3315 | IMPACT FACTOR: 10.57 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 10.57 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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