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JCR Impact Factor: 0.800
JCR 5-Year IF: 1.000
SCOPUS CiteScore: 2.0
Issues per year: 4
Current issue: Feb 2024
Next issue: May 2024
Avg review time: 75 days
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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Analysis of the Hybrid PSO-InC MPPT for Different Partial Shading Conditions, LEOPOLDINO, A. L. M., FREITAS, C. M., MONTEIRO, L. F. C.
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2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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Clarivate Analytics published the InCites Journal Citations Report for 2020. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 1.221 (1.053 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.961.

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  3/2021 - 3

An Efficient Biocrypto-system Using Least Square Polynomial Curve Fitting with Interpolation Based New Chaff-Points Generation Method

TANTUBAY, N. See more information about TANTUBAY, N. on SCOPUS See more information about TANTUBAY, N. on IEEExplore See more information about TANTUBAY, N. on Web of Science, BHARTI, J. See more information about BHARTI, J. on SCOPUS See more information about BHARTI, J. on SCOPUS See more information about BHARTI, J. on Web of Science
 
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Download PDF pdficon (1,792 KB) | Citation | Downloads: 835 | Views: 1,103

Author keywords
cryptography, curve fitting, information security, interpolation, least squares

References keywords
vault(12), fuzzy(12), biometric(12), fingerprint(7), scheme(6), chaff(6), security(5), generation(5), system(4), sciences(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2021-08-31
Volume 21, Issue 3, Year 2021, On page(s): 21 - 30
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.03003
Web of Science Accession Number: 000691632000003
SCOPUS ID: 85114832016

Abstract
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Large cryptographic-key ensures high security and robustness of asymmetric and symmetric cryptography. The conventional Fuzzy Vault Scheme (FVS) biocrypto-system is employed to shield private or secret-key using biometric features. The strength of FVS consists in its polynomial degree and chaff-points. In FVS, the system's performance is degraded with increment in the polynomial degree to make system robust against attacks. Similarly, valid chaff-point generation is also a crucial task that needs to be considered in the conventional FVS. Therefore, an efficient and more secure Modified FVS (MFVS) using Least Square Polynomial Curve Fitting (LSPC) is proposed in this paper to enhance the security of conventional FVS. Moreover, Newtons Divided Difference Interpolation (NDDI) based new chaff-points generation method is also proposed to minimize the number of required candidate points. The proposed system demonstrations average accuracy as 100%, Genuine Acceptance Rate (GAR) as 99%, False Rejection Rate (FRR) as 1%, and False Acceptance Rate (FAR) as 0%. Security of MFVS is analyzed against brute-force attack, it evident that 10-Million more combinations are required to break the generated Fuzzy Vault as compared to prior research. Consequently, proposed chaff-point generation reduces required candidate points by 13-times than existing methods


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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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