A Comparison among Fast Point Multiplication Algorithms in Elliptic Curve Cryptosystem

Padhy, Sasmita; Shankar, T.; Dash, Sachikanta

doi:10.21203/rs.3.rs-862241/v1

Cited by 6 publications

(3 citation statements)

References 23 publications

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“…Sasmita Padhy, T.N. Shankar, and Sachikanta Dash (2022) [10] compared the performance of fast point multiplication algorithms in terms of computation and execution time to determine the quickest solution for elliptic curve cryptosystems. The authors focused on evaluating different techniques, such as addition and subtraction, mutual opposite form (MOF), and complementary recoding, for fast scalar multiplication schemes.…”

Section: Literature Reviewmentioning

confidence: 99%

An Optimized Point Multiplication Strategy in Elliptic Curve Cryptography for Resource-Constrained Devices

Sabbry,

Levina

2024

Mathematics

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Elliptic curve cryptography (ECC) is widely acknowledged as a method for implementing public key cryptography on devices with limited resources thanks to its use of small keys. A crucial and complex operation in ECC calculations is scalar point multiplication. To improve its execution time and computational complexity in low-power devices, such as embedded systems, several algorithms have been suggested for scalar point multiplication, with each featuring different techniques and mathematical formulas. In this research, we focused on combining some techniques to produce a scalar point multiplication algorithm for elliptic curves over finite fields. The employed methodology involved mathematical analysis to investigate commonly used point multiplication methods. The aim was to propose an efficient algorithm that combined the best computational techniques, resulting in lower computational requirements. The findings show that the proposed method can overcome certain implementation issues found in other multiplication algorithms. In certain scenarios, the proposed method offers a more efficient approach by reducing the number of point doubling and point addition operations on elliptic curves using the inverse of the targeted point.

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Section: Literature Reviewmentioning

confidence: 99%

An Optimized Point Multiplication Strategy in Elliptic Curve Cryptography for Resource-Constrained Devices

Sabbry,

Levina

2024

Mathematics

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“…It is a visual detection of diseases by analyzing a huge amount of image data, processing and interpreting them to understand the structural changes of the lesion sites of patients. Machine learning [7][8][9][10] This paper makes the following contributions: Section 2 discusses literature survey, section 3 explains about the proposed approach, Section 4 discusses about the experimental setup, Section 5 discusses concludes.…”

Section: Introductionmentioning

confidence: 99%

Identification of Polyp from Colonoscopy Images by Deep Belief Network based Polyp Detector Integration Model

Dash,

Padhy

et al. 2023

EAI Endorsed Trans Perv Health Tech

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Cancer is a disease involving unusual cell growth likely to spread to other parts of the body. According to WHO 2020 report, colorectal malignancy is the globally accepted second leading cause of cancer related deaths. Colorectal malignancy arises when malignant cells often called polyp, grow inside the tissues of the colon or rectum of the large intestine. Colonoscopy, CT scan, Histopathological analysis are some manual approaches of malignancy detection that are time consuming and lead to diagnostic errors. Supervised CNN data model requires a large number of labeled training samples to learn parameters from images. In this study we propose an expert system that can detect the colorectal malignancy and identify the exact polyp area from complex images. In this approach an unsupervised Deep Belief Network (DBN) is applied for effective feature extraction and classification of images. The classified image output of DBN is utilized by Polyp Detector. Residual network and feature extractor components of Polyp Detector helps polyp inspector in pixel wise learning. Two stage polyp network (PLPNet) is a R-CNN architecture with two stage advantage. The first stage is the extension of R-CNN to detect the polyp lesion area through a location box also called Polyp Inspector. Second Stage performs polyp segmentation. Polyp Inspector transfers the learned semantics to the polyp segmentation stage. It helps to enhance the ability to detect polyp with improved accuracy and guide the learning process. Skip schemes enrich the feature scale. Publicly available CVC-Clinical DB and CVC Colon DB datasets are used for experiment purposes to achieve a better prediction capability for clinical practices.

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“…Six 𝐸𝐶𝑆𝑀 algorithms were examined in this work. Some of the conventional scalar recoding algorithms have been investigated and examined including the binary method [10], the Non-Adjacent Form (𝑁𝐴𝐹) method [13], Window 𝜔 − −𝑁𝑜𝑛 𝐴𝑑𝑗𝑎𝑐𝑒𝑛𝑡 𝐹𝑜𝑟𝑚(𝜔 − 𝑁𝐴𝐹 ) method [14], Mutual Opposite Form (𝑀𝑂𝐹) method [15], Direct Recoding Method (𝐷𝑅𝑀) [16], and Complementary Recoding Technique (𝐶𝑅𝑇) [17].…”

Section: Introductionmentioning

confidence: 99%

Elliptic Curve Scalar Multiplication Operation: a Survey Study

Waleed,

Al Saffar

2023

Jour. Kufa Math. Comp.

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Scalar multiplication is the fundamental operation in the elliptic curve cryptosystem. It involves calculating the integer multiple of a specific elliptic curve point. It involves three levels: field, point, and scalar arithmetic. Scalar multiplication will be significantly more efficient overall if the final level is improved. By reducing the hamming weight or the number of operations in the scalar representation, one can raise the level of scalar arithmetic. This paper reviews some of the algorithms and techniques that improve the elliptic curve scalar multiplication in terms of the third level.

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A Comparison among Fast Point Multiplication Algorithms in Elliptic Curve Cryptosystem

Cited by 6 publications

References 23 publications

An Optimized Point Multiplication Strategy in Elliptic Curve Cryptography for Resource-Constrained Devices

An Optimized Point Multiplication Strategy in Elliptic Curve Cryptography for Resource-Constrained Devices

Identification of Polyp from Colonoscopy Images by Deep Belief Network based Polyp Detector Integration Model

Elliptic Curve Scalar Multiplication Operation: a Survey Study

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