Framework and Smart Contract for Blockchain Enabled Certificate Verification System Using Robotics

The most well-known cryptocurrency, Bitcoin, is one of many that are sweeping the globe. Along with them, fungible tokens traded on numerous centralised or decentralised exchanges are different from non-fungible tokens traded on NFT marketplaces. The majority of NFTs are currently digital, and in the future, producers may innovate in this area to allow for more innovative user experiences. The blockchain and its NFTs can provide fantastic chances for artists and content producers to profit from their work. The NFT Marketplace intends to be at the centre of all these fantastic use cases for NFTs by giving users a platform to produce and exchange non-fungible tokens. NFTs offer a wide range of application cases. Automated Market Makers, which are essentially decentralised markets for crypto-tokens and offer users three core operations—depositing crypto tokens in exchange for AMM shares, performing a dual operation in which shares are obtained in exchange for base tokens, and exchanging two tokens for one another—are some of the main applications of DeFi. This conceptual research discusses AMMs that are already in existence on the Ethereum blockchain and their developments, including the AMM that is now being created on the Tezos blockchain. The goal of this study is to present a thorough understanding of blockchain technology and all of its practical uses, including voting, trading NFTs, etc. It then focuses on how NFTs are traded on various platforms before aiming for improved NFT trading marketplaces, namely Automated Market Makers on various blockchains like Ethereum and Tezos.

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“…According to the studies [28][29][30][31], certificate verification is a highly helpful application of blockchain.…”

Section: Blockchain Applicationsmentioning

confidence: 99%

A New Era of Automated Market-Makers (AMM) powered by Non-Fungible Tokens- A Review

Gupta

Malsa

2023

Glo.Jou.of.Innov.and.Eme.Tech

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“…Tan et al [35] highlight the practicable usage of blockchain and smart contracts to cross-organizational SLA (service legal agreement) in cloud manufacturing industries. A robotic verification system of the certificate has been developed by Malsa et al [36], where a blockchain network safely and immutably stores certificate information, and smart contract can check and verify the authenticity of the certificate. The application of blockchain with smart contract demonstrates that both of the technology works as a compatible dyad in which both blockchain and smart contract bolster each other's abilities and maximize their usability [72].…”

Section: A Blockchain and Smart Contractmentioning

confidence: 99%

Blockchain and Machine Learning for Fraud Detection: A Privacy-Preserving and Adaptive Incentive Based Approach

et al. 2022

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Financial fraud cases are on the rise even with the current technological advancements. Due to the lack of inter-organization synergy and because of privacy concerns, authentic financial transaction data is rarely available. On the other hand, data-driven technologies like machine learning need authentic data to perform precisely in real-world systems. This study proposes a blockchain and smart contract-based approach to achieve robust Machine Learning (ML) algorithm for e-commerce fraud detection by facilitating interorganizational collaboration. The proposed method uses blockchain to secure the privacy of the data. Smart contract deployed inside the network fully automates the system. An ML model is incrementally upgraded from collaborative data provided by the organizations connected to the blockchain. To incentivize the organizations, we have introduced an incentive mechanism that is adaptive to the difficulty level in updating a model. The organizations receive incentives based on the difficulty faced in updating the ML model. A mining criterion has been proposed to mine the block efficiently. And finally, the blockchain network is tested under different difficulty levels and under different volumes of data to test its efficiency. The model achieved 98.93% testing accuracy and 98.22% Fbeta score (recall-biased f measure) over eight incremental updates.Our experiment shows that both data volume and difficulty level of blockchain impacts the mining time. For difficulty level less than five, mining time and difficulty level has a positive correlation. For difficulty level two and three, less than a second is required to mine a block in our system. Difficulty level five poses much more difficulties to mine the blocks.INDEX TERMS blockchain, collaborative machine learning, incremental learning, privacy, smart contract Dr. RASHEDUR M. RAHMAN works as a Professor in the Electrical and Computer Engineering Department

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“…Names were generated using a name test data generator tool [23]. The formula for error rate and accuracy will be computed as ( 1)- (2).…”

Section: Performance Analysismentioning

confidence: 99%

“…But recently, people get involved in the creation of fraudulent academic credentials therefore its prevalence [1]. Verification of these documents is quite challenging because they cannot be traced as quickly and accurately [2]. Thus, a system is needed to inspect the authenticity and validity of such document certification rapidly and precisely [3].…”

Section: Introductionmentioning

confidence: 99%

Document verification using quick response code with modified secure hash algorithm-1 and modified blowfish algorithm

Quilala

2022

IJEECS

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A previous study has been conducted integrating modification on secure hash algorithm 1 (SHA-1) to document integrity verification of printed documents using quick response (QR) codes. However, encryption is warranted as data is transmitted in plaintext directly to the server to prevent hacking and ensuring not only data integrity but data security as well. A more secured document integrity verification using QR code was designed and developed by successfully incorporating a better hashing algorithm– modified SHA-1 and integrating a modern encryption algorithm–modified blowfish algorithm. By integrating both, data integrity and data confidentiality is assured as compared to previous research. The developed software was checked against user requirements to check the acceptability of the software. Error rate and accuracy were also checked to see how the software performed. Based on the testing conducted, it has been found that the document integrity verification software using QR code with the integration of modified SHA-1 hash and Modified Blowfish encryption was acceptable, accurate, and more secure.

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Framework and Smart Contract for Blockchain Enabled Certificate Verification System Using Robotics

Cited by 42 publications

References 12 publications

A New Era of Automated Market-Makers (AMM) powered by Non-Fungible Tokens- A Review

A New Era of Automated Market-Makers (AMM) powered by Non-Fungible Tokens- A Review

Blockchain and Machine Learning for Fraud Detection: A Privacy-Preserving and Adaptive Incentive Based Approach

Document verification using quick response code with modified secure hash algorithm-1 and modified blowfish algorithm

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