Ethereum Network Research Articles

A Blockchain-Powered Voting System for Enhanced Accuracy, Security, and Voter Confidence

Decentralized voting on the Ethereum blockchain offers a secure, transparent, and tamper- proof method for online elections. This system, built as a decentralized application on the Ethereum network, allows participants to cast votes and view results without relying on intermediaries. Votes are securely recorded on the blockchain, preventing any manipulation or alteration of the results. Smart contracts automate the voting process, ensuring transparency and security throughout. By leveraging blockchain technology, this decentralized approach provides a reliable, cost-effective solution for conducting trustworthy and fair elections. KeyWords-blockchain, DApp, smart contract, Multi- factor authentication, truffle suit.

Impact of Black Swan Events on Ethereum blockchain ERC20 token transaction networks

The Ethereum blockchain and its ERC20 token standard have revolutionized the landscape of digital assets and decentralized applications. ERC20 tokens are programmable and interoperable tokens, enabling various applications and token economies. Transaction graphs, representing the flow of the value between wallets within the Ethereum network, have played a crucial role in understanding the system’s dynamics, such as token transfers and the behavior of traders. Here, we explore the evolution of daily transaction graphs of ERC20 token transactions, which sheds light on the trader’s behavior during the Black Swan Events – 2018 crypto crash and the COVID-19 pandemic. By using the tools from network science and differential geometry, we analyze 0.98 billion of ERC20 token transaction data from November 2015 to January 2023. Our analysis reveals an increase in diverse interaction among the traders and a greater adoption of ERC20 tokens in a maturing Ethereum ERC20 financial ecosystem after the Crypto Crash 2018 and the COVID-19 pandemic. Before the crash and the COVID-19 pandemic, most traders interacted with other traders in an isolated or restricted manner, with each trader focusing solely on either buying or selling activities. However, after the crash and during the pandemic, most traders diversely interacted among themselves by participating in both buying and selling activities. In addition, we observe no significant negative impact of the COVID-19 pandemic on user behavior in the financial ecosystem.

Blockchain-Driven Generalization of Policy Management for Multiproduct Insurance Companies

This article presents a Blockchain-based solution for the management of multipolicies in insurance companies, introducing a standardized policy model to facilitate streamlined operations and enhance collaboration between entities. The model ensures uniform policy management, providing scalability and flexibility to adapt to new market demands. The solution leverages Merkle trees for secure data management, with each policy represented by an independent Merkle tree, enabling updates and additions without altering existing policies. The architecture, implemented on a private Ethereum network using Hyperledger Besu and Tessera, ensures secure and transparent transactions, robust dispute resolution, and fraud prevention mechanisms. The validation phase demonstrated the model’s efficiency in reducing data redundancy and ensuring the consistency and integrity of policy information. Additionally, the system’s technical management has been simplified, operational redundancies have been eliminated, and privacy is enhanced.

Anonymous Access System with Limited Number of Uses in a Trustless Environment

This article proposes a novel method for managing usage counters within an anonymous credential system, addressing the limitation of traditional anonymous credentials in tracking repeated use. The method takes advantage of blockchain technology through Smart Contracts deployed on the Ethereum network to enforce a predetermined maximum number of uses for a given credential. Users retain control over increments by providing zero-knowledge proofs (ZKPs) demonstrating private key possession and agreement on the increment value. This approach prevents replay attacks and ensures transparency and security. A prototype implementation on a private Ethereum blockchain demonstrates the feasibility and efficiency of the proposed method, paving the way for its potential deployment in real-world applications requiring both anonymity and usage tracking.

IoT-GChain: Internet of Things-Assisted Secure and Tractable Grain Supply Chain Framework Leveraging Blockchain

The grain supply chain is crucial for any nation’s self-sustainability due to its huge impact on food security, economic stability, and the livelihoods of several people. The path grain takes from farmers to consumers is opaque and complicated, due to which consumers cannot trust grain quality and its origin. Although blockchain is widely used for fair and secure transactions between farmers and buyers, issues related to transparency and traceability in the grain supply chain, such as counterfeiting and middlemen involvement, have not been adequately addressed. To tackle these issues, a blockchain-based solution is proposed that unites farmers, warehouses, government central and state agencies, transporters, and food corporations on a single platform to enhance transparency, traceability, and trust among all parties. This system involves minting a non-fungible token (NFT) corresponding to each lot of grain approved by government officials. The NFT comprises grain quality, type, temperature data from sensors, weight, and ownership information, which updates as the grain lot moves across the supply chain from central agencies to state agencies and so on. NFTs enable stakeholders to track the grain lot from cultivation to end-users, providing insights into grain conditions and quality. An Internet of Things-based circuit is designed using a Digital-output relative humidity & temperature (DHT22) sensor, which offers real-time temperature and humidity readings, and geolocation coordinates are gathered from the GPS module across the supply chain. Farmers can directly interact with warehouses to sell grains, eliminating the need for middlemen and fostering trust among all parties. The proposed four-tier framework is implemented and deployed on the Ethereum network, with smart contracts interacting with React-based web pages. Analysis and results of the proposed model illustrate that it is viable, secure, and superior to the existing grain supply chain system.

Leveraging tabular GANs for malicious address classification in ethereum network

The popularity of ethereum for cryptocurrency transactions attracts malicious actors to engage in illegal activities like phishing, ponzi, and gambling. Previous studies have focused mainly on phishing due to the large number of phishing addresses. However, there is no work done on ponzi or gambling classification due to the limited availability of these addresses, which makes their classification more challenging. In this paper, we propose a machine learning (ML) based method for classifying malicious addresses in ethereum, with a specific focus on phishing, ponzi, and gambling addresses. We use a selective upsampling technique through the tabular generative adversarial network (GAN) to solve limited data problems. We perform not only binary but also multiclass classification on various feature extraction methods, including Trans2Vec and Node2Vec, using Ethereum transactional data. We evaluate our method on F1 score, precision, recall, and accuracy. Our results show that the proposed method is effective in ponzi and gambling detection when compared with the state-of-the-art.

Using blockchain technology to achieve sustainability in the hospitality industry by reducing food waste

The hospitality industry generates significant food waste, leading to adverse environmental and economic impacts, social and ethical concerns, legal and regulatory issues, and operational challenges. The lack of traceability and trust among stakeholders in the hospitality industry exacerbates the expensive and difficult nature of food waste management. This work proposes a blockchain-based solution that aims to minimize food waste generated in hospitality outlets, thereby fostering a sustainable food ecosystem. Within this context, the term’sustainable food ecosystem’ refers to the interconnected network of stakeholders involved in the responsible management of food resources within the hospitality industry. In this context, we categorize these stakeholders under the umbrella of’food resource management entities,’ encompassing both food donation organizations and recycling companies, recognizing their distinct roles in the effective management of surplus food resources. With our proposed solution, businesses can track and verify the origin, movement, and disposal of food items in real-time, facilitating streamlined inventory planning, waste reduction, and heightened operational efficiency. Additionally, the proposed system ensures transparency and accountability, guaranteeing the proper and efficient disposal of food waste. Using a permissioned Ethereum network, our solution establishes seamless connectivity between food and beverage outlets and various food resource management entities. We present a generalized system for secure information sharing, integrating advanced algorithms tailored to capture and enhance trust among participating stakeholders. Furthermore, our thorough security analysis underscores the robustness of our proposed solution, effectively addressing various security vulnerabilities. Lastly, the proposed blockchain-based solution is commercially viable, enabling the hospitality industry to operate with enhanced efficiency while providing improved information connectivity for various stakeholders in the food supply chain.

Suspicious transaction alert and blocking system for cryptocurrency exchanges in metaverse’s social media universes: RG-guard

In this study, we propose an effective system called RG-Guard that detects potential risks and threats in the use of cryptocurrencies in the metaverse ecosystem. In order for the RG-Guard engine to detect suspicious transactions, Ethereum network transaction information and phishing wallet addresses were collected, and a unique dataset was created after the data preprocessing process. During the data preprocessing process, we manually distinguished the features within the original dataset that contained potential risk indicators. The learning process of the RG-Guard engine in risk classification was achieved by developing a deep learning model based on LSTM + Softmax. In the training process of the model, RG-Guard was optimised for maximum accuracy, and optimum hyperparameters were obtained. The reliability and dataset performance of the preferred LSTM + Softmax model were verified by comparing it with algorithms used in risk classification and detection applications in the literature (Decision tree, XG boost, Random forest and light gradient boosting machine). Accordingly, among the trained models, LSTM + Softmax has the highest accuracy with an F1-score of 0.9950. When a cryptocurrency transaction occurs, RG-Guard extracts the feature vectors of the transaction and assigns a risk level between 1 and 5 to the parameter named βrisk. Since transactions with βrisk > = 3 are labelled as suspicious transactions, RG-Guard blocks this transaction. Thus, thanks to the use of the RG-Guard engine in metaverse applications, it is aimed to easily distinguish potential suspicious transactions from instant transactions. As a result, it is aimed to detect and prevent instant potential suspicious transactions with the RG-Guard engine in money transfers, which have the greatest risk in cryptocurrency transactions and are the target of fraud. The original dataset prepared in the proposed study and the hybrid LSTM + Softmax model developed specifically for the model are expected to contribute to the development of such studies.

BiLSTM4DPS: An attention-based BiLSTM approach for detecting phishing scams in ethereum

With the burgeoning adoption of blockchain technology, cryptocurrencies have surged in popularity, becoming a focal point of global interest. Concurrently, the emergence of cryptocurrency phishing scams poses a significant threat to the financial security of the blockchain ecosystem, inflicting substantial economic damage on platforms and users alike. This study introduces an innovative approach leveraging an attention-augmented Bidirectional Long Short Term Memory Network (BiLSTM), termed BiLSTM4DPS, for the detection of phishing scams within the Ethereum network. We initiate by converting account transaction records into sequences, thereby extracting temporal and latent patterns of transactions. Subsequently, we integrate BiLSTM with multi-head attention mechanisms and masking techniques to construct a robust classification model aimed at identifying fraudulent accounts. Extensive experiments were conducted to assess the efficacy of BiLSTM4DPS, particularly under scenarios with limited account activity data. The results demonstrate that BiLSTM4DPS achieves remarkable predictive accuracy, surpassing existing state-of-the-art methods.

The Decentralized Non-Fungible Token Exchange with Secure Connections

During the COVID-19 outbreak, due to the lockdown, all museums and galleries were closed for more than a year. So, the buying and selling of physical arts have dropped. This project aims to overcome this challenge by developing a decentralized application called Decentralized NFT Exchange. The decentralized non-fungible token (NFT)exchange includes features such as secure wallet connections, NFT creations, buying, selling, and profile management. The back-end of the decentralized NFT exchange is implemented using Solidity-based smart contracts, while InterPlanetary File System (IPFS)is used for decentralized storage. Front-end development of decentralized NFT exchange is implemented using React JSX and framework web3.js that helps developers connect to the Ethereum network. Decentralized NFT can help art creators sell their artworks using a smart contract system where the ownership of the work will become the property of the new owner with proof of a digital certificate. The project demonstrates the practical application of blockchain technology in developing decentralized applications (DApps)for secure and decentralized digital asset management. Overall, Decentralized NFT might be a solution for the copyright of work in the future and the project contributes to secure and decentralized digital asset management

Performing Encrypted Cloud Data Keyword Searches Using Blockchain Technology on Smart Devices

Data owners seeking to boost processing power, storage, or bandwidth can take advantage of cloud computing services. However, this shift poses new challenges related to privacy and data security. Searchable Encryption (SE), which combines encryption and search techniques, addresses these issues (violation of data users' privacy) by allowing user data to be encrypted, transmitted to a cloud server, and searched using keywords. Despite its benefits, several recent real-world attacks have raised concerns about the security of searchable encryption. Ensuring forward and backward privacy is likely to become a standard requirement in the development of new SE systems. To address these issues, we propose a scheme that exclusively uses symmetric cryptographic primitives, achieving high communication efficiency and forward and backward privacy. In addition, we emphasize improved I/O efficiency because only the results of subsequent updates are loaded when searching. The time required to retrieve results is so significantly reduced compared to existing SE methods that we have shown that our scheme achieves superior efficiency. Moreover, by integrating blockchain network services with cloud services, we have developed a searchable intelligent cryptosystem suitable for lightweight smart devices. In our study conducted on the Ethereum network, we found our method to be both efficient and secure, especially when compared to methods such as PPSE and Jiang. The results indicate that our system delivers results in terms of performance and privacy within dynamic cloud environments making it a solution for protecting confidential information.

Improving Supply Chain Management Processes Using Smart Contracts in the Ethereum Network Written in Solidity

Improving Supply Chain Management Processes Using Smart Contracts in the Ethereum Network Written in Solidity

Transaction fee mechanisms with farsighted miners

AbstractWe investigate the recent fee mechanism EIP1559 of the Ethereum network. Whereas previous studies have focused on myopic miners, we here focus on strategic miners in the sense of miners being able to reason about the future blocks. We derive expressions for optimal miner behavior (in terms of setting block sizes) in the case of two‐block foresight and varying degrees of hashing power. Results indicate that a sufficiently large mining pool will have enough hashing power to gain by strategic foresight. We further use a simulation study to examine the impact of both two‐block and three‐block foresight. In particular, the simulation study indicates that for realistic levels of hashing power, mining pools do not gain from being able to reason more than two blocks ahead. Moreover, even though the presence of strategic miners increases the variation in block sizes and potentially empty blocks, overall system throughput tends to increase slightly compared with myopic mining. We further analyze the effect of varying the base fee updating rule.

COST-EFFECTIVE AND EFFICIENT BLOCKCHAIN FRAMEWORK FOR VERIFYING CERTIFICATE IN YEMENI UNIVERSITIES

Recognizing the necessity to preserve the integrity and good name of degrees awarded by Yemeni universities. It should provide an efficient way of verifying certificates. The effectiveness of the conventional method of confirming the validity of certificates in reducing fraud has not been very strong. Therefore, it is necessary to stop this kind of fraud by using blockchain technology, which has several benefits, such as encryption, sharing of data, and the capacity to store information as permanent data that cannot be altered. Low latency and low cost will be available for the issuance, sharing, and verification of these certifications in universities if the suggested system is implemented. The paper presents the proposed framework, which uses smart contracts in the Ethereum blockchain and a distributed peer-to-peer network (filebase) for certification verification by a certificate’s hash immediately without waiting for the facility’s response. It also contains an estimate of the average cost of publishing a certificate. It also frees students from having to constantly carry paper copies of their documents by enabling them to access them via a certificate's hash. Furthermore, there is no extra cost for the verification process, and it does not require an Ethereum network account.

Implementation of Diploma and Transcript Verification System on the Ethereum Blockchain Network

Blockchain, a decentralized database safeguarded by cryptographic security, has gained prominence for its resistance to manipulation. Its application extends notably to ensuring the security of financial transactions, including the acquisition of digital currencies. This study endeavors to develop a system aimed at validating diplomas and academic transcripts, enhancing their authenticity and bolstering the security of document storage. Leveraging the Ethereum Blockchain and Smart Contracts, the methodology focuses on the utilization of specialized codes executed within the Ethereum network. The outcome of this research manifests as a system blueprint designed for the verification of diplomas and transcripts, integrated within a web-based Ethereum Network platform. By harnessing the Ethereum Blockchain's inherent security features and employing Smart Contracts, the proposed system endeavors to streamline the verification process, ensuring the integrity and reliability of academic credentials while fortifying document storage against potential breaches. Through this innovative approach, the study contributes to advancing the authentication and security standards within the realm of academic documentation management.

SeedChain: A Secure and Transparent Blockchain-Driven Framework to Revolutionize the Seed Supply Chain

Farming is a major sector required for any nation to become self-sustainable. Quality seeds heavily influence the effectiveness of farming. Seeds cultivated by breeders pass through several entities in order to reach farmers. The existing seed supply chain is opaque and intractable, which not only hinders the growth of crops but also makes the life of a farmer miserable. Blockchain has been widely employed to enable fair and secure transactions between farmers and buyers, but concerns related to transparency and traceability in the seed supply chain, counterfeit seeds, middlemen involvement, and inefficient processes in the agricultural ecosystem have not received enough attention. To address these concerns, a blockchain-based solution is proposed that brings breeders, farmers, warehouse owners, transporters, and food corporations to a single platform to enhance transparency, traceability, and trust among trust-less parties. A smart contract updates the status of seeds from a breeder from submitted to approved. Then, a non-fungible token (NFT) corresponding to approved seeds is minted for the breeder, which records the date of cultivation and its owner (breeder). The NFT enables farmers to keep track of seeds right from the date of their cultivation and their owner, which helps them to make better decisions about picking seeds from the correct owner. Farmers directly interact with warehouses to purchase seeds, which removes the need for middlemen and improves the trust among trust-less entities. Furthermore, a tender for the transportation of seeds is auctioned on the basis of the priority location locp, Score, and bid_amount of every transporter, which provides a fair chance to every transporter to restrict the monopoly of a single transporter. The proposed system achieves immutability, decentralization, and efficiency inherently from the blockchain. We implemented the proposed scheme and deployed it on the Ethereum network. Smart contracts deployed over the Ethereum network interact with React-based web pages. The analysis and results of the proposed model indicate that it is viable and secure, as well as superior to the current seed supply chain system.

Educational Certificate Verification System: Enhancing Security and Authenticity using Ethereum Blockchain and IPFS

Educational certificate counterfeiting is a major global challenge. There is no doubt that addressing both the problem of forgery and the verification of academic certificates is a fundamental issue that deserves research, development, and support at the highest levels. This paper presents a decentralized educational certificate verification system leveraging the Ethereum blockchain and the InterPlanetary File System (IPFS) to combat counterfeiting. Ropsten is used as a real-life Ethereum test network to demonstrate the effectiveness of the proposed system. IPFS is used to store educational certificate files on a decentralised file system. The smart contract is built in the Solidity language, compiled, and deployed using the online Remix IDE. The verification process is supported by scanning a QR code, which retrieves the validating certificate’s information from the Ethereum network in real-time.

Learning to Traverse Cryptocurrency Transaction Graphs Based on Transformer Network for Phishing Scam Detection

Cryptocurrencies have experienced a surge in popularity, paralleled by an increase in phishing scams exploiting their transactional networks. Therefore, detecting anomalous transactions in the complex structure of cryptocurrency transaction data and the imbalance between legitimate and fraudulent data is considered a very important task. To this end, we introduce a model specifically designed for scam detection within the Ethereum network, focusing on its capability to process long and complex transaction graphs. Our method, Deep Graph traversal based on Transformer for Scam Detection (DGTSD), employs the DeepWalk algorithm to traverse extensive graph structures and a Transformer-based classifier to analyze intricate node relationships within these graphs. The necessity for such an approach arises from the inherent complexity and vastness of Ethereum transaction data, which traditional techniques struggle to process effectively. DGTSD applies subgraph sampling to manage this complexity, targeting significant portions of the network for detailed analysis. Then, it leverages the multi-head attention mechanism of the Transformer model to effectively learn and analyze complex patterns and relationships within the Ethereum transaction graph to identify fraudulent activity more accurately. Our experiments with other models demonstrate the superiority of this model over traditional methods in performance, with an F1 score of 0.9354. By focusing on the challenging aspects of Ethereum’s transaction network, such as its size and intricate connections, DGTSD presents a robust solution for identifying fraudulent activities, significantly contributing to the enhancement of blockchain security.

A Systematic Literature Survey on Electronic Health Record System Using Blockchain

Abstract-Compared with traditional paper-based medical records , Electronic health records (EHRs) are widely used because of their efficiency, secu- rity, and reducing data redundancy.The Electronic Health Record (EHR) system is a major technolog- ical development in healthcare that has completely changed how patient data is collected, stored, and used. Through the use of cutting-edge digital tech- nologies, the EHR system offers a safe, centralized location for all patient data. Healthcare personnel may easily access, edit, and share patient informa- tion thanks to its user-friendly interfaces, which helps them make more informed clinical decisions and provide better treatment.The system developed using the Ethereum network using Ganache. The measured approach is to store patients data and execute functions in a decentralized system using blockchain smart contracts. To further protect pa- tient privacy and adhere to privacy laws, the system places a high priority on data security and uses strong authentication and encryption mechanisms. Keywords-Blockchain, Decentralized, Ethereum, Healthcare, Smartcontacts,

Advanced Fraud Detection in Blockchain Transactions: An Ensemble Learning and Explainable AI Approach

In recent years, cryptocurrencies have experienced rapid growth and adoption, revolutionizing the financial sector. However, the rise of digital currencies has also led to an increase in fraudulent transactions and illegal activities. In this paper, we present a comprehensive study on the detection of fraudulent transactions in the context of cryptocurrency exchanges, with a primary focus on the Ethereum network. By employing various Machine Learning (ML) techniques and ensemble methods, including the hard voting ensemble model, which achieved a remarkable 99% accuracy, we aim to effectively identify suspicious transactions while maintaining high accuracy and precision. Additionally, we delve into the importance of eXplainable Artificial Intelligence (XAI) to enhance transparency, trust, and accountability in AI-based fraud detection systems. Our research contributes to the development of reliable and interpretable models that can significantly improve the cryptocurrency ecosystem security and integrity.