Follow blockchain research across journals, conferences, and preprint repositories.
7,423 results · page 164 of 310
Yu Tang, Yi Sun, Zhaowen Lin
No abstract is available for this record.
Josephine Permata Sari, Joniarto Parung
Blockchain as a distributed ledger technology that can guarantee transparency and speed in real time is increasingly being used to increase supply chain performance directly or indirectly.Blockchain in the form of smart contracts in the insurance business will speed up insurance claims and increase transparancy, which will indirectly improve supply chain performance.This article aims to identify the role of smart contracts in increasing efficiency and applying smart contract designs to disbursing life insurance claims.The method for designing and implementing smart contracts was developed on the Ethereum platform involving several parties such as insurers, customers, and CAIPY Dapp.CAIPY is the name of the system being developed.CAIPY ensures that the system can prevent data manipulation, data leakage and guarantees the security of the smart contract itself.This research includes planning what data is needed in the smart contract design.Based on these data requirements, a system architecture, system mechanism is prepared, and closed with the design of a smart contract.This research produces a life insurance claim system in the form of a website by utilizing smart contracts.Analysis of the impact of implementing this system found an accelerated claim process, transparency of reasons for rejection in real time, and claims that are guaranteed as long as the conditions meet the policy requirements.
Negar Fazlollahi, Saeed Ebrahimijam
No abstract is available for this record.
Jia‐Geng Liu, Igor Makarov, Antoinette Schoar
No abstract is available for this record.
Wenbing Zhao, Izdehar M. Aldyaflah, Pranav Gangwani, Santosh Joshi · 6 authors
In this paper, we present the design, implementation, and evaluation of a secure sensing data processing and logging system. The system is inspired and enabled by blockchain. In this system, a public blockchain is used as immutable data store to store the most critical data needed to secure the system. Furthermore, several innovative blockchain-inspired mechanisms have been incorporated into the system to provide additional security for the system’s operations. The first priority in securing sensing data processing and logging is admission control,i.e., only legitimate sensing data are accepted for processing and logging. This is achieved via a sensor identification and authentication mechanism. The second priority is to ensure that the logged data remain intact overtime. This is achieved by storing a small amount of data condensed from the raw sensing data on a public blockchain. A Merkel-tree based mechanism is devised to link the raw sensing data stored off-chain to the condensed data placed on public blockchain. This mechanism passes the data immutability property of a public blockchain to the raw sensing data stored off-chain. Third, the raw sensing data stored off-chain are secured with a self-protection mechanism where the raw sensing data are grouped into chained blocks with a moderate amount of proof-of-work. This scheme prevents an adversary from making arbitrary changes to the logged data within a short period of time. Fourth, mechanisms are developed to facilitate the search of the condensed data placed on the public blockchain and the verification of the raw sensing data using the condensed data placed on the public blockchain. The system is implemented in Python except the graphical user interface, which is developed using C#. The functionality and feasibility of the system have been evaluated locally and with two public blockchain systems, one is the IOTA Shimmer test network, and the other is Ethereum.
B. Subashini, D. Hemavathi
Due to an increase in agricultural mislabeling and carelesshandling of non-perishable foods in recent years, consumers have been calling for the food sector to be more transparent. Due to information dispersion between divisions and the propensity to record inaccurate data, current traceability solutions typically fail to provide reliable farm-to-fork histories ofproducts. The three most enticing characteristics of blockchain technology areopenness, integrity, and traceability, which make it a potentially crucial tool for guaranteeing the integrity and correctness of data. In this paper, we suggest a permissioned blockchain system run by organizations, such as regulatory bodies, to promote the origin-tracking of shelf-stable agricultural products. We propose a four-tiered architecture, parallel side chains, Zero-Knowledge Proofs (ZKPs), and Interplanetary File Systems (IPFS). These ensure that information about where an item came from is shared, those commercial competitors cannot get to it, those big storage problems are handled, and the system can be scaled to handle many transactions at once. Thesolution maintains the confidentiality of all transaction flows whenprovenance data is queried utilizing smart contracts and a consumer-grade reliance rate. Extensive simulation testing using Ethereum Rinkeby and Polygon demonstrates reduced execution time, latency, and throughput overheads.
Sam McCarthy
No abstract is available for this record.
Gulab Sanjay, S. B. Goyal, Prasenjit Chatterjee
Blockchain technology has gained significant attention as a secure and decentralized platform for various applications. However, the immutable and distributed nature of blockchain also presents unique challenges for detecting anomalies and suspicious activities within the network. This research paper proposes a novel approach to anomaly detection in blockchain using machine learning techniques. The goal of this study is to develop an effective and scalable anomaly detection framework that can analyze the vast amount of data generated within a blockchain network and identify irregularities or potential security threats. The proposed framework leverages the power of machine learning algorithms to learn patterns, relationships, and behaviours from historical blockchain data, enabling the detection of anomalous activities in real time.The research paper first focuses on feature extraction techniques tailored specifically for blockchain data. These techniques consider key characteristics of blockchain transactions, such as transaction size, timestamp, and involved addresses, to construct meaningful features that capture the underlying patterns and trends. Various dimensionality reduction techniques are also explored to handle the high-dimensional nature of blockchain data.Subsequently, several machine learning algorithms, including clustering, classification, and anomaly detection methods, are employed to train models using the extracted features. The performance of different algorithms is evaluated using benchmark datasets and real-world blockchain data to assess their accuracy, precision, and recall in detecting anomalies. Additionally, the scalability of the proposed framework is investigated to ensure its effectiveness in large-scale blockchain networks.Furthermore, the research paper investigates the integration of domain-specific knowledge, such as known attack patterns and regulatory compliance rules, into the anomaly detection framework. This hybrid approach combines the strengths of machine learning algorithms with expert knowledge to enhance the accuracy and interpretability of anomaly detection results.The experimental results demonstrate that the proposed anomaly detection framework achieves promising performance in identifying various types of anomalies in blockchain data. It exhibits high detection rates while minimizing false positives, thereby providing valuable insights for blockchain network administrators and regulators to mitigate security risks and safeguard the integrity of blockchain systems. In conclusion, this research paper presents an innovative approach to anomaly detection in blockchain using machine learning. The proposed framework addresses the unique challenges posed by blockchain's decentralized and immutable nature, offering an effective solution for detecting suspicious activities and ensuring the security of blockchain networks. The findings of this study contribute to the growing field of blockchain analytics and have significant implications for real-world blockchain applications in domains such as finance, supply chain management, and healthcare.
Jonathan Cardoz, Prithvi Gawade, Chirac Parmar, Smita S. Pawar · 5 authors
This project introduces an innovative E-Commerce platform leveraging blockchain technology, specifically built on the Ethereum blockchain.The system employs a decentralized architecture, integrating Smart Contracts written in Solidity for secure and transparent transactions.Key technologies such as Metamask, React, Solidity, HardHat, and NodeJS are utilized, with Ethereum's native cryptocurrency, Ether, serving as a primary component.The decentralized nature of the blockchain ensures immutability and transparency, fostering trust between buyers and sellers.Smart Contracts automate and secure business logic, enabling seamless transactions without intermediaries.The user-friendly interface, developed with React, enhances the overall user experience.Metamask integration provides secure wallet management, facilitating seamless user interaction with the Ethereum blockchain.The backend, powered by NodeJS, ensures scalability and efficiency for various aspects of the E-Commerce platform.Adhering to best practices, the development process utilizes the HardHat environment for Ethereum smart contracts, ensuring a robust and reliable codebase for enhanced security.In summary, this project exemplifies the transformative potential of blockchain technology in decentralizing and creating trust in traditional E-Commerce.By combining Ethereum, Smart Contracts, and a modern tech stack, including React, Metamask, Solidity, HardHat, and NodeJS, the resulting platform offers users a secure, transparent, and efficient online shopping experience.
G. Pavithra, Kunwar Singh
Blockchain-based systems - Bitcoin, Ethereum, etc. - are very famous for various applications but, due to their properties like pseudo-anonymity, no central authority, they can pave way for criminal applications which are difficult to detect. We have proposed one such criminal application (which we call criminal smart contract) that can happen: on the blockchain, how a perpetrator can sell the symmetric key of a specific user to a contractor (who specifies his/her target user of interest) using ZK-SNARKs. We consider that the perpetrator has somehow already stolen/gotten to know the key of the user as specified by the contractor. Through this, we want to emphasise on the point that we have to devise methods to prevent the occurrence of various types of crimes in order to fully leverage the benefits of the blockchain. On this line, we have also provided few counter measures to avoid such cases of privacy and security issues.
Polina Ellina
No abstract is available for this record.
Vinod Salunkhe, R. Sujatha
No abstract is available for this record.
Yu Ma, xingya wang, Xin Gu, Zhihong Zhao
No abstract is available for this record.
Mei Li
This research paper explores the relationship between the global economic policy uncertainty index (GEPU) and Ethereum price.By employing the Hodrick-Prescott Filter Decomposition, the price of Ethereum is decomposed into a trend component, which reflects the increasingly wide usage, and the cyclical component, which shows its character as a safe haven asset and a speculative financial asset.By examining the relationship between the GEPU and the cyclical component of Ethereum, I find that GEPU Granger causes cyclical Ethereum, and they have a cointegration relationship.Their error correction models also demonstrate that cyclical Ethereum responds in the short-run to changes in GEPU and deviations from long-run equilibrium.The dynamics make the cyclical Ethereum converge towards their long-run equilibrium relationship.
Gabriel Marcuzzo do Canto Cavalheiro, Mariana Brandão Cavalheiro
The rapid and enormous market capitalization achieved by Bitcoin in recent years has also increased demand for cryptocurrencies based on blockchain technology.At present, Bitcoin and Ethereum are the leading cryptocurrencies in terms of market capitalization and trading volume.As such, those cryptocurrencies play a central role in the ongoing Decentralized Finance (DeFi) process, which regards the development of a financial ecosystem based on blockchain technology.This comparative study seeks to contribute to filing a gap in the intellectual property management literature by examining the main technological trends associated with both cryptocurrencies based the analysis of patent information.We have found that both Bitcoin and Ethereum started to become a technological hotspot from 2016 onwards, as the number of patent applications for both cryptocurrencies started to skyrocket in this particular year.We also present evidence that both Bitcoin and Ethereum patents address data processing issues, rather than hardware technologies.Furthermore, we observed that the US and China are the main patent applicants regarding Bitcoin, while China is by far the leading applicant of Ethereum patents.
Vaseem Ahmed Qureshi, G. Divya, T. Satayanarayana
No abstract is available for this record.
Noe Elisa, Longzhi Yang, Fei Chao, Nitin Naik · 5 authors
Electronic Government (e-Government) systems constantly provide greater services to people, businesses, organisations, and societies by offering more information, opportunities, and platforms with the support of advances in information and communications technologies. This usually results in increased system complexity and sensitivity, necessitating stricter security and privacy-protection measures. The majority of the existing e-Government systems are centralised, making them vulnerable to privacy and security threats, in addition to suffering from a single point of failure. This study proposes a decentralised e-Government framework with integrated threat detection features to address the aforementioned challenges. In particular, the privacy and security of the proposed e-Government system are realised by the encryption, validation, and immutable mechanisms provided by Blockchain. The insider and external threats associated with blockchain transactions are minimised by the employment of an artificial immune system, which effectively protects the integrity of the Blockchain. The proposed e-Government system was validated and evaluated by using the framework of Ethereum Visualisations of Interactive, Blockchain, Extended Simulations (i.e. eVIBES simulator) with two publicly available datasets. The experimental results show the efficacy of the proposed framework in that it can mitigate insider and external threats in e-Government systems whilst simultaneously preserving the privacy of information.
Komal Manohar Tekale, Nivedita Rahul
In this paper, a model is presented in the operational form of blockchain and smart contract utilization to modernise insurance claims settlement, which is enterprise-ready. Design a permissioned, Ethereum-compatible ledger that encodes policy terms limits, deductibles, exclusions and orchestrates deterministic claim state transitions from First Notice of Loss (FNOL) to payout. Off-chain storage stores sensitive artifacts (PII/PHI, images, medical records) encrypted in vaults, and on-chain records append cryptographic digests and events that can be audited by tampering evidence. This is provided by evidence (in the form of signed oracles, such as weather indices, hospital discharge summaries, police reports), and permits parametric claims to be settled quickly and routine indemnity claims to undergo high straight-through processing (STP) with human attention reserved to exceptions. The methodology emphasizes formal assurance (static analysis, property-based tests, optional formal verification), runtime safety (circuit breakers, timelocked upgrades), and robust key/oracle governance. Pilot testing in pilot testing, the methodology provides a shorter cycle time, less reconciliation, and quantifiable mitigation of fraud-leakage but still ensures regulatory compliance by selective disclosure and privacy-by-design. Also work through the dynamics of constraints throughput and fee dynamics, legal enforceability, legacy interoperability, and privacy-versus-transparency trade-off and a roadmap of staged adoption, starting with low-dispute, oracle-rich products, then triage, partial advances, and subrogation workflows. Findings indicate that blockchain is likely to be the most useful as a coordination/assurance layer to supplement, but not to substitute, fundamental insurance infrastructure
Hao Sui, Jiale Zhang, Xiaobing Sun, Bing Chen · 6 authors
No abstract is available for this record.
Anita Thakur, Virender Ranga, Ritu Agarwal
No abstract is available for this record.
Khiem Huynh Gia, Huong Hoang Luong, Hong Khanh Vo, Phuc Nguyen Trong · 14 authors
Current traditional shipping models are increas-ingly revealing many shortcomings and affecting the interests of sellers and buyers due to having to depend on trusted third parties. For example, the Cash-on-Delivery (CoD) model must depend on the carrier/shipper, or the Letter-of-Credit (LoC) model depends on the place of the Letter certification (i.e., bank). There have been many examples demonstrating the riskiness of the two models above. Specifically, in developing countries (e.g., Vietnam), the demand for exporting goods and trading between sellers and buyers have not yet applied the benefits of current technology to improve traditional shipping models. Two typical examples in the last five years that have demonstrated the risks of both sellers and buyers when applying CoD and LoC models are the problem of keeping the money of the seller of GNN Expresses (2017) as well as risks in losing control of 4 containers of cashew nuts when exporting from Vietnam to Italy (2021). A series of studies have proposed solutions based on distributed storage, blockchain, and smart contracts to solve the above problems. However, the role of the shipper has not been considered in some approaches or is not suitable for deployment in a developed country (i.e., Vietnam). In this paper, we propose a combination model between the traditional CoD model and blockchain technology, smart contracts, and NFT to solve the above problems. Specifically, our contribution includes four aspects: a) proposing a shipping model based on blockchain technology and smart contracts; b) proposing a model for storing package information based on Ethereum’s NFT technology (i.e. ERC721); c) implementing the proposed model by designing smart contracts that support the creation and transfer of NFTs between sellers and buyers; d) deploy smart contracts on four EVM-enabled platforms including BNB Smart chain, Fantom, Celo, and Polygon to find a suitable platform for the proposed model.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves
In this study, we analyse systematic risk associated with the two leading cryptocurrencies - Bitcoin and Ethereum, from 2015 to 2023. Our findings show a significant escalation in the systematic risk levels, with beta estimates rising from 0.032 to 0.834 for Bitcoin, and from 0.087 to 1.003 for Ethereum. This hike in risk levels has dramatically reduced the diversification benefits of cryptocurrency that were documented in prior studies. In addition, we also identify increased autocorrelation of cryptocurrency systematic risk.
Sarat Chandra Nayak, Subhranginee Das, Satchidananda Dehuri, Sung‐Bae Cho
Cryptocurrencies have carved out a significant presence in financial transactions during the past few years. Cryptocurrency market performs similarly to other financial markets with considerable nonlinearity and volatility and its prediction is a growing research area. It is challenging to capture the inherent uncertainties connected with cryptocurrency using the currently used conventional methodologies. The popularity of random vector functional link networks (RVFLN) is attributed to its simple structural layout, quick rate of learning, and enhanced generalization ability. It computes the output layer weights using non-iterative techniques like least square methods or iterative techniques like gradient methods, and assigns hidden neuron parameters at random. Random initialization of non-optimal hidden neuron settings, however, degrades the performance. Population-based metaheuristics are a superior option to random initialization for determining the ideal parameters and avoiding the problem of local optima stagnation. In the current article, an elitist artificial electric field algorithm (eAEFA) for training RVFLN is proposed. Here, eAEFA is utilized to create an ideal RVFLN by determining the weights and biases of the hidden layer connections. The elitism method is used by AEFA to maximize its strength. Here, the most suitable entities are directly inserted to create the population of the following generation. By predicting the closing values of six widely used cryptocurrencies, including Bitcoin, Litecoin, Ethereum, ZEC, XLM, and Ripple, one may determine how well the eAEFA+RVFLN model is performing. For comparison study, models including ARIMA, multi-layer perceptron (MLP), basic RVFLN, support vector regression (SVR), LSTM, GA trained RVFLN, and AEFA trained RVFLN are also constructed concurrently. In terms of performance and statistical significance testing, the suggested eAEFA+RVFLN findings outperform the comparator models. On an average, it achieves a MAPE (mean absolute percentage of error) value of 0.0573, R2(coefficient of determination) of 0.9589, POCID (prediction of change in direction) of 0.9676, RMSE (root mean squared error) of 0.0685, MAE (mean absolute error) of 0.0727 and an average rank of 1.346; as a result, it is possible to recommend it as a useful financial forecasting tool.
Kanis Saengchote, Voraprapa Nakavachara, Yishuang Xu
When land becomes more connected, its value can change because of network externalities. This idea is intuitive and appealing to developers and policymakers, but documenting their importance is empirically challenging because it is difficult to isolate the determinants of land value in practice. We address this challenge with real estate in The Sandbox, a virtual economy built on blockchain, which provides a series of natural experiments that can be used to estimate the causal impact of land-based of network externalities. Our results show that when new land becomes available, the network value of existing land increases, but there is a trade-off as new land also competes with existing supply. Our work illustrates the benefits of using virtual worlds to conduct policy experiments.