COVID-19 is a pandemic outbreak for each country worldwide. Each government needs to monitor every citizen and the COVID-19 test becomes an essential evidence for people who are travelling. This gives rise to the necessity of disruptive technologies such as Blockchain. In this paper, we provide an overview of the Hyperledger and Ethereum platforms and present how healthcare organizations can control and monitor digital health test certificates with citizens or other stakeholders. We also present a smart contract structure and implementation for COVID-19 test certificates in both blockchain platforms.
Open access
Blockchain Technology Applications and Security
Artificial Intelligence in Healthcare and Education
Mengyao Du, Miao Zhang, Yue Hu, Jie Yang · 6 authors
Multi-agent systems (MAS) promote developments in various applications such as rescue, tracking, and health care. Through the cooperation of multiple agents, the system can emerge beyond the ability of individual intelligence. However, considering the flexibility and mobility of agents, accountability and trusted interactions among agents have become mandatory aspects. One of the challenges in developing multi-agent systems is the design of appropriate coordination strategies. In this paper, we leverage the features of Ethereum architecture and propose a novel Clique-based distributed multi-agent system. The advantages of our system include secure, self-governing, and tamper-proof properties. We implement our system framework and test custom smart contracts based on a private blockchain in Ethereum. The experimental results show that the resource consumption of our proposed scheme is reasonable and feasible.
Most of the existing smart-contract-based cryptocurrencies, such as Ethereum, use an account-based ledger. However, while the account-based model is advantageous for the efficient use of smart contracts and the increased exchangeability of cryptocurrencies, it is not well-suited to the parallel execution of smart contracts. However, unspent transaction output (UTXO)-based cryptocurrencies such as Bitcoin are advantageous for parallel cryptocurrency transfers but not well-suited to smart contracts. In this paper, we propose a hierarchical multi-blockchain system that uses multiple pairs of sidechain and dual-sidechains extended by independent block mining in their blockchain networks and a mainchain to control the branching and connection process of sidechains and dual sidechains. In the proposed method, one pair of a sidechain and dual sidechain forms one shard. The proposed method uses multiple shards to execute cryptocurrency transfers and smart contracts in parallel. In addition, the proposed model uses an accoutchain to record the resulting state changes generated by smart contract executions in each shard and securely share them with all other nodes. The proposed method uses a modifiable blockchain structure for the accountchain to obtain the database to record the smart contract execution results in each shard in as small and secure a manner as possible to ensure that all nodes trust the recorded results without executing smart contracts themselves. To examine the validity of the proposed method, we conducted a threat analysis of the proposed method by examining possible attacks in various scenarios as a thought experiment. This threat analysis concludes that the proposed blockchain system can execute smart contracts in parallel while keeping the concurrency in resulting state changes secure.
Unmanned aerial vehicles (UAVs) are gaining immense attention due to their potential to revolutionize various businesses and industries. However, the adoption of UAV-assisted applications will strongly rely on the provision of reliable systems that allow managing UAV operations at high levels of safety and security. Recently, the concept of UAV traffic management (UTM) has been introduced to support safe, efficient, and fair access to low-altitude airspace for commercial UAVs. A UTM system identifies multiple cooperating parties with different roles and levels of authority to provide real-time services to airspace users. However, current UTM systems are centralized and lack a clear definition of protocols that govern a secure interaction between authorities, service providers, and end-users. The lack of such protocols renders the UTM system unscalable and prone to various cyber attacks. Another limitation of the currently proposed UTM architecture is the absence of an efficient mechanism to enforce airspace rules and regulations. To address this issue, we propose a decentralized UTM protocol that controls access to airspace while ensuring high levels of integrity, availability, and confidentiality of airspace operations. To achieve this, we exploit key features of the blockchain and smart contract technologies. In addition, we employ a mobile crowdsensing (MCS) mechanism to seamlessly enforce airspace rules and regulations that govern the UAV operations. The solution is implemented on top of the Etheruem platform and verified using four different smart contract verification tools. We also provided a security and cost analysis of our solution. For reproducibility, we made our implementation publicly available on Github.
Noura Metawa, Mohamemd I. Alghamdi, Ibrahim M. El‐Hasnony, Mohamed Elhoseny
Recently, bitcoin-based blockchain technologies have received significant interest among investors. They have concentrated on the prediction of return and risk rates of the financial product. So, an automated tool to predict the return rate of bitcoin is needed for financial products. The recently designed machine learning and deep learning models pave the way for the return rate prediction process. In this aspect, this study develops an intelligent return rate predictive approach using deep learning for blockchain financial products (RRP-DLBFP). The proposed RRP-DLBFP technique involves designing a long short-term memory (LSTM) model for the predictive analysis of return rate. In addition, Adam optimizer is applied to optimally adjust the LSTM model’s hyperparameters, consequently increasing the predictive performance. The learning rate of the LSTM model is adjusted using the oppositional glowworm swarm optimization (OGSO) algorithm. The design of the OGSO algorithm to optimize the LSTM hyperparameters for bitcoin return rate prediction shows the novelty of the work. To ensure the supreme performance of the RRP-DLBFP technique, the Ethereum (ETH) return rate is chosen as the target, and the simulation results are investigated in different measures. The simulation outcomes highlighted the supremacy of the RRP-DLBFP technique over the current state of art techniques in terms of diverse evaluation parameters. For the MSE, the proposed RRP-DLBFP has 0.0435 and 0.0655 compared to an average of 0.6139 and 0.723 for compared methods in training and testing, respectively.
The advent of blockchain technology has transformed traditional business processes from centralized to decentralized. By eliminating the unnecessary intervention of middlemen, it can reduce the overall cost of patient medication by turning the drug supply chain entirely into a point-to-point decentralized business. This paper presents a reliable and encouraging P2P drug trading block chain technology and four related smart contracts. These contracts include consumer contracts and the supply, bidding and trading of drugs, which have been deployed on the Ethereum blockchain for the decentralized trading of drugs. We will use the Approach of Real cost descending (RCD) to achieve incentive transactions for suppliers and patients. This method provides P2P transactions and ensures the safety and transparency of drug data, as well as the anonymity of users in the transaction process. Finally, according to the requirements of Good Supplying Practice(GSP), the effectiveness of the proposed model is evaluated and analyzed.
Ethereum Smart contracts are pieces of code that are run on this blockchain. The correctness of smart contracts is important as they are immutable, their source can be seen by everyone, and they transfer Ether. In this paper, we propose a framework for the automated generation of a set of effective test cases for a given smart contract. We use symbolic execution for generation and mutation testing for selection of test cases. We have evaluated our tool on a set of smart contracts, and our results show how mutation can reduce the size of test suites generated by symbolic execution. Also, by analyzing the survived mutants, we have interesting results about effective test cases that cannot be generated by the symbolic execution engine for smart contracts.
Abstract: A decentralised, Secure, Peer-to-Peer Multi-Voting System on Ethereum Blockchain is a distributed ledger technology (DLT) that permits virtual votes to be transacted in a peer-to-peer decentralized network. Those transactions are validated and registered through every node of the network, so creating a transparent and immutable series of registered events whose truthfulness is supplied through a consensus protocol. Smart contract automates the execution of agreement that runs routinely as soon as the conditions are satisfied. Smart contract would not need any third parties consequently prevents time loss. By Eliminating the requirement for third parties, consequently, allows numerous processes to be extra efficient and economical. The system is secure, reliable, and anonymous. Smart contract is enforced for the Ethereum network using the Ethereum wallets and also the Solidity language. Users are capable of submit their votes immediately from their Ethereum wallets, and those transaction requests is handled with the consensus of each single Ethereum node. This creates a transparent environment for evoting. A lot of concerning efficiency of the peer-to-peer decentralized electoral system on Ethereum network along with application and the outcomes of implementation are provided in this paper. Keywords: Blockchain, Distributed Ledger Technology (DLT), Consensus Protocol, Smart Contracts, Ethereum, Solidity
Francesco Maria De Collibus, Alberto Partida, Matija Piškorec, Claudio J. Tessone
In this study, we analyse the aggregated transaction networks of Ether (the native cryptocurrency in Ethereum) and the three most market-capitalised ERC-20 tokens in this platform at the time of writing: Binance, USDT, and Chainlink. We analyse a comprehensive dataset from 2015 to 2020 (encompassing 87,780,546 nodes and 856,207,725 transactions) to understand the mechanism that drives their growth. In a seminal analysis, Kondor et al. (PLoS ONE, 2014, 9: e86197) showed that during its first year, the aggregated Bitcoin transaction network grew following linear preferential attachment. For the Ethereum-based cryptoassets, we find that they present in general super-linear preferential attachment, i.e., the probability for a node to receive a new incoming link is proportional to k α , where k is the node’s degree. Specifically, we find an exponent α = 1.2 for Binance and Chainlink, for Ether α = 1.1, and for USDT α = 1.05. These results reveal that few nodes become hubs rapidly. We then analyse wealth and degree correlation between tokens since many nodes are active simultaneously in different networks. We conclude that, similarly to what happens in Bitcoin, “the rich indeed get richer” in Ethereum and related tokens as well, with wealth much more concentrated than in-degree and out-degree.
Machine learning models have been widely used for fraud detection, while developing and maintaining these models often suffers from significant limitations in terms of training data scarcity and constrained resources. To address these issues, in this paper, we leverage machine learning vulnerability to adversarial attacks, and design a novel model AdvRFD that Adversarially Reprograms an ImageNet classification neural network for Fraud Detection task. AdvRFD first embeds transaction features into a host image to construct new ImageNet data, and then learns a universal perturbation to be added to all inputs, such that the outputs of the pretrained model can be accordingly mapped to the final detection decisions for all transactions. Extensive experiments on two transaction datasets made over Ethereum and credit cards have demonstrated that AdvRFD is effective to detect fraud using limited data and resources.
The COVID-19 pandemic has profoundly affected almost all facets of peoples' lives, various economic areas and regions of the world. In such a situation implementation of a vaccination can be viewed as essential but its success will be dependent on availability and transparency in the distribution process that will be shared among the stakeholders. Various distributed ledgers (DLTs) such as blockchain provide an open, public, immutable system that has numerous applications due the mentioned abilities. In this paper the authors have proposed a solution based on blockchain to increase the security and transparency in the tracing of COVID-19 vaccination vials. Smart contracts have been developed to monitor the supply, distribution of vaccination vials. The proposed solution will help to generate a tamper-proof and secure environment for the distribution of COVID-19 vaccination vials. Proof of delivery is used as a consensus mechanism for the proposed solution. A feedback feature is also implemented in order to track the vials lot in case of any side effect cause to the patient. The authors have implemented and tested the proposed solution using Ethereum test network, RinkeyBy, MetaMask, one clicks DApp. The proposed solution shows promising results in terms of throughput and scalability.
Muhammad Danil Muis, Muhammad Rifki Fauzan, Parman Sukarno, Aulia Arif Wardana
This reserach build access control and file distribution management system for electronic diploma and transcript using ethereum smart contract and InterPlanetary File System (IPFS). The falsification of diplomas/transcripts is one of the problems in education. In Indonesia, falsification of diplomas/transcripts is a form of criminal act of falsifying letters. In addition, diplomas/transcripts that have not been digitalized make them easily damaged, lost, and difficult to manage. Therefore, this research developed digital diploma/transcript as digital twin from the hardcopy of diploma/tramscript. This research used IPFS to store data in a distributed system and Smart Contracts Blockchain to store and protect the digital diploma/transcript. The system also comes with access control to create and give approval for diplomas or transcripts to be published and saved into the system. Access control settings will be saved using the blockchain. This research using Quality of Service test method for measurethroughput, packet loss, and delay. Beside that, tis research also analysis the usage of Central Processing Unit and Random Access Memory from the system. Based on the test that has been done, the fake diploma/transcript detection system can be run properly by using 1 node to 5 nodes. The best throughput value during the process of making and validating the diploma/transcript is to use 1 node. The value of packet loss in the process of making and validating the certificate/transcript has a very good category. The value of delay in the process of making and validating the diploma/transcript has a very good category.
Fakultas Ekonomi dan Bisnis, Universitas Sumatera Utara, Medan, Mutia Fitri Chania, Oyami Sara, Fakultas Ekonomi dan Bisnis, Universitas Sumatera Utara, Medan · 6 authors
Abstract Purpose: This research aims to analyze the risk and return of investing in ethereum and LQ45 shares and to see the difference between LQ45 stock prices and ethereum prices before and after the announcement of the Covid-19 pandemic in Indonesia. Research Methodology: The research method uses the Kruskall-Wallis test and the Paired Sample t-test. Results: The results show the level of the return on ethereum and LQ45 shares did not have a significant difference, while the level of the risk between ethereum and LQ45 shares have a significant difference. For the price of Ethereum and LQ45 shares, there was a significant difference between before and after the Covid-19 pandemic was announced in Indonesia. The average price of ethereum and LQ45 shares decreased compared to before the announcement of the Covid-19 pandemic in Indonesia. Limitations: This research was conducted without including the risk-free rate in the calculation of stock risk. Contribution: This research is expected to be a reference for investors in viewed and analyzed investment opportunities based on risk and return during Covid-19.
In this paper the author’s interpretation of essence and applicability of smart-contracts in economics. Examples are given along with critical view on wrong statements, found in publications on examined topic. Repeating of certain theses from similar papers won’t be redundant, because it will help to observe the topic from different point of view. In general, author gives positive valuation of applicability of smart-contracts technology in economics (both, financial and real sector, despite of some obvious inherent disadvantages of current implementation in Ethereum. In author’s opinion, integration of smartcontracts and blockchain with IoT can give synergetic effect and consider real cyber-social interaction. Certain value to this paper is added by author’s practical experience of coding and adopting smart-contracts. Smart-contracts are mentioned by Bank of Russia with implementation of CBDC (Central Bank Digital Currency) concept in the form of digital rubble and receive additional significance in current trend of dematerialization and virtualization of money. In paper essential terms and author’s point to ability to change contract terms after deploy are given.
Aastha Agarwal, S Keerthana, Rahul Reddy, Afraz Moqueem
Bitcoin, Etherium, and Litecoin are among the most extensive market capitalized cryptocurrencies in the present era. With the increased popularity, there is also an increased proclivity of investors towards investing in cryptocurrencies. To gain maximum profits and avoid risks, one needs to analyze the trends and history of the cryptocurrency diligently. This paper put forth various machine learning algorithms to scrutinize cryptocurrencies such as Bitcoin, Etherium, and Litecoin based on multiple trading factors such as open price, close price, volume, market price, history, etc. We have performed various state-of-the-art machine learning to predict the future market value of the cryptocurrencies and derived the performance analysis of the same.
Simone Casale-Brunet, Paolo Ribeca, Patrick Charles Doyle, Marco Mattavelli
Non-fungible tokens (NFTs) as a decentralized proof of ownership represent one of the main reasons why Ethereum is a disruptive technology. This paper presents the first systematic study of the interactions occurring in a number of NFT ecosystems. We illustrate how to retrieve transaction data available on the blockchain and structure it as a graph-based model. Thanks to this methodology, we are able to study for the first time the topological structure of NFT networks and show that their properties (degree distribution and others) are similar to those of interaction graphs in social networks. Time-dependent analysis metrics, useful to characterize market influencers and interactions between different wallets, are also introduced. Based on those, we identify across a number of NFT networks the widespread presence of both investors accumulating NFTs and individuals who make large profits.
Blockchain, as a distributed ledger technology, becomes increasingly popular, especially for enabling valuable cryptocurrencies and smart contracts. However, the blockchain software systems inevitably have many bugs. Although bugs in smart contracts have been extensively investigated, security bugs of the underlying blockchain systems are much less explored. In this paper, we conduct an empirical study on blockchain's system vulnerabilities from four representative blockchains, Bitcoin, Ethereum, Monero, and Stellar. Specifically, we first design a systematic filtering process to effectively identify 1,037 vulnerabilities and their 2,317 patches from 34,245 issues/PRs (pull requests) and 85,164 commits on GitHub. We thus build the first blockchain vulnerability dataset. We then perform unique analyses of this dataset at three levels, including (i) file-level vulnerable module categorization by identifying and correlating module paths across projects, (ii) text-level vulnerability type clustering by natural language processing and similarity-based sentence clustering, and (iii) code-level vulnerability pattern analysis by generating and clustering code change signatures that capture both syntactic and semantic information of patch code fragments. Our analyses reveal three key findings: (i) some blockchain modules are more susceptible than the others; notably, each of the modules related to consensus, wallet, and networking has over 200 issues; (ii) about 70% of blockchain vulnerabilities are of traditional types, but we also identify four new types specific to blockchains; and (iii) we obtain 21 blockchain-specific vulnerability patterns that capture unique blockchain attributes and statuses, and demonstrate that they can be used to detect similar vulnerabilities in other popular blockchains, such as Dogecoin, Bitcoin SV, and Zcash.
Murat Tunç, Thomas van den Heuvel, Hasan Cavusoglu, Zhiqiang Zheng
Startups adopt non-fungible token (NFT) standard on Ethereum network and create marketplaces for collectible assets, trading cards and digital art. NFTs minted on blockchain must be paid a gas fee to miners at delivery. Due to increased traffic on Ethereum blockchain network, the constant upsurge in cost of minting bear hard on monetary security of token creators. As a potential cure for ever-rising minting cost, NFT platform managers adopt resale royalty which is a practice that transfers a fixed percentage of future sale amount to the creator of digital good. The adoption of resale royalty is seemingly beneficial for token creators as it provides a recurrent cash flow. However, it may have unintended consequences on the sale prices, which, in turn, affects the commission revenue for the platforms. In this paper, we develop several hypotheses for the impact of resale royalty on average sale prices on the primary and secondary markets. We leverage a panel dataset from a popular NFT marketplace and test our hypotheses using instrumental variables estimation. We find that the resale royalty leads to a significant decrease in the average primary sale price. We also find evidence that the average secondary sale price significantly increases with resale royalty. Our estimations suggest that token creators benefit from NFTs with resale royalty only after they are sold on the secondary market numerous times. Contrary to the conventional wisdom, re-sellers are better off when they make investments to NFTs with resale royalty even after adjusting for the royalty premium. We argue the managerial implications of the adoption of resale royalty for platform managers, token creators and re-sellers.
Johnnatan Messias, Mohamed Alzayat, B. Chandrasekaran, Krishna P. Gummadi · 6 authors
Most public blockchain protocols, including the popular Bitcoin and Ethereum blockchains, do not formally specify the order in which miners should select transactions from the pool of pending (or uncommitted) transactions for inclusion in the blockchain. Over the years, informal conventions or "norms" for transaction ordering have, however, emerged via the use of shared software by miners, e.g., the GetBlockTemplate (GBT) mining protocol in Bitcoin Core. Today, a widely held view is that Bitcoin miners prioritize transactions based on their offered "transaction fee-per-byte." Bitcoin users are, consequently, encouraged to increase the fees to accelerate the commitment of their transactions, particularly during periods of congestion. In this paper, we audit the Bitcoin blockchain and present statistically significant evidence of mining pools deviating from the norms to accelerate the commitment of transactions for which they have (i) a selfish or vested interest, or (ii) received dark-fee payments via opaque (non-public) side-channels. As blockchains are increasingly being used as a record-keeping substrate for a variety of decentralized (financial technology) systems, our findings call for an urgent discussion on defining neutrality norms that miners must adhere to when ordering transactions in the chains. Finally, we make our data sets and scripts publicly available.
A large number of grid-connected distributed photovoltaic and wind power generation projects bring challenges to traditional electricity market trading. A distributed power trading model based on blockchain technology is designed in this paper, and the transaction process is introduced in detail. The transaction is established in an annual cycle and settled monthly. The trading model adopts the average price of the sellers' and buyers' quotation price by matching, and the matching transaction takes into account the influence of the differences in transmission prices between different buyers and sellers. The matching transaction mechanism and the monthly transaction settlement mechanism are elaborated. A distributed power trading system based on blockchain technology is developed on the Ethereum platform. Combined with a distributed power trading example, the feasibility of the trading system for distributed power trading is verified.
In the real scene of project management, the lifetime management of information about the project s an important content of the project information management. Aiming at technical risks such as information storage pressure, the risk of data lost or improper using in the information management of project as well as moral risks such as department misuse of authority, even bending the information, refusing to provide the real information. In this paper, we resorted to the basic idea of parallel control. Firstly, we put up the mechanism structure that basic on real world and the virtual world that block chain and smart contract found.via the interaction and comparison between the real record in the real world and the record in block chain and smart contract which can not be tampered, to face up the above risks. Second, taking the execution of the project as an example, we designed the contract of parallel management of the project, provided the module contracts with SPESC language . These contracts can be transformed to solidity contract and deploy on Ethereum to run.