Based on the VAR model, we use Bitcoin prices as well as the Ethereum price daily data between December 2019 and January 2022 for dynamic identification, and the empirical analysis results show that the Bitcoin price is the granger reason of Ethereum prices, but Ethereum price is not the Bitcoin prices granger reason, namely in the long run the Bitcoin price fluctuation can affect the Ethereum price fluctuations, But Ethereum price fluctuations do not affect bitcoin price fluctuations. Meanwhile, according to the impulse response diagram, when the Bitcoin price is impacted by one unit, the Ehereum price will fluctuate greatly and approach 0 in the 11th phase. Based on the above research conclusions, this paper will put forward corresponding policy suggestions.
Matheus V. X. Ferreira, Daniel J. Moroz, David C. Parkes, Mitchell Stern
In recent years, prominent blockchain systems such as Bitcoin and Ethereum have experienced explosive growth in transaction volume, leading to frequent surges in demand for limited block space and causing transaction fees to fluctuate by orders of magnitude. Existing systems sell space using first-price auctions; however, users find it difficult to estimate how much they need to bid in order to get their transactions accepted onto the chain. If they bid too low, their transactions can have long confirmation times. If they bid too high, they pay larger fees than necessary. In light of these issues, new transaction fee mechanisms have been proposed, most notably EIP-1559, aiming to provide better usability. EIP-1559 is a history-dependent mechanism that relies on block utilization to adjust a base fee. We propose an alternative design - a dynamic posted-price mechanism - which uses not only block utilization but also observable bids from past blocks to compute a posted price for subsequent blocks. We show its potential to reduce price volatility by providing examples for which the prices of EIP-1559 are unstable while the prices of the proposed mechanism are stable. More generally, whenever the demand for the blockchain stabilizes, we ask if our mechanism is able to converge to a stable state. Our main result provides sufficient conditions in a probabilistic setting for which the proposed mechanism is approximately welfare optimal and the prices are stable. Our main technical contribution towards establishing stability is an iterative algorithm that, given oracle access to a Lipschitz continuous and strictly concave function f, converges to a fixed point of f.
Blockchain for health care has the potential to standardize secure data exchange in a less burdensome way. Traditional data-sharing platforms rely on a third party. Owning to the consideration of a third party, such systems compromised transparency, trust, and integrity. To solve the aforementioned issues, we have proposed a smart contract-based secure data-sharing scheme in healthcare by leveraging the advantages of the interplanetary file system (IPFS). Our scheme achieves data confidentiality, integrity, and access control rules by implementing the access control policy written in a smart contract by active entities. This thesis is to attain higher levels of medical records security using Ethereum Blockchain methods. Finally, it also helps organ donation, to incentivize medical stakeholders such as researchers, health authorities, etc. to participate in the network as blockchain miners. This provides them with access to aggregate, anonymous data mining awards in return for sustaining, and securing the network.
Сергій Михайлович Фролов, Volodymyr Orlov, Regional State Administration, Yevhenii Kozmenko
The paper notes that at the present stage, research primarily by foreign scientists defines decentralized finance as based on the cryptocurrency ecosystem. The development of new financial technologies, which led to the emergence of digital currency, and its attractiveness, primarily as an asset for investment, have already formed a certain ecosystem of cryptocurrencies. In particular, the functioning of crypto-exchanges, which include various participants: issuers providing mining, agents and a kind of intermediaries in cryptocurrency transactions during the circulation of stablecoins. The dynamics of market capitalization of cryptoassets was analyzed according to the statistics of the International Monetary Fund (IMF), which increased more than 10.5 times (from USD 191.6 bln at the beginning of 2020 to USD 2,027.5 bln as of the end of September 2021). At the same time, it should be noted that the structure of the cryptocurrency market is unstable, which is typical for the new market that is in its infancy. This is confirmed by the market capitalization structure of bitcoin, ethereum, and stablecoins for the above period. Based on IMF data, indicators characterizing the state of formation of the cryptocurrency ecosystem, namely, bitcoin volatility and market capitalization of tokens, are analyzed. It is noted that the fairly rapid spread in the global financial space, and especially the growing attractiveness of cryptocurrencies in emerging financial markets, require the study of possible risks, arising from the formation of an ecosystem of cryptocurrencies and decentralized finance to ensure the stability of the centralized financial system. The main financial stability risks associated with the cryptocurrency ecosystem are systematized and grouped into key blocks: operational risk, cyber risk, misappropriation, bribery and corruption, as well as risks related to financial imbalances. The emphasis is on a problem that is formed purely in the field of decentralized finance and is associated with the development of peer-to-peer lending, crowdfunding and crowdinvesting. A generalization is made about the understanding of the ecosystem in the financial system (financial ecosystem), which is used in modern research at two levels: at the micro level it reflects the business model of a financial institution, and at the macro level it reflects the transformation of the financial system under the influence of financial technology. The formation of the financial ecosystem was the result of the intensive development of financial technologies (FinTech), among which neobanks are the most popular today. In addition, a classification of neobanks is proposed with an emphasis on the level of digitalization.
Controversy surrounding whether cryptocurrency is a bubble and whether the price of bitcoin should be zero instead of $40.000 USD ignores a foundational problem: cryptocurrency has been assessed based on the wrong assumptions. This article outlines a method for providing a more suitable and reasonable assessment of the real value of cryptocurrency. The main argument against cryptocurrency has been that there is nothing behind it. Backing a traditional currency is a national bank, a state and the right of taxation. When cryptocurrency is measured these traditional measures it falls short and the value calculation comes to zero. However, a cryptocurrency is not a traditional currency and should not be measured as such. Instead, it is the associated blockchain that provides cryptocurrency its real value and not its properties as a currency. A blockchain is a digital platform. A piece of software that supports the demand of different companies for a common independent ledger. The valuation of a cryptocurrency must, therefore, be based on the value of its blockchain. The right question to ask is “How valuable is the blockchain itself?” From that point of view, it is clear that a cryptocurrency must be priced more like the price of a digital platform company rather than as a regular currency. To demonstrate the usefulness of this approach the value of Bitcoin, Ethereum, Ripple, Solana, Filecoin, and Cardano is assessed, and it is suggested that several of these cryptocurrencies—when understood and priced as digital platforms—are priced low in relation to their business potential and application area.
New technologies have a significant role in modern financial markets. The application of new technologies, application and software solutions has enabled financial institutions and individual and institutional investors to use mathematical-statistical and econometric models, which are based on analysis and evaluation of investment portfolios, financial risk assessment and extrapolation, as well as predictability related to cyclical economic trends, which are directly reflected in the investment portfolio. Due to the impact of the financial crisis, and especially due to global negative economic trends caused by the COVID-19 pandemic, alternative forms of financial assets that are directly created by the application of new technologies are becoming increasingly important in the international financial market. These alternative forms of financial assets are presented as cryptocurrencies. Bitcoin is the first cryptocurrency in the global financial market, and Ethereum is the second cryptocurrency in terms of market turnover. In this regard, arises the question: "Do these two leading cryptocurrencies have a significant impact on the modern financial market, as well as on the decision of individual and institutional investors regarding a different structure of the investment portfolio?" Restructuring the investment portfolio by including cryptocurrencies, aims to achieve portfolio diversification in order to better manage market and financial risks. This paper will analyze the impact of cryptocurrencies, their volatility, turnover volume and the possibility of using them as alternative financial assets of an optimal investment portfolio.
Cryptocurrencies have won a lot of attention as an investment tool in recent years. Specific research has been done on cryptocurrencies’ price prediction while the prices surge up. Classic models and recurrent neural networks are applied for the time series forecast. However, there remains limited research on how the Transformer works on forecasting cryptocurrencies price data. This paper investigated the forecasting capability of the Transformer model on Bitcoin (BTC) price data and Ethereum (ETH) price data which are time series with high fluctuation. Long short term memory model (LSTM) is employed for performance comparison. The result shows that LSTM performs better than Transformer both on BTC and ETH price prediction. Furthermore, in this paper, we also investigated if sentiment analysis can help improve the model’s performance in forecasting future prices. Twitter data and Valence Aware Dictionary and sEntiment Reasoner (VADER) is used for getting sentiment scores. The result shows that the sentiment analysis improves the Transformer model’s performance on BTC price but not ETH price. For the LSTM model, the sentiment analysis does not help with prediction results. Finally, this paper also shows that transfer learning can help on improving the Transformer’s prediction ability on ETH price data.
The current legacy system used in processing health insurance claims causes a huge amount of financial loss every year due to fraud claims. It is also highly prone to privacy and security threats due to the use of traditional methods. Health insurance claims for prescription drugs are one such claim that is highly prone to being tampered with. Also, there is a lack of linkage in the prescription data between the medical care provider and the pharmacy, which also leads to miscommunication and the use of false prescriptions. In this paper, we propose processing health insurance claims for drug prescriptions using blockchain technology that manages the processing of prescription drugs in a private, secure, trustworthy, and decentralized manner. The proposed system utilizes a private Ethereum blockchain. The system includes two smart contracts: registration and approval smart contracts, which provide traceability and trustworthiness to the system. The system was integrated with off-chain storage (IPFS) and a fronted decentralized applications (DApps), which improves the accessibility of centralized patient information by authorized parties. To maintain the privacy of the data, a gateway is used to filter the data that can be viewed by the participants. We present the system architecture, sequence diagrams, entity-relationship diagram, and algorithms to demonstrate the working principles of the proposed process for processing health insurance claims for prescription drugs using blockchain. The performance of the proposed solution is evaluated by conducting security analysis and comparing it to the existing solutions. Our smart contract code is publicly available on GitHub.
Elvira Albert, Pablo Gordillo, Alejandro Hernández-Cerezo, Clara Rodríguez-Núñez · 5 authors
Abstract The use of the Ethereum blockchain platform [17] has experienced an enormous growth since its very first transaction back in 2015 and, along with it, the verification and optimization of the programs executed in the blockchain (known as Ethereum smart contracts ) have raised considerable interest within the research community.
Blockchain is a revolutionary new technology that facilitates peer-to-peer transfer of value without the need for a centralised intermediary. It uses cryptographic hashing functions, consensus protocols and decentralised data storage to ensure security, decentralised trust, immutability and transparency of business transactions. Blockchain technology paired with smart contracts is a reliable method of automating business rules in an efficient and trustworthy mechanism. A smart contract is a self-executing piece of code that runs on a blockchain platform. Predefined rules between participating organisations are translated into smart contract functions to establish trust. Blockchain is undergoing rapid development and has revolutionary potential for application in Intelligent Transport Systems applications. Blockchain can be used to create a secure, reliable and decentralised autonomous system, creating the best use of legacy infrastructure and resources. One of the most important issues is security, caused by the evolution of ITS towards centralisation. Fast-growing technologies, including the Internet of Things (IoT) and cloud computing, allow most data processing, analysis and decision-making to be done by centralised systems. The distinguishing factor of Ethereum is that it is programmed according to user requirements, rather than providing users with a set of predefined transactions, such as Bitcoin transactions. As a result, it could theoretically be used to automatically and securely execute any transaction involving trust, security or persistence. Although Ethereum is a relatively new implementation of blockchain, it has sparked reaction because of its potential to change the way many businesses operate.
Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammad Saidur Rahman, Abdelaziz Bouras
Smart manufacturing systems involve a large number of interconnected devices resulting in massive data generation. Cloud computing technology has recently gained increasing attention in smart manufacturing systems for facilitating cost-effective service provisioning and massive data management. In a cloud-based manufacturing system, ensuring authorized access to the data is crucial. A cloud platform is operated under a single authority. Hence, a cloud platform is prone to a single point of failure and vulnerable to adversaries. An internal or external adversary can easily modify users' access to allow unauthorized users to access the data. This paper proposes a role-based access control to prevent modification attacks by leveraging blockchain and smart contracts in a cloud-based smart manufacturing system. The role-based access control is developed to determine users' roles and rights in smart contracts. The smart contracts are then deployed to the private blockchain network. We evaluate our solution by utilizing Ethereum private blockchain network to deploy the smart contract. The experimental results demonstrate the feasibility and evaluation of the proposed framework's performance.
With a growing number of institutions involved in the global education market, it has become increasingly challenging to verify the authenticity of academic achievements such as CVs and diplomas. Blockchain is an enabling technology that can play a key role in solving this problem. This study introduces a blockchain-based achievement record system that produces a verifiable record of achievements. The proposed system aims to facilitate the process of authentication and validation of certificates reliably, easily, and quickly, leveraging the unique capabilities offered through Blockchain technology (public Ethereum Blockchain) and smart contracts. We present the design and implementation of the system and its components and tools. We then evaluate the system through a number of studies to measure the system's usability, effectiveness, performance, and cost. A System Usability Scale (SUS) test gave a scale of 77.1. Through a literature survey, we demonstrate that this system is a significant improvement on legacy systems, being both more user-friendly and more efficient. We also conduct a detailed cost analysis and discuss the positives and limitations of alternative blockchain solutions.
Due to the rising complexity of the metaverse's business logic and the low-latency nature of the metaverse, developers typically encounter the challenge of effectively reading, writing, and retrieving historical on-chain data in order to facilitate their functional implementations at scale. While it is true that accessing blockchain states is simple, more advanced real-world operations such as search, aggregation, and conditional filtering are not available when interacting directly with blockchain networks, particularly when dealing with requirements for on-chain event reflection. We offer Matrix Syncer, the ultimate middleware that bridges the data access gap between blockchains and end-user applications. Matrix Syncer is designed to facilitate the consolidation of on-chain information into a distributed data warehouse while also enabling customized on-chain state transformation for a scalable storage, access, and retrieval. It offers a unified layer for both on- and off-chain state, as well as a fast and flexible atomic query. Matrix Syncer is easily incorporated into any infrastructure to aggregate data from various blockchains concurrently, such as Ethereum and Flow. The system has been deployed to support several metaverse projects with a total value of more than $15 million USD.
Ayelet Lotem, Sarah Azouvi, Patrick McCorry, Aviv Zohar
Many prominent smart-contract applications such as payment channels, auctions, and voting systems often involve a mechanism in which some party must respond to a challenge or appeal some action within a fixed time limit. This pattern of challenge-response mechanisms poses great risks if during periods of high transaction volume, the network becomes congested. In this case fee market competition can prevent the inclusion of the response in blocks, causing great harm. As a result, responders are allowed long periods to submit their response and overpay in fees. To overcome these problems and improve challenge-response protocols, we suggest a secure mechanism that detects congestion in blocks and adjusts the deadline of the response accordingly. The responder is thus guaranteed a deadline extension should congestion arise. We lay theoretical foundations for congestion signals in blockchains and then proceed to analyze and discuss possible attacks on the mechanism and evaluate its robustness. Our results show that in Ethereum, using short response deadlines as low as 3 hours, the protocol has >99% defense rate from attacks even by miners with up to 33% of the computational power. Using shorter deadlines such as one hour is also possible with a similar defense rate for attackers with up to 27% of the power.
Money transfer is an abstraction that realizes the core of cryptocurrencies. It has been shown that, contrary to common belief, money transfer in the presence of Byzantine faults can be implemented in asynchronous networks and does not require consensus. Nonetheless, existing implementations of money transfer still require a quadratic message complexity per payment, making attempts to scale hard. In common blockchains, such as Bitcoin and Ethereum, this cost is mitigated by payment channels implemented as a second layer on top of the blockchain allowing to make many off-chain payments between two users who share a channel. Such channels require only on-chain transactions for channel opening and closing, while the intermediate payments are done off-chain with constant message complexity. But payment channels in-use today require synchrony; therefore, they are inadequate for asynchronous money transfer systems. In this paper, we provide a series of possibility and impossibility results for payment channels in asynchronous money transfer systems. We first prove a quadratic lower bound on the message complexity of on-chain transfers. Then, we explore two types of payment channels, unidirectional and bidirectional. We define them as shared memory abstractions and prove that in certain cases they can be implemented as a second layer on top of an asynchronous money transfer system whereas in other cases it is impossible.
Khoi Le Quoc, Phuc Nguyen Trong, Hieu Le Van, Hong Khanh Vo · 13 authors
The exchange of goods between countries is growing, contributing to the promotion of logistics-related technologies. More and more systems are adopting advances in science and engineering to reduce manual handling steps, thereby reducing transit time. Letter-of-Credit (LOC) is a standard method where the parties involved will enter into agreements for the sale and exchange of goods. Specifically, each party will receive a set of original documents and does not need to meet face-to-face under the bank’s witness. The process brings many benefits in terms of time and reduces records processing. However, the system faces a lot of risks when one of the parties is dishonest. On the other hand, the traditional LOC systems face a lot of risks related to the transparency of information about the goods, and also the supplier may lose the goods (e.g., 4/100 Vietnamese cashew nut containers are lost. stuck in Italy) or deposits in the hands of shipping companies (e.g., GNN Express - Vietnam) and many more. To this end, many research directions have exploited blockchain technology and smart contracts. Specifically, all information related to the transaction between the supplier and the demander including package, time, and delivery location. However, there needs to be a mechanism to ensure the smooth implementation of smart contracts, specifically for sanctioning when there is a conflict between a supplier and a demander. This role should be considered for the transaction manager, who directly designs and is responsible for their smart contracts. Currently, there is no mechanism to guarantee all interests of the parties involved in non-bank transactions. To increase the processing capacity and integrate with the Blockchain system, we propose the Letter-of-credit Chain that defines the agreements between the parties in international trade. We also deploy the proof-of-concept of the Letter-of-credit Chain on the three EVM-supported platforms (i.e., under ERC20), namely, Ethereum, Binance Smart Chain, and Fantom. By evaluating the actual execution of Gas for each platform, we found that our proposed model had the cheapest fee when deployed on the Fantom platform. Finally, we share the deployment/implementation of these platforms’ proof-of-concept to encourage further future research.
Montassar Naghmouchi, Hella Kaffel Ben Ayed, Maryline Laurent
Nowadays, open standards for self-sovereign identity and access management enable portable solutions that are following the requirements of IoT systems. This paper proposes a blockchain-based identity and access management system for IoT -- specifically smart vehicles -- as an example of use-case, showing two interoperable blockchains, Ethereum and Hyperledger Indy, and a self-sovereign identity model.
Cryptocurrencies have become a trendy topic recently, primarily due to their disruptive potential and reports of unprecedented returns. In addition, academics increasingly acknowledge the predictive power of Social Media in many fields and, more specifically, for financial markets and economics. In this paper, we leverage the predictive power of Twitter and Reddit sentiment together with Google Trends indexes and volume to forecast the log returns of ten cryptocurrencies. Specifically, we consider $Bitcoin$, $Ethereum$, $Tether$, $Binance Coin$, $Litecoin$, $Enjin Coin$, $Horizen$, $Namecoin$, $Peercoin$, and $Feathercoin$. We evaluate the performance of LASSO-VAR using daily data from January 2018 to January 2022. In a 30 days recursive forecast, we can retrieve the correct direction of the actual series more than 50% of the time. We compare this result with the main benchmarks, and we see a 10% improvement in Mean Directional Accuracy (MDA). The use of sentiment and attention variables as predictors increase significantly the forecast accuracy in terms of MDA but not in terms of Root Mean Squared Errors. We perform a Granger causality test using a post-double LASSO selection for high-dimensional VARs. Results show no "causality" from Social Media sentiment to cryptocurrencies returns
Abstract The emergence of crypto currencies such as Bitcoin and Ethereum have shown the value in decentralized technologies. The idea of having 24/7 access to programmable money peaked the interest in the field, and as a by-product, came the realization that the same core technologies that enable programmable dog money, can enable highly-available DNS services, highly-available storage services, 24/7 asset exchanges, and peer-to-peer marketplaces to name a few. This paper explores the use of smart contracts in multi-cloud environments in order to facilitate business processes across multiple providers speaking different languages in terms of policies, best practices, APIs, and SLAs.
Unlike traditional currencies that rely on centralized such as banks or governments, cryptocurrencies today have become popular due to its decentralized transactions. Decentralization takes advantage of no requirement for intermediaries, thus reducing transaction fees and processing time. However, investing in cryptocurrencies incurs risks and uncertainties due to price volatility and rapid changes. The fact that prediction of asset prices is complex due to the influence of multiple factors on price movements. This paper studied the technical factor to analyze the short-term returns of Ethereum in the periods of 1-10 days. The historical data containing Ethereum closing price are collected from CoinGecko. The twenty-two indicators are chosen from Momentum, Volatility, and Sentiment factors as candidates to provide valuable insights in market trends. The values of these indicators are calculated based on past Ethereum closing prices and then used for XGBoost learning to discover patterns in previous trading. The model performance is evaluated using the multi-class AUC-ROC metric, which measures the accuracy of predicting three types of Ethereum returns: Downtrend, Sideway, and Uptrend. The experimental results reported that the models achieved the values of micro-average ROC curve ranging from 0.65 to 0.67. Moreover, the study emphasizes the importance of considering momentum indicators when making investment decisions in Ethereum.
Syed Muhammad Sajjad, Muhammad Rafiq Mufti, Muhammad Yousaf, Waqar Aslam · 9 authors
DDoS (distributed denial of service) attacks have drastically effected the functioning of Internet‐based services in recent years. Following the release of the Mirai botnet source code on GitHub, the scope of these exploitations has grown. The attackers have been able to construct and launch variations of the Mirai botnet thanks to the open‐sourcing of the Mirai code. These variants make the signature‐based detection of these attacks challenging. Moreover, DDoS attacks are typically detected and mitigated reactively, making DDoS mitigation solutions very expensive. This paper presents a proactive IoT botnet detection system that detects the anomalies in the behavior of the IoT device and mitigates the DDoS botnet exploitation at the source end, which makes our proposal a low‐cost solution. Further, this paper uses a collaborative trust relationship‐based threat intelligence‐sharing mechanism to prevent other IoT devices from being compromised by the detected botnet. The researchers have evaluated the collaborative threat intelligence sharing mechanism using Ethereum Virtual Machine and Hyperledger. The performance of our proposed system can detect 97% of the Mirai botnet attack activities. Furthermore, our collaborative threat intelligence sharing mechanism based on the Ethereum Virtual Machine showed more scalability.
Trusted online credential management solutions are needed for instant and practical verification. Most of the available frameworks targeting this field violate the privacy of end-users or lack sufficient solutions in terms of security and Quality-of-Service (QoS). In this paper, we propose a Privacy-aware Fog-enhanced Blockchain-based online credential management solution, namely PriFoB. Our proposed solution adopts a public permissioned Blockchain model with different reliable encryption schemes, standardized Zero-Knowledge-Proofs (ZKPs) and Digital Signatures (DSs) within a Fog–Blockchain integrated framework, which is also GDPR compliant. We deploy both the Proof-of-Authority (PoA) and the Signatures-of-Work (SoW) consensus algorithms for efficient and secure handling of Verifiable Credentials (VCs) and global accreditation of VC issuers, respectively. Furthermore, we propose a novel three-dimensional DAG-based model of the Distributed Ledger (3DDL), and provide a ready-to-deploy PriFoB implementation. We discuss insights regarding the utilization and the potential of PriFoB, and evaluate it in terms of security, privacy, latency, throughput and power utilization. We analyze its performance in different layers of a Fog-enabled cloud architecture with simulation and emulation, and we show that PriFoB outperforms several Blockchain-based solutions utilizing Ethereum, Hyperledger Fabric, Hyperledger Besu and Hyperledger Indy platforms.
The return series of cryptocurrencies, which are emerging digital assets, exhibit nonstationarity, nonlinearity, and volatility clustering compared to other traditional financial markets, making them exceptionally difficult to forecast. Therefore, accurate cryptocurrency price forecasting is important for both market participants and regulators. It has been demonstrated that improved data forecasting accuracy can be achieved through decomposition, but few researchers have performed information extraction on the residual series generated by data decomposition. Based on the construction of a "decomposition-optimization-integration" hybrid model framework, in this paper, we propose a multi-scale hybrid forecasting model that combines the residual components after primary decomposition for secondary decomposition and integration. This model uses the variational modal decomposition (VMD) method to decompose the original return series into a finite number of components and residual terms; then, the residual terms are decomposed and the features are extracted using the completed ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method. The components are predicted by an extreme learning machine optimized by the sparrow search algorithm, and the final predictions are summed to obtain the final results. Forecasts for the returns of Bitcoin and Ethereum, which are major cryptocurrency assets, are compared with other benchmark models constructed based on different ideas, and we find that the proposed quadratic decomposition VMD-Res.-CEEMDAN-SSA-ELM hybrid model demonstrates the optimal and most stable forecasting performance in both one-step and multi-step ahead prediction of the cryptocurrency return series.