Blockchain-based Cryptocurrencies Research Articles

The Regulation of Cryptocurrency in China

Abstract As a distributed ledger technology (DLT) application, cryptocurrency has impacted the current financial legal relationship, and its regulation is becoming increasingly important. Some international organizations and countries have ratified laws and regulations concerning cryptocurrency. However, the supervision and regulation of cryptocurrency in China are still encountered some problems, such as consumer protection, the opposition between the global asset flow and the supervision of a single sovereign state, and the difficulty in determining the subject of legal responsibility. To seek solutions to these problems in China, the primary task is to define the legal attribute of cryptocurrency, to balance blockchain innovation and financial risk. At the same time, the regulatory sandbox can be used to regulate blockchain-based cryptocurrency. Among others, the core regulatory measures are establishing the technical standard access system, financing audit registration system, and investor suitability management system of blockchain financial enterprises.

TMAS: A Transaction Misbehavior Analysis Scheme for Blockchain

The emergence of blockchain-based cryptocurrencies, such as Bitcoins, has presented a promising alternative for e-payment methods, owing to their unique features of decentralization and anonymity. The usage of these currencies has grown exponentially, particularly in anonymous e-payment and without any trusted third party. However, the decentralized and anonymous nature of these currencies has also resulted in misbehaviors, e.g., money laundering. Therefore, detecting transaction misbehaviors has garnered increasing attention. In this paper, we propose TMAS, a transaction misbehavior analysis scheme for blockchain-based cryptocurrencies. We propose various transaction analysis approaches, feature extraction algorithms, and detection models for misbehaviors, including money laundering. We have implemented a real experimental system to detect misbehaviors, including money laundering, in blockchain-based cryptocurrencies such as Bitcoins. The proposed system includes ten features in the transaction graph, two heuristic money laundering models, and an analysis method for account linkage, which identifies accounts that are distinct but controlled by an identical entity. To verify the effectiveness of our proposed indicators and models, we have analyzed a sample of 100M transactions and computed transaction features, leading to the identification of some suspicious accounts. Moreover, the proposed methods can be applied to other cryptocurrencies, no matter token-based such as Bitcoins or account-based such as Ethereum.

User acceptance of social network-backed cryptocurrency: a unified theory of acceptance and use of technology (UTAUT)-based analysis

Turbulent market conditions, well-publicized advantages, and potential individual, social, and environmental risks make blockchain-based cryptocurrencies a popular focus of the public and scientific communities. This paper contributes to the literature on the future of crypto markets by analyzing a promising cryptocurrency innovation from a customer-centric point of view; it explores the factors influencing user acceptance of a hypothetical social network-backed cryptocurrency in Central Europe. The research model adapts an internationally comparative framework and extends the well-established unified theory of acceptance and use of the technology model with the concept of perceived risk and trust. We explore user attitudes with a survey on a large Hungarian sample and analyze the database with consistent partial least square structural equation modeling methodology. The results show that users would be primarily influenced by the expected usefulness of the new technology assuming it is easy to use. Furthermore, our analysis also highlights that while social influence does not seem to sway user opinions, consumers are susceptible to technological risks, and trust is an important determinant of their openness toward innovations in financial services. We contribute to the cryptocurrency literature with a future-centric technological focus and provide new evidence from an under-researched geographic region. The results also have practical implications for business decision-makers and policymakers.

Visual Analysis of Money Laundering in Cryptocurrency Exchange

Blockchain-based cryptocurrencies, such as Bitcoin (BTC) and Ethereum (ETH), are newly emerging financial assets. Cryptocurrency exchanges are marketplaces for cryptocurrency circulation while becoming a new venue for money laundering. In this work, we cooperate with a cryptocurrency exchange to investigate new solutions for anti-money laundering in cryptocurrency exchanges. First, we learn the domain knowledge of cryptocurrency transactions and summarize data analytical requirements of transaction supervisors in their daily work of anti-money laundering. Then, we propose a visual analysis approach to support their daily work. The approach consists of a new algorithm that automatically detects suspicious money laundering accounts and a multiviewed user interface that visualizes the algorithm results and relevant transaction data. An abacus-inspired visualization is designed in the interface to depict transaction patterns contained in numerous cryptocurrency transactions, which can help supervisors find money laundering clues and deduce the trading tactic adopted by launderers. Finally, an algorithm performance experiment, a case study, and a field study are conducted with real-world data to demonstrate the effectiveness of our solution.

Decentralization Is Good or Not? Defending Consensus in Ethereum 2.0

Proof-of-Stake (PoS) protocols are widely accepted as a viable substitute for the Proof-of-Work-based consensus, which is why recent blockchain-based cryptocurrencies and applications, most notably Ethereum 2.0, are using some variant of PoS as the basis for the consensus protocol. However, the implementation of PoS protocols in Ethereum 2.0 are not without its share of problems and vulnerabilities, especially with respect to the malicious behavior of validator nodes. In this paper, we first review the basic tenets of PoS protocols. We then discuss some of the recently described attacks on the Ethereum 2.0 consensus, and we also show that some of the design rationales adopted in PoS implementation—the decentralization of the voting process in particular—have, in actuality, enabled attacks that can be launched at a very low cost to the attacker. We also propose simple remedies that can reduce or eliminate the impact of those attacks and can evaluate the performance of the Ethereum 2.0 consensus when these remedies are applied.

Some aspects of legal regulation of cryptocurrency circulation in Ukraine

The impact of modern information technology has led to the emergence of a new form of currency – cryptocurrency, based on blockchain technology. This study aims to analyze the existing legal framework and delve into potential ways of legal regulation of activities related to the circulation of cryptocurrencies, in particular bitcoin. To achieve this goal, the study used a comprehensive set of both general scientific and specialized cognitive methods, including the comparative legal method, the systemic and structural method, methods of generalization, analysis and synthesis.
 The study clarifies the essence of blockchain-based cryptocurrencies as an alternative to traditional fiat currencies based on the fundamental principle of decentralization. It is noteworthy that among the many cryptocurrencies, bitcoin stands out with a distinctive feature called “hardness,” which gives it the properties of “digital gold.” This quality makes bitcoin a powerful means of preserving value, like precious metals, strengthening its status in global finance.
 In addition, the study outlines the current state of legal regulation of relations related to the circulation of virtual assets. A thorough analysis of the existing legal framework and its effectiveness in addressing the unique challenges posed by decentralized currencies has also been conducted.
 The study pays considerable attention to the prospects for the development of legal regulation of cryptocurrencies, which will consider the dynamic nature of virtual assets.
 To summarize, this study contributes to the understanding of the economic intricacies inherent in blockchain-based cryptocurrencies, with a special emphasis on the “hardness” of bitcoin as a distinguishing factor. In addition, the study sheds light on the current state of legal regulation of virtual assets, paving the way for insightful predictions of the future regulatory landscape. This work not only adds to the academic discourse around cryptocurrencies, but also serves as a valuable resource for policymakers, practitioners and academics grappling with the challenges and opportunities presented by this new financial paradigm.

A stochastic target problem for branching diffusion processes

We consider an optimal stochastic target problem for branching diffusion processes. This problem consists in finding the minimal condition for which a control allows the underlying branching process to reach a target set at a finite terminal time for each of its branches. This problem is motivated by an example from fintech where we look for the super-replication price of options on blockchain-based cryptocurrencies. We first state a dynamic programming principle for the value function of the stochastic target problem. Next, we show that the value function can be simplified into a novel function with the use of a finite-dimensional argument through a concept known as the branching property. Under wide conditions, this last function is shown to be the unique viscosity solution to an HJB variational inequality.

A centrality analysis of the Lightning Network

Blockchain technology has a huge impact on our digital society by enabling a more decentralized economy and policy making. This decentralization is also pivotal in payment Payment channel networks (PCNs), including the Lightning Network, have emerged as a promising solution to the scalability challenges that many blockchain-based cryptocurrencies, like Bitcoin, grapple with. These PCNs, while innovative, also inherit the rigorous dependability demands of the blockchain. A pivotal aspect of this dependability is the need for a high degree of decentralization, essential for mitigating liquidity bottlenecks and on-path attacks.Driven by this imperative, our research embarks on an empirical centrality analysis of the Lightning Network, with a keen focus on the betweenness centrality distribution of its routing system. Utilizing an extensive dataset, sourced from several millions of broadcasted messages via the gossip protocol, we introduce the TimeMachine tool, an innovative method that allows for a temporal exploration of the network’s evolution.Our findings reveal that while the Lightning Network exhibits a commendable level of decentralization, there is a discernible skew: a limited set of nodes command a significant portion of the transactions. Alarmingly, over the past two years, the network’s centrality has surged, with the inequality, as gauged by the Gini index, rising by over 15 uptick of approximately 5 in. This research not only uncovers critical insights into the Lightning Network’s structural dynamics but also raises the question about strategies and policies that ensure its sustained decentralization in the face of evolving challenges such as security vulnerabilities, potential monopolistic tendencies, liquidity bottlenecks, the risk of transaction censorship and many more.

Introducing technological disruption: how breaking media attention on corporate events impacts online sentiment

ABSTRACT One modern strategy to anticipate consumer reaction to new products and services involves looking towards social media sites to explore consumer opinions. A rich body of literature on social media marketing suggests that an effective way to leverage social media platforms is the empirical analysis of electronic word-of-mouth (eWOM), particularly through sentiment analysis (SA). We propose a novel method for innovators to leverage social media by exploring how breaking media attention on notable corporate events impacts the general public sentiment surrounding a pre-introduced, potentially disruptive innovation (PPDI). Twitter conversations surrounding Facebook’s pre-introduced payment system called Libra, a permissioned blockchain-based cryptocurrency, were analysed as a case study. The analysis suggests that breaking media attention leads to a significant change in sentiment polarity. An event with a preannouncement leads to an emotional momentum effect whereby sentiment polarity accumulates across an anticipation period. Implications for how managers may leverage these insights are discussed.

Phishing scams detection via temporal graph attention network in Ethereum

Recently, phishing scams have become one of the most serious types of crime involved in Ethereum, the second-largest blockchain-based cryptocurrency platform. The existing phishing scams detection techniques for Ethereum mostly use traditional machine learning or network representation learning to mine the key information from the transaction network and identify phishing addresses. However, these methods typically crop the temporal transaction graph into snapshot sequences or construct temporal random wanderings to model the dynamic evolution of the topology of the transaction graph. In this paper, we propose PDTGA, a method that applies graph representation learning based on temporal graphs attention to improve the effectiveness of phishing scams detection in Ethereum. Specifically, we learn the functional representation of time directly and model the time signal through the interactions between the time encoding function and node features, edge features, and the topology of the graph. We collected a real-world Ethereum phishing scam dataset, containing over 250,000 transaction records between more than 100,000 account addresses, and divided them into three datasets of different sizes. Through data analysis, we first summarized the periodic pattern of Ethereum phishing scam activities. Then we constructed 14 kinds of account node features and 3 kinds of transaction edge features. Experimental evaluations based on the above three datasets demonstrate that PDTGA with 94.78% AUC score and 88.76% recall score outperforms the state-of-the-art methods.

StableFees: A Predictable Fee Market for Cryptocurrencies

Blockchain-based cryptocurrencies must solve the problem of assigning priorities to competing transactions. The most widely used mechanism involves each transaction offering a fee to be paid once the transaction is processed, but this discriminatory price mechanism fails to yield stable equilibria with predictable prices. We propose an alternate fee setting mechanism, StableFees, that is based on uniform price auctions. We prove that our proposed protocol is free from manipulation by users and miners as the number of users and miners increases and show empirically that gains from manipulation are small in practice. We show that StableFees reduces the fees paid by users and reduces the variance of fee income to miners. Data from December 2017 show that, if implemented, StableFees could have saved Bitcoin users $272,528,000 USD in transaction fees while reducing the variance of miner’s fee income, on average, by a factor of 7.4. We argue that our fee protocol also has important social welfare and environmental benefits. This paper was accepted by Agostino Capponi, Special Section of Management Science: Blockchains and Crypto Economics. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4735 .

НЕСТАБІЛЬНІ ФІНАНСОВО-ЕКОНОМІЧНІ ЧИННИКИ У СВІТІ І ЇХ ВПЛИВ НА РОЗВИТОК БЛОКЧЕЙН ТЕХНОЛОГІЙ

The article explores the impact of unstable financial and economic factors on the development of blockchain technologies. In recent years, blockchain has emerged as a disruptive innovation with the potential to transform various sectors, including finance, supply chain management, and healthcare. This article sheds light on the interplay between the volatile financial and economic landscape and the evolution of blockchain technologies. The author emphasizes that unstable financial and economic conditions have significantly influenced the trajectory of blockchain development. The article argues that during periods of economic uncertainty, blockchain technology gains traction as a trusted and transparent alternative to traditional financial systems. Blockchain's decentralized nature, cryptographic security, and immutable recordkeeping capabilities make it an attractive solution for addressing issues such as fraud, corruption, and lack of transparency. Furthermore, the article delves into specific instances where blockchain adoption has been fueled by unstable financial and economic factors. For instance, in countries facing hyperinflation or economic crises, blockchain-based cryptocurrencies have provided individuals with a means to protect their wealth and conduct secure transactions. Similarly, in supply chain management, blockchain's ability to enhance transparency and traceability has gained momentum in the wake of widespread disruptions caused by global events such as the COVID-19 pandemic. The article also explores the potential challenges and limitations that arise from the relationship between unstable financial and economic factors and blockchain technologies. It acknowledges that while blockchain holds promise, regulatory uncertainties, scalability issues, and interoperability concerns can hinder its widespread adoption. In conclusion, this article highlights the intricate relationship between unstable financial and economic factors and the development of blockchain technologies. It provides valuable insights into the growing relevance of blockchain in addressing the shortcomings of traditional financial systems during times of economic instability. However, it also underscores the need for continued research, collaboration, and regulatory clarity to harness the full potential of blockchain technology in a rapidly evolving financial landscape. Overall, this article serves as a thoughtprovoking resource for researchers, policymakers, and industry professionals seeking to understand the dynamic interplay between unstable financial and economic factors and the development of blockchain technologies.

Exploring Barriers and Resistance in the Adoption of Cryptocurrency among Micro, Small, and Medium Enterprises MSMEs in Lusaka

The aim of this article is to Explore Barriers and Resistance in the Adoption of Cryptocurrency among Micro, Small, and Medium Enterprises MSMEs in Zambia’s capital city, Lusaka. When considering the benefits of innovation, one of the trickiest questions to answer is how quickly people will adopt new technologies. This article delves into what motivates and what holds back potential business entities in the MSMEs sector from making a transition to blockchain-based cryptocurrencies like bitcoin. Our findings are narrowly focused on these impediments to adoption, which we identify as Lack of regulatory support, risk of revealing personal data system complexity, lack of regulatory authority, trust deficit, and value speculation.

Cryptocurrency Acceptance Model to Analyze Consumers’ Usage Intention: Evidence From Pakistan

Blockchain and cryptocurrencies are transformative fintech breakthroughs that infiltrate the financial sector; however, they have many drawbacks and limits. Consumers have shown an insufficient level of acceptance of these innovations. This paper elucidates the main reasons for the effective growth of a cryptocurrency from user behavior. The objective is to determine what factors influence consumers’ intentions to engage in blockchain-based cryptocurrency dealings. Considering the complexity of emerging technologies, this paper applied an integration model which assumes various external elements such as financial literacy, performance expectancy, facilitating conditions, effort expectancy, awareness, trust, design, and social influence. Smart PLS3 has been used. The most critical determinant of a cryptocurrency’s growth is “design.” On the other hand, “design” affects effort expectancy positively, and social influence affects trust. Awareness, performance expectancy, financial literacy, and effort expectancy significantly affect intentions to use cryptocurrency. It’s worth mentioning that it is the first research to examine Pakistani customers’ perceptions of Bitcoin and their ability to partake. As a result, it is intended to serve as a base for potential research in this area.

Preferential Delegated Proof of Stake (PDPoS)—Modified DPoS with Two Layers towards Scalability and Higher TPS

Security and a decentralized system are identical unique features of Blockchain. In recent times, blockchain-based cryptocurrency has become mainstream, but the growth and value of transactions and application services remain volatile. Among all these applications, finding a fast consensus in a large-scale blockchain network frequently requires extreme energy for huge computations and storing the complete blockchain for verification. These problems prevent further commercialization. Here, we present a solution to this problem. In this paper, we introduce a revised blockchain consensus algorithm, PDPoS, to address the scalability and transaction efficiency limitations. The symmetry in between Proof of Stake (PoS) and Delegated Proof of Stake (DPoS) is PoS. However, their ways of working are dissimilar. Here, we review the existing consensus algorithms, such as Proof of work (PoW), PoS and DPoS, as they are directly relating to our proposed work: PDPoS. We highligh Delegated Proof of Stake (DPoS)–based crypto-currencies, as they have much higher transactions per second (TPS) than PoW-based currencies. Then, we describe our proposed works and the working steps of the proposed PDPoS. Simulation results of the proposed PDPoS with two layers result in improved efficiency. We used TPS as the evolution criteria for showing that the proposed PDPoS is more efficient than DPoS. This makes the proposed work more relevant to the large-scale blockchain network as it is more efficient and requires less energy consumption.

Multi-Party Payment Channel Network Based on Smart Contract

Blockchain-based cryptocurrencies are severely limited in transaction throughput and latency. A promising solution to this issue is a payment channel, which allows trust-free payments between two peers without exhausting the resources of the blockchain. A linked payment channel network (PCN) enables payments between two peers through a series of intermediate nodes that forward and charge for the payments. However, most of existing proposals only use the shortest path as the path of the transaction, which causes the frequently reused channels to be exhausted quickly. In addition, most of existing PCNs are almost only designed for payments between two parties, which leads to limited application scenarios. When multiple payments use the same intermediate channel, the two-party PCNs cannot achieve simultaneous payments. In this paper, we propose a multi-party payment channel (MPC) network, a payment channel proposal that supports multiple payments using the same intermediate channel simultaneously, thereby greatly expanding the application scenarios of payment channels. In addition, our channel selection and transaction conversion strategies can also increase the success rate of transactions. We implement MPC network in the simulated blockchain network and lightning network based on Truffle, and a large number of experiments verify the effectiveness of our solution.

Blockchain-based Cryptocurrency Price Prediction with Chaos Theory, Onchain Analysis, Sentiment Analysis and Fundamental-Technical Analysis

Crypto assets succeeded in making their name known to large masses with Bitcoin, which emerged as a result of the creation of the first genesis block in 2008. Until 2010, the aforementioned recognition showed itself mostly in areas such as games, but over time it managed to enter the portfolios of individual investors. Especially as of end of 2017, the rapid increases in monetary value quickly attracted the attention of corporate companies and then the (Central Banks). These assets have created different alternatives (also know as altcoins) by working and have managed to become one of the important financial instruments today. This study has examined in detail the techniques (Chaos theory, Onchain analysis and Sentiment analysis) developed on the price predictions of crypto assets, which are very important in terms of the number and quality of investors. In the study, findings were obtained that new techniques such as onchain and sentiment are more prominent in estimating crypto asset prices compared to traditional asset price estimation methods of crypto assets and that these techniques can make consistent estimations.

Ultra-Short-Term Continuous Time Series Prediction of Blockchain-Based Cryptocurrency Using LSTM in the Big Data Era

This study uses the API of Upbit, one of Korea’s cryptocurrency exchanges, to predict continuous time series for a limited period and cryptocurrencies using LSTM, a machine learning technique. The trading (buying and selling) point algorithm presented in this study was used to conduct experimental research on efficient profit creation for cryptocurrency investment. Several related studies have shown the results of time series prediction for long-term forecasts, such as a week or several months. Still, they have not attempted to make an ultra-short-term prediction in units of one minute. This paper attempts such a 1 min prediction. This is an experiment to create efficient profits by setting efficient trading (buying and selling) points using machine learning techniques and repeating these operations by an algorithm. Applying it to cryptocurrency shows the possibility of time series prediction.

Utilising the Computational Power of Blockchain Proof-ofWork in Computer-Aided Drug Design

Proof-of-Work (PoW) algorithm is a popular blockchain algorithm employed in many blockchain applications such as Bitcoin. Cryptographic hashing is the foundation of the PoW algorithm and blockchain technology in general. Unfortunately, the use of hashing in PoW has led to huge computational requirements. Researchers and industrialists are aware of the immense energy consumed by the PoW algorithm in blockchain-based cryptocurrencies. For instance, Bitcoin currently consumes above 110 TWh of electricity annually. This vast amount of energy is used to calculate non-valuable cryptographic hashes, which eventually becomes a waste when the right nonce value is found. Bioinformatic researchers depend on molecular docking simulation, which is effective but requires heavy computing resources. This paper proposes a solution to the above issues by taking advantage of the wasted computing power harnessed by the PoW algorithm and subsequently channelling the computing resources towards molecular docking simulations for drug discovery. With the new proposed framework, molecular docking is introduced into PoW algorithm where energy from a PoW system like bitcoin can be used to help researchers crunch bioinformatics data for computer aided drug discovery. A target protein receptor and ligands are introduced at the beginning of a new mining period, rather than computing random computer bits to discover a nonce, mining nodes will perform docking simulations with the receptor and ligands to generate docked conformations for drug creation research. This research does not seek to reduce the computational energy of the PoW rather utilise this energy for valuable drug creation process. Keywords— Blockchain, Bitcoin, PoW, Ligand, Molecular docking, RMSD, Score

Coin Transfer Unlinkability Under the Counterparty Adversary Model

Unlinkability is a crucial property of cryptocurrencies that protects users from deanonymization attacks. However, currently, even anonymous cryptocurrencies do not necessarily attain unlinkability under specific conditions. For example, Mimblewimble, which is considered to attain coin unlinkability using its transaction kernel offset technique, is vulnerable under the assumption that privacy adversaries can send their coins to or receive coins from the challengers. This paper first illustrates the privacy issue in Mimblewimble that could allow two colluded adversaries to merge a person’s two independent chunks of personally identifiable information (PII) into a single PII. To analyze the privacy issue, we formulate unlinkability between two sets of objects and a privacy adversary model in cryptocurrencies called the counterparty adversary model. On these theoretical bases, we define an abstract model of blockchain-based cryptocurrency transaction protocols called the coin transfer system, and unlinkability over it called coin transfer unlinkability (CT-unlinkability). Furthermore, we introduce zero-knowledgeness for the coin transfer systems to propose a method to easily prove the CT-unlinkability of cryptocurrency transaction protocols. Finally, we prove that Zerocash is CT-unlinkable by using our proving method to demonstrate its effectiveness.