Abstract It has been claimed that technology would replace the legal profession with artificial intelligence and codification of documents replacing the twenty‐first century lawyer. With this premise in mind, this paper discusses smart legal contract formation in the context of Australian contract law, the perceived replacement of lawyers through blockchain technology and how the COVID‐19 pandemic has set the trajectory for smart legal contract convention. We consider whether the legal profession can ever truly be replaced by technological advances and whether COVID‐19 has pivoted the way the legal profession performs business transactions towards modernisation. Although prior literature has considered how the legal profession may benefit from increased technology use, the expected timeframe for occurrence was dependant on a strong reluctance by the profession to change the status quo. Analysis of the impact of COVID‐19 on the legal profession including the execution of legal documents, provides insight into areas for improvement going forward and whether a regulatory overhaul is required. This research shows that, although there are a number of advantages to the implementation of smart legal contracts using blockchain technology, there still remains numerous implementation and regulatory concerns that need resolution if smart legal contracts are to be widely used.
Cryptocurrencies have become an attractive asset class for all types of investors. A relevant question is whether their inclusion in portfolios improves their risk-return output. In this chapter, we conduct an empirical study of the effect of the inclusion of Bitcoin and Ethereum in the portfolio of a European investor. Additionally, we analyze the results of previous studies on this question under other assumptions. The empirical data are overwhelming regarding the attractiveness of Bitcoin and by extension other cryptocurrencies as an asset class. The important question is whether this appeal is temporary and will eventually disappear so investors do not have to worry about this new asset class. In the chapter we discuss this issue.
This paper proposes a novel blockchain-based advanced banking system that leverages the distributed ledger technology of Ethereum to create a secure, transparent, and efficient financial system. The system utilizes a permission blockchain network, where participants are pre-authorized to join and contribute to the network. This ensures the security and integrity of the system, while still allowing for a wider range of participants than a fully public blockchain network. The system works by first having a user initiate a transaction request. The system then verifies the user's identity and ensures the authenticity of the request. The transaction is entered into the blockchain ledger after it has been validated. This ensures that the transaction is immutable and transparent, as all participants in the network can view the transaction details. The system also includes a fraud detection mechanism that can detect any changes made to the transaction after it has been recorded on the blockchain. This helps to ensure the security of the system and protect users from fraudulent activity. The proposed system has the potential to revolutionize the banking industry by providing a more secure, transparent, and efficient way to conduct financial transactions. Keywords: blockchain, online banking, ethereum, ganache, hash, smart contract, blocks
Organizations today are shifting toward collaborative forms of value creation and rely on digital technologies to operate interorganizational processes. This has led blockchain technology to gain considerable momentum, given its ability to foster collaboration among multiple actors. Nevertheless, despite its benefits, building a blockchain-based platform requires integrating heterogeneous needs and adapting to decentralized governance structures. This research investigates the successful deployment of a blockchain-based solution for interbank collaboration. Our empirical analysis focuses on the Spunta Banca DLT Project, initiated in 2017 to automate the interbank reconciliation processes in Italy, through the deployment of a permissioned blockchain-based solution. A qualitative analysis of interview data collected from project participants was conducted to gain insights on the process to build a blockchain-based platform for interbank collaboration. The findings of our exploratory case study reveal that successful deployment hinges on a sequential legitimacy-building process, encompassing pragmatic, normative, and cognitive legitimacy.
In the post-COVID-19 era, academic papers on changing financial investment habits are proliferating rapidly as the pandemic has disrupted economic and financial markets, altered investment decisions, and brought new risks and challenges. In addition to traditional market instruments such as gold, oil, and other commodities, cryptocurrencies have attracted new attention due to their dynamic and decentralized nature in these extraordinary times, which must be constantly analyzed from different angles. This paper aims to analyze the evolving academic interest in the adoption of cryptocurrencies for investment decisions, focusing on research papers published in the Scopus database between 2020 and 2023 through bibliometric analysis. The Scopus database provides high-quality publications that have been peer-reviewed and rigorously scrutinized, and the chosen time period corresponds exactly to the period that was sufficient to provide a significant amount of research. The choice of bibliometric research methodology supported our research question and significantly improved our understanding of the relationship between the rise in financial market usage related to COVID-19. The specific focus of this research shows a significant correlation between COVID-19 and cryptocurrencies as an investment option, as evidenced by the increasing number of academic papers and collaboration between numerous countries and institutions. The analysis of the bibliometric research results underlines the increasing importance of cryptocurrencies as alternative investment opportunities in the financial markets. A remarkable interest in this area can be observed globally, with leading countries such as China, India, the USA, the UK, and Malaysia driving research efforts. Through the use of bibliometric analysis, this study encourages cross-border collaboration and highlights the academic recognition of cryptocurrencies as viable investment opportunities in the international financial landscape. Investors, researchers, and policymakers are interested in the growing recognition of cryptocurrencies as a viable investment opportunity, which is reflected in increasing research collaborations and investment opportunities. These trends highlight the evolving landscape of financial markets and regulatory considerations.
Cryptocurrencies have revolutionized the financial landscape by providing decentralized and anonymous payment systems, making them an intriguing subject for investors and researchers. This article delves into applying machine learning techniques for predicting cryptocurrency prices, mainly focusing on Bitcoin, Ethereum, and Binance Coin. Employing a range of machine learning models, including XGBoost, Linear Regression, and Gaussian Processes, the study aims to evaluate their predictive performance comprehensively. The results are promising; our models outperform existing studies, achieving impressively low RMSE values of 0.0040 for Bitcoin, 0.028 for Ethereum, and 0.027 for Binance Coin. These findings contribute valuable insights into the volatility and dynamics of cryptocurrency prices and underscore the potential of machine learning in shaping financial decision-making. Future directions include integrating advanced deep learning models, additional data sources, and ensemble methods to enhance prediction accuracy and robustness.
Daniel Bennet, Lily Maria, Yulia Putri Ayu Sanjaya, Achani Rahmania Az Zahra
Blockchain technology emerges as a transformative innovation reshaping traditional transactional processes, eliminating intermediaries, enhancing security, and improving trust through its decentralized and transparent ledger system. However, challenges such as scalability and regulatory concerns hinder widespread adoption. Concrete examples and statistics from research enhance clarity regarding Blockchain's impacts, elaborating on how these challenges directly affect the adoption of Blockchain Technology in digital transactions. By analyzing case studies and current trends, this research underscores the efficiency and reliability of Blockchain implementation compared to traditional methods, advocating for widespread adoption to foster transparency, efficiency, and trust across diverse sectors. It emphasizes the necessity for organizations to adapt to stay competitive in the increasingly complex digital landscape, suggesting that a better understanding of Blockchain's impacts and challenges will aid organizations in taking strategic steps towards its long-term adoption.
Krzysztof Gogol, Yaron Velner, Benjamin Kraner, Claudio J. Tessone
Liquid staking and restaking represent recent innovations in Decentralized Finance (DeFi) that garnered user interest and capital. Liquid Staking Tokens (LSTs), tokenized representations of staked tokens on Proof-of-Stake (PoS) blockchains, are the leading staking method. LSTs offer users the ability to earn staking rewards while maintaining liquidity, enabling seamless integration into DeFi protocols and free tradeability. Restaking builds upon this concept by allowing staked tokens, LSTs or native Bitcoin tokens to secure additional protocols and PoS chains for supplementary rewards. Liquid Restaking Tokens (LRTs) unlock liquidity of restaked assets. This Systematization of Knowledge (SoK) establishes a comprehensive framework for the technical and economic models of liquid staking protocols. Using this framework, we systematically compare protocols mechanics, including node operator selection, staking reward distribution, and slashing. Our empirical analysis of token performance reveals that protocol design and market dynamics impact token market value. We further present the recent developments in restaking and discuss associated risks and security implications. Lastly, we review the emerging literature on liquid staking and restaking.
Malak Sulaiman Alrumaih, Mohammad Mahdi Hassan, Muhammad Martuza, Suliman Abdallah Alsuhibany
Blockchain is an emerging technology based on the digital ledger in the distributed system. The decentralized trust is one of its prominent features that ensures better transparency. Blockchain-based systems also enhance data integrity, confidentiality, and anonymity by eliminating third-party involvement in completing the transactions. Many SLRs have been published related to blockchain recently, but no comprehensive and systematic study on blockchain platforms has been conducted. So, there is a need for an organized and systematic review of blockchain platforms. This paper has reported a systematic literature review on existing blockchain platforms. We have formulated two research questions to determine the major frameworks used to implement blockchain-based systems and how they differ in implementation and operation. We have identified eighty-five blockchain platforms. To provide comprehensive insights on blockchain platforms, we identified related technologies and provided a map for further research development on blockchain technology.
Blockchain is an emerging technology that has been widely used in various sectors, including the financial sector. This study analyzes research trends on blockchain technology for regional government financial management in Indonesia using bibliometric techniques. Database searches identified 141 documents on blockchain in Indonesia and 34 documents specifically on financial blockchain from 2016-mid 2023. This research utilizes bibliometric methods complemented by a research question to uncover significant findings or trends in the literature related to the potential implementation of blockchain in regional government finance in Indonesia. Research on blockchain in the Indonesian financial sector has already been widely conducted, accounting for 24% of the research related to blockchain in Indonesia. This indicates that the financial sector has become one of the primaries focuses of blockchainrelated research in Indonesia. Bibliometric analysis of the literature suggests that blockchain has potential to enhance transparency, efficiency, and accountability in regional government finance through features like smart contracts, immutable records, and decentralized networks. A private blockchain structure can provide security and control. This study informs blockchain implementation plans for regional finance in Indonesia.
Cryptocurrency is a growing fintech trend frequently encountered in various moderneconomic activities. Therefore, this research aimed to provide knowledge and understanding of cryptocurrency, particularly from the perspective of Islamic finance and economics using secondary data obtained from literature. As a digital financial transaction system, cryptocurrency fundamentally uses relatively new technology. However, the legal nature still needs further examination without constituting a form of violation. In Indonesia, the government has yet to adopt a definitive stance on the presence of cryptocurrency, thereby permitting its usage. The results showed that cryptocurrency investment includes substantially greater risk compared to others due to the inherent challenge of predicting the value. From the perspective of Islamic finance and economics, the transactions are considered to lack clarity in terms of quality and quantity, containing elements of uncertainty (gharar). Moreover, the concept of Bitcoin as a transaction tool is forbidden (haram) by the Indonesian Ulama Council since the project contains uncertainty and does not comply with the existing regulations. The implications of the research emphasize the necessity ofavoiding dubious activities, such as cryptocurrency, as well as transactions leading to higher harm (madharat) compared to benefits, particularly from the perspective of Islamic finance and economics.
Purpose: This research explains and reviews two innovative solutions based on blockchain that were used for Islamic social finance projects by two separate companies namely Finterra and Blossom Finance. Policy implications are suggested for the future use of blockchain in innovative financial products for the Islamic financial industry. Design/methodology/approach: This is qualitative research conducted through library research and semi-structured interviews with experts and founders of Finterra and Blossom Finance. Data obtained from published literature and the interviews were accordingly examined and interpreted through content analysis and the results are presented in this research. Findings: There is rising interest in Islamic social finance for economic revival post COVID-19 pandemic. Innovation through technology seems to be the future of Islamic social finance. Innovation through blockchain technology would see a renaissance in Islamic social finance, hence the need for relevant stakeholders to understand the technology. However, there is a regulatory gap in terms of proper legal framework to support blockchain related innovations in Islamic social finance and a policy gap to manage Shariah and legal risks involved in Islamic social finance transactions. Originality: This research is original because it explains unique case studies from the source of innovation itself, and analyses the hurdles that were present and offers recommendations for future use of innovative technology in the Islamic financial sector. Keywords: Blockchain technology, Blossom Finance, Finterra, Islamic Social Finance, Regulatory and Policy Issues
Ethereum smart contracts are highly powerful, immutable, and able to retain massive amounts of tokens. However, smart contracts keep attracting attackers to benefit from smart contract flaws and Ethereum unexpected behavior. Thus, methodologies and tools have been proposed to help implement secure smart contracts and to evaluate the security of smart contracts already deployed. Most related surveys focus on tools without discussing the logic behind them. in addition, they assess the tools based on papers rather than testing the tools and collecting community feedback. Other surveys lack guidelines on how to use tools specific to smart contract functionalities. This paper presents a literature review combined with an experimental report that aims to assist developers in developing secure smarts, with a novel emphasis on the challenges and vulnerabilities introduced by NFT fractionalization by addressing the unique risks of dividing NFT ownership into tradeable units called fractions. It provides a list of frequent vulnerabilities and corresponding mitigation solutions. In addition, it evaluates the community most widely used tools by executing and testing them on sample smart contracts. Finally, a comprehensive guide on implementing secure smart contracts is presented.
With the growing concern of AI safety, there is a need to trust the computations done by machine learning (ML) models. Blockchain technology, known for recording data and running computations transparently and in a tamper-proof manner, can offer this trust. One significant challenge in deploying ML Classifiers on-chain is that while ML models are typically written in Python using an ML library such as Pytorch, smart contracts deployed on EVM-compatible blockchains are written in Solidity. We introduce Machine Learning to Smart Contract (ML2SC), a PyTorch to Solidity translator that can automatically translate multi-layer perceptron (MLP) models written in Pytorch to Solidity smart contract versions. ML2SC uses a fixed-point math library to approximate floating-point computation. After deploying the generated smart contract, we can train our models off-chain using PyTorch and then further transfer the acquired weights and biases to the smart contract using a function call. Finally, the model inference can also be done with a function call providing the input. We mathematically model the gas costs associated with deploying, updating model parameters, and running inference on these models on-chain, showing that the gas costs increase linearly in various parameters associated with an MLP. We present empirical results matching our modeling. We also evaluate the classification accuracy showing that the outputs obtained by our transparent on-chain implementation are identical to the original off-chain implementation with Pytorch.
In recent years, blockchain technology has drawn a lot of attention, especially in the field of decentralised finance (De-Fi). However, scalability problems have come to light as a significant obstacle to the broad use of blockchain-based applications. To solve the issue of scalability, this paper has created a decentralised finance application with three main components: the addition of more liquidity to the swapping application, the implementation of a Polygon Proof of Stake bridge to enable efficient asset transfers, and the ability to transfer tokens between accounts seamlessly regardless of network agnosticism. The first feature, network agnostic capabilities for interoperability, facilitates token transfers between blockchain networks, allowing users to access and transact across them with ease The second component, the Polygon Proof-of-Stake bridge, makes asset transfers more efficient by taking advantage of the Polygon network's scalability advantages, which drastically lower transaction costs and processing times. Finally, adding more liquidity to the swapping programme makes it more scalable by guaranteeing that there is enough money for transactions, which prevents delays and bottlenecks. The scalability issue with blockchain technology is efficiently resolved by adding these three characteristics to the decentralised finance application, creating new opportunities for the mass acceptance and utilisation of blockchain-based financial services.
This paper studies the adoption of blockchain technology under the scope of the Unified Theory of Acceptance and Use of Technology (UTAUT). Previous results on Management Information Systems (MIS) research are divergent about the significance of UTAUT variables in explaining the adoption behaviour of blockchain technology. The paper focuses on this specific concern and tries to contribute to existing studies by testing the model in a specific context (Tunisia) and by considering the individual variable “trust in technology” as a mediating one. For this aim, a structural equation approach is adopted among 95 Tunisian professional respondents operating in technology-based sectors. The findings stipulate the importance of facilitating conditions and performance expectancy as drivers of the adoption intention. Additionally, the study reveals that trust in technology is significant in its mediating role in influencing the intention of adoption with the facilitating conditions and the social influence constructs. Moreover, the paper uncovers a direct relationship with the same variable. These findings provide valuable insights for both researchers and practitioners in understanding the factors that influence blockchain technology adoption in the Tunisian context and stress the indirect role of trust in technology with which decision-makers should be concerned.
Abdullah M. Al‐Enizi, Shailendra Mishra, Abdullah Baihan
Blockchain and artificial intelligence are innovative technologies that can securely process and share data across unreliable networks. Due to data leakage from user information, it is critical to keep the data confidential and completely protected because criminals are looking for this information to attack the system or steal information in the banking sector. To address this issue, this paper suggests an Integrated Blockchain and Artificial intelligence (IBAI) Framework for secure financial transactions. A blockchain can store every customer's data in one place, while AI-driven algorithms can speedily examine that data and make an unbiased decision. The rising blockchain technology provides a decentralized architecture that enables the secure sharing of data and resources to the different networks and is promoted for removing centralized control and resolving the problems of AI. When suspicious behaviour happens, alerts can be triggered to avert theft. Furthermore, registration protocols based on AI are utilized to keep this data in comprehensive security. The numerical results show that the suggested IBAI model enhances the suspicious behaviour detection ratio and increases accuracy up to 98% compared to other models.
Yi‐Shun Wang, Nam Tien Duong, Chia-Hsuan Ying, Yun-Chi Chang
By integrating the Self-Determination Theory and individual difference perspectives, this study examines how individual differences (i.e.locus of control, self-efficacy, and risk preference) influence behavioral intention to invest cryptocurrency through the mediation of the intrinsic and extrinsic motivations.Data collected from a sample of 305 valid responses are used to examine the research model and test the hypotheses with the employment of partial least squares structural equation modeling.The findings reveal that locus of control and self-efficacy significantly influence both intrinsic and extrinsic motivations to invest in cryptocurrencies.However, risk preference significantly impacts only extrinsic motivation.Both intrinsic and extrinsic motivations markedly influence the behavioral intention to invest in cryptocurrencies.The findings of this study provide several important theoretical and practical implications for understanding online cryptocurrency investment behaviors.
Can Zhao, Yibing Wang, Dejun Wang, Guangyan Sun · 5 authors
The analysis on conformance between legal contracts and smart contracts is necessary and precondition for constructing the secure blockchain. Currently, the analysis method is the language-dependent single qualitative analysis. There does not exist quantitative metrics and quantitative analysis methods. Hence, the quantitative metric and language-independent quantitative analysis method are proposed to analyze the conformance between legal contract and smart contract. First, the definitions and metrics of partial conformance and complete conformance are proposed, and then rewrite logic and language-independent symbol execution are used to construct a language-independent quantitative method; then, the executable formal semantic for legal contract description language Business Process Model and Notation2.0 (BPMN2.0) is presented. Finally, the conformance of the five main methods for mapping BPMN2.0 legal contracts to Solidity smart contracts is analyzed. The results show that three methods have partial conformance, one method has complete conformance, and method has neither complete conformance nor partial conformance.
Michael Paul Kramer, Jochen Heussner, Jon Henrich Hanf
Abstract A recent publication reports that the number of active Non-Fungible Tokens (NFTs) in self-custodial wallets has grown exponentially in the past years across several industries. This study analyzed 65 token-based use cases in the wine sector. It was found that most current applications revolve around the downstream part of the supply chain. The research has also demonstrated that the various solutions involving fungible tokens and NFTs can be classified into three categories. Consequently, a taxonomy has been introduced. Furthermore, it was identified that digital tokens can solve current challenges in the wine industry related to provenance, proof of origin, authenticity, and fraud prevention. At the same time, the utilization of tokens enables an extended consumer interaction with the product. Managers potentially considering connecting their physical products and services with digital tokens can obtain insights towards their use in the web3 economy.
The project aims to develop a decentralized file-sharing platform that harnesses the power of blockchain technology, Ethereum smart contracts, and InterPlanetary File System (IPFS) to create a secure, censorship-resistant, and user-centric file-sharing ecosystem, eliminating reliance on centralized intermediaries, enhancing data privacy, and reducing the risk of censorship or data loss for a future of decentralized and secure data management.
Blockchain technology has emerged as a disruptive force in the realm of global finance, offering the promise of enhanced efficiency, transparency, and security. This paper provides a comprehensive examination of the applications, opportunities, and challenges presented by blockchain in the context of international financial management. The decentralized ledger system of blockchain holds significant potential for automating processes and improving credit identification in Islamic finance, yet it faces obstacles such as regulatory uncertainty and interoperability issues in traditional banking systems. Despite these challenges, blockchain has the capacity to streamline cross-border payments, digitize trade finance operations, and revolutionize cross-border remittances. However, scalability concerns and regulatory ambiguities pose significant hurdles to widespread adoption and implementation. Considering these challenges, collaboration and innovation are essential to unlocking the full transformative potential of blockchain in reshaping the landscape of global finance. By addressing regulatory uncertainties, enhancing scalability, and fostering collaboration between industry stakeholders and policymakers, blockchain technology can pave the way for a more efficient, transparent, and inclusive international financial ecosystem.
In recent years, both researchers and internet users have been attracted to the concept of blockchain technology for transforming smart Bangladesh. This study focuses on the possibilities of blockchain technology leading to the transformation of Bangladesh into a smart nation. This article also explains the working procedure and potential usage of the blockchain concept in Bangladesh. The study is mainly focused on qualitative approaches. The researcher used the PRISMA 2020 platform to identify and choose relevant studies and reports from indexed publications. As the idea of block chain technology is very new and not being adopted by all the sectors of Bangladesh's economy, that’s why only secondary data were used to conduct the study. The researcher has tried to find the different potential areas of blockchain technology from such developing countries like Bangladesh. The potential areas, such as the supply chain management, voting system, and health care industry, where blockchain can be implemented by introducing different polices and regulations. From the implication point of view, blockchain technology might be implemented to transform smart Bangladesh within 2041 if adequate regulations can be undertaken by concerned authority. This revolutionary technology has great potential and has recently caused upheaval. Based on the descriptive study, some of the relevant recommendations including suggestions for reducing challenges of using blockchain are discussed and future research works can be continued in both academic and business sectors in Bangladesh based on this finding.
Smart contracts are decentralized applications built atop blockchains like Ethereum. Recent research has shown that large language models (LLMs) have potential in auditing smart contracts, but the state-of-the-art indicates that even GPT-4 can achieve only 30% precision (when both decision and justification are correct). This is likely because off-the-shelf LLMs were primarily pre-trained on a general text/code corpus and not fine-tuned on the specific domain of Solidity smart contract auditing. In this paper, we propose iAudit, a general framework that combines fine-tuning and LLM-based agents for intuitive smart contract auditing with justifications. Specifically, iAudit is inspired by the observation that expert human auditors first perceive what could be wrong and then perform a detailed analysis of the code to identify the cause. As such, iAudit employs a two-stage fine-tuning approach: it first tunes a Detector model to make decisions and then tunes a Reasoner model to generate causes of vulnerabilities. However, fine-tuning alone faces challenges in accurately identifying the optimal cause of a vulnerability. Therefore, we introduce two LLM-based agents, the Ranker and Critic, to iteratively select and debate the most suitable cause of vulnerability based on the output of the fine-tuned Reasoner model. To evaluate iAudit, we collected a balanced dataset with 1,734 positive and 1,810 negative samples to fine-tune iAudit. We then compared it with traditional fine-tuned models (CodeBERT, GraphCodeBERT, CodeT5, and UnixCoder) as well as prompt learning-based LLMs (GPT4, GPT-3.5, and CodeLlama-13b/34b). On a dataset of 263 real smart contract vulnerabilities, iAudit achieves an F1 score of 91.21% and an accuracy of 91.11%. The causes generated by iAudit achieved a consistency of about 38% compared to the ground truth causes.