Blockchain Papers

Cameron MacDonald, Laura Zhao

No abstract is available for this record.

Fabio Bassan, Maddalena Rabitti

The issue surrounding the nature and function of smart contracts in the context of legal relationships has garnered significant attention from the European and national legislators, regulatory bodies and legal scholarship. Sections I and II of this essay give an account of the results of the ongoing doctrinal debate, which is not univocal. The objective is to provide an assessment of both the advantages and limitations associated with smart legal contracts. In Section III, the authors introduce a novel negotiation process termed "contracts on chain". This process enables parties to engage in negotiations, formalize agreements and execute contracts directly on the blockchain . Consequently, this negotiation approach serves as a potential bridge between the realms of Web 2 and Web 3. Further, it offers a user experience akin to online contracts but benefits from the inherent capabilities of third-generation blockchains. Albeit on-chain contracts can be deployed on both private and public blockchains, the authors express a preference for their use on the public blockchain within a "logical platform". This choice allows to enhance regulatory compliance and mitigate the effects of decentralization on liability regimes, while simultaneously optimizing the efficiency gains of public blockchains. Notably, this approach ensures a level of protection commensurate with that offered by private blockchains. The ultimate goal of this innovative process is to streamline the ongoing technological transition and cultivate greater trust within the market for emerging technologies.

Runhuan Feng, Mao Li

No abstract is available for this record.

Lisa J. Y. Tan

No abstract is available for this record.

Xia Feng, Haiyang Liu, Liangmin Wang, Huijuan Zhu · 5 authors

Smart contracts hold billions of dollars in digital currency, and their security vulnerabilities have drawn a lot of attention in recent years. Traditional methods for detecting smart contract vulnerabilities rely primarily on symbol execution, which makes them time-consuming with high false positive rates. Recently, deep learning approaches have alleviated these issues but still face several major limitations, such as lack of interpretability and susceptibility to evasion techniques. In this paper, we propose a feature selection method for uplifting modeling. The fundamental concept of this method is a feature selection algorithm, utilizing interpretation outcomes to select critical features thereby reducing the scales of features. The learning speed could be accelerated significantly because of the reduction of the feature size. The experiment shows that our proposed model performs well in six types of vulnerability detection. The accuracy of each is higher than 93% and the average detection time of each smart contract is less than 1 ms. Notably, through our proposed feature selection algorithm, the training time of each type of vulnerability is reduced by nearly 80% compared with its original.

Anne Lafarre, Christoph Van der Elst

Blockchain and distributed ledger technologies are considered as transformative for corporate governance and enabling decentralized autonomous organizations (DAOs) that challenge hierarchical structures. However, legal, governance, and liability issues surround DAOs. Despite the aim for decentralization, practical implementation often reveals centralized elements. The chapter also explores blockchain’s impact on traditional corporations, emphasizing improvements in share issuance, trading, and decision-making. Blockchain can also address custody chain problems, enhancing transparency in securities and stock ownership. Yet, transitioning to blockchain, exemplified by ASX CHESS Replacement, is complex. While blockchain holds promise in fostering shareholder and stakeholder rights, a nuanced assessment of limitations and practicalities is crucial. More classical alternatives like secure and transparent centralized systems should also be considered in corporate governance.

Hyungjin Ko, Bumho Son, Jaewook Lee

No abstract is available for this record.

Ken Huang, Xi Chen, Youwei Yang, Jyoti Ponnapalli · 5 authors

No abstract is available for this record.

Nitin Liladhar Rane, Saurabh Choudhary, Jayesh Rane

No abstract is available for this record.

Wanqing Jie, Qi Chen, Jiaqi Wang, Arthur Sandor Voundi Koe · 8 authors

No abstract is available for this record.

Christoph Sendner, Huili Chen, Hossein Fereidooni, Lukas Petzi · 9 authors

Ethereum smart contracts are automated decentralized applications on the blockchain that describe the terms of the agreement between buyers and sellers, reducing the need for trusted intermediaries and arbitration. However, the deployment of smart contracts introduces new attack vectors into the cryptocurrency systems. In particular, programming flaws in smart contracts have been already exploited to lead to enormous financial loss. Hence, it is crucial to detect various vulnerability types in contracts effectively and efficiently. Existing vulnerability detection methods are limited in scope as they typically focus on one or a very limited set of vulnerabilities. Also, extending them to new vulnerability types requires costly re-design. \n \nIn this work, we develop ESCORT, a deep learning-based vulnerability detection method that uses a common feature extractor to learn generic bytecode semantics of smart contracts and separate branches to learn the features of each vulnerability type. As a multi-label classifier, ESCORT can detect multiple vulnerabilities of the contract at once. Compared to prior detection methods, ESCORT can be easily extended to new vulnerability types with limited data via transfer learning. When a new vulnerability type emerges, ESCORT adds a new branch to the trained feature extractor and trains it with limited data. We evaluated ESCORT on a dataset of 3.61 million smart contracts and demonstrate that it achieves an average F1 score of 98% on six vulnerability types in initial training and yields an average F1 score of 96% in transfer learning phase on five additional vulnerability types. To the best of our knowledge, ESCORT is the first deep learning-based framework that utilizes transfer learning on new vulnerability types with minimal model modification and re-training overhead. Compared with existing non-ML tools, ESCORT can be applied to contracts of arbitrary complexity and ensures 100% contract coverage. In addition, we enable concurrent detection of multiple vulnerability types using a single unified framework, thus avoiding the efforts of setting up multiple tools and greatly reducing the detection time. We will open source our dataset and the data labeling toolchain to facilitate future research.

Akanksha Jalan, Roman Matkovskyy

No abstract is available for this record.

Junghwan Cho, Sun-Woong Kim, Heung-Sik Choi

무기한 선물(Perpetual Swaps)은 가상 자산 시장에서만 유일하게 관찰할 수 있는 파생상품으로 2020년 이후 현재 약 20여 곳 이상의 가상 자산 거래소에서 서비스를 제공하고 있으며 2020년 전체 거래 시장의 20.4%, 2021년 50.4%를 차지할 정도로 양적 성장을 이루었다. 본 연구는 거래소 간 비트코인 무기한 선물과 현물(Spot) 간의 가격 차이를 이용해 차익 거래 기회에 대한 실증 분석 결과를 제시한다. 연구 결과, 비트코인 현물과 무기한 선물 가격의 음과 양이 역전 될 때를 거래 진입 및 청산 신호로 인식하는 매매를 통하여 차익 거래 수익을 창출할 수 있음을 확인하였다. 또한 분 단위 거래에서 거래수수료는 차익 거래 수익에 민감하게 작용하였지만, 일 단위 거래에서는 거래 수수료에 민감하지 않은 양의 수익을 보여주었다. 그리고 분 단위 거래에서는 월 평균 9%, 일 단위 거래에서는 월 평균 38%의 높은 수익률을 나타내었다.

Jiaqi Qin, Shansong Huang, Boying Yang, Yilin Ma · 6 authors

Everyone is eager for high yield and low risk. In this research, we use Markowitz's investment theory and Monte Carlo simulation to find the optimal investment portfolio and then study the impact of adding Bitcoin to the traditional investment portfolio on the cumulative rate of return. Our results show that the return performance of the investment portfolio with Bitcoin is better than that of the traditional investment portfolio. Moreover, despite the impact of COVID-19 on the global economy and the Federal Reserve's quantitative easing policy, it is beneficial for investors to include Bitcoin in their portfolio allocation.

ZHENG Yue LI Leixiao

As an important part of blockchain technology, smart contracts are widely used in various fields through decentralized applications written by smart contracts, providing important technical support for the development and application of blockchain. However, the development has brought security problems at the same time, and a large number of vulnerability attacks against smart contracts have made researchers pay more attention to the security vulnerabilities of smart contracts. How to quickly and accurately perform vulnerability detection has become an urgent problem to be solved. Firstly, through the analysis of common vulnerabilities such as reentrancy attack vulnerabilities, integer overflow and access control vulnerabilities, researchers can fully understand the common vulnerabilities. Secondly, by investigating the current status of vulnerability detection methods such as formal verification, symbolic execution, machine learning and their corresponding tools at home and abroad, analyzing and discussing the advantages and disadvantages of the tools, at the same time, replicating some tools for experiments, the performance of the vulnerability detection tools is demonstrated based on the detection speed, accuracy, and the number of vulnerabilities that support detection. Finally, suggestions for future research directions are given based on the analysis results of smart contract vulnerability detection tools.

C Turnbull, Wily Sher, Liyaning Tang

Abstract Construction industry professionals suffer regularly from poor cash-flow which reflects non-payment or payment delays down the hierarchical chain. This issue is important as the construction industry has the highest rates of insolvency in Australia, the UK and many other countries. Payment conditions under current construction contracts have proven to be inefficient in delivering timely payments as human interference has control over processing claims. This paper investigated the status of contracts and contract law in Australia and the potential of smart contract technology in improving payment issues in the industry. Qualitative data was collected from secondary literature sources which included observations from industry professionals, real case studies, secondary research and government surveys. It was found that smart contracts feature self-executing digital contracts, immutable data, require no intermediaries and provide transparency on all levels. Although these features are fit for purpose in resolving current contractual issues, smart contracts are not yet available in the construction industry. It was also found that smart contracts do have the potential to provide a trusted and reliable payment system in the construction industry, although there are some aspects it is unlikely to replace such as human performance. Research limitations and future research directions are also provided.

Sungnam Lee

In this study, the future of the insurance industry and legal tasks related to digitalization and artificial intelligence were examined. What is artificial intelligence technology? Among them, we reviewed what the insurance industry can do and what it is doing, and looked at legal issues and what to change in the future. First of all, the development status of digitalization and artificial intelligence was investigated, and the impact on the insurance industry and the opportunities and risks brought by digitalization and artificial intelligence were examined. Second, if digitalization and the development of artificial intelligence replace existing human tasks, it should be considered whether to treat such artificial intelligence robots or tools as simple tools or give legal effects by giving similar status to humans. Third, the emergence of digitalization and artificial intelligence is expected to have an impact on various areas of insurance work, especially focusing on insurance recruitment work, and legal discussions related to it were attempted. The introduction of digitalization and artificial intelligence is expected to have an impact on the overall financial transaction or insurance transaction. The emergence of new technologies implies new opportunities and risks at the same time. It will also lead to changes in the existing socio-economic and cultural institutions. Legal significance in changes in the insurance environment is related to which process digitalization and artificial intelligence play a role in which of the conventional insurance tasks, and that is the problem caused. It is necessary to guarantee the right to access various channels centered on consumers by drastic deregulation to promote digitalization. Accordingly, insurance companies need to develop a model that allows consumers to actively select suitable, convenient means, and methods for themselves at each stage of insurance subscription. With the rise of the platform as a new business model, it will affect product counseling and recommendation, product description, subscription receipt, notification receipt, premium receipt, and insurance policy issuance, so in-depth discussions are needed on whether to accept the platform as a new recruitment channel or as a simple information provider or advisory business. In seeking legal changes through the introduction of digitalization and artificial intelligence, whether or not to grant a legal personality to tools or platforms equipped with artificial intelligence, which is the starting point of the most basic discussion, needs to be carefully introduced in consideration of future technological developments and social needs. As a legal discussion due to the advent of digitalization and artificial intelligence, the legal effects of AI intervention and operation were examined. At each transaction stage, various notifications and explanations that insurance recruiters must perform before signing insurance contracts, automation of subscription receipt and approval, and legal improvement should be promoted. Meanwhile, with the development of artificial intelligence technology, unmanned transportation such as robot dogs, robot disabled assistants, drones, trucks, aircraft, ships, etc., virtual assets, digital currency, metaverse, and NFT (non-fungible token) will be developed and utilized. It is necessary to solve the legal problems that these various artificial intelligence tools can create and guarantee measures through the development of new insurance products. Dr Stephen Hawking said, “The advent of powerful artificial intelligence will be the best or the worst. What could happen to mankind. We don’t know which one.” However, the reality is that artificial intelligence technology has been developed and used for each task. With history evolving in time, society is causing significant changes.

Eliza Mik

Given the continuing fascination with “magic computers” and “self-executing code,” it is necessary to re-examine the promises – and premises - of technology-driven improvements to transacting practices purportedly introduced by smart contracts. Contrary to the popular narrative, smart contracts do not eliminate the need for trust and are technically incapable of guaranteeing performance. The fascination with clear and unbreakable rules that are executed by code obfuscates the fact that such rules may be suboptimal and may incorrectly represent what was agreed. It also obscures the fact that it is impossible to write perfect code. Being in plain view and impossible to modify, changes nothing in this regard. Trust and certainty do not magically emerge from immutability or transparency. Regulatory efforts in this area must be based on facts, not fairy tales.

Heinz Herrmann, Becksndale Masawi

Abstract The banking, financial services, and insurance (BFSI) sector is one of the earliest and most prominent adopters of artificial intelligence (AI). However, academic research substantially lags behind the adoption of AI in practice. At the beginning of this century, AI research has been centered on the sector's credit risk. In the 2010s decade, expert systems were increasingly replaced by data‐driven, “algorithmic” AI. Big data enjoyed much hype in that decade, which diminished later mostly due to unsuccessful implementations. Much published research on big data actually relates to machine and deep learning but not to big data per se. These terms are often found to be conflated in research and practice. The insurance sector is substantially underrepresented in published AI research, and current research is dominated by banking and investments. Governance frameworks for “responsible AI” (RAI) are yet to be incorporated into practice by fintech companies as well as incumbent organizations. RAI is a particular issue for decentralized finance (DeFi). The most successful implementations of AI in BFSI practice, as well as dominant academic research areas, are in investments, securities, market making, customer relationships, lending, risk management, and compliance.

Nada Mallah Boustani, Magnaghi Elisabetta

As the Fourth Industrial Revolution gains momentum and involves a plethora of disruptive technology concepts, such as blockchain, they have infiltrated economies that have only experienced a small portion of their scope, consequences, and applications in their different branches. This research aims to examine the potential uses of blockchain technology within the framework of smart contracts in the insurance sector, notably in the event of a pandemic that results in business interruption. Businesses hardly ever take business interruption insurance into account, particularly in a country similar to Lebanon, where natural disasters and pandemics are scarce. Due to the complexity of the task and the numerous requirements for trust in terms of risk consistency, traditional insurance companies are not interested in offering these kinds of insurance contracts. In this current study, a quantitative study was conducted over 213 businesses in various fields and revealed acceptance and socio-demographic differences in the activity sectors of this potentially ground-breaking solution for a developing country that is undergoing a sanitary and economic crisis. As a result, smart contracts and decentralized finance (DeFi) were proposed in the current research as potential solutions to overcome the Lebanese currency devaluation and high insurance costs.

Jasvant Mandloi, Pratosh Bansal

Real-world application development through Smart Contracts on the Ethereum Blockchain platform is one of the emerging technologies. It also has much vulnerability, and reentrancy is among the most popular ones. In our work, we have reviewed the tools based on ML for vulnerability detection in Ethereum smart contracts. Based on that, we proposed a framework that can dynamically monitor threats based on the blockchain platform's transaction meta-data and balance data. It does not require any changes or updates to the existing system and does not require expertise to implement. This framework will extract features for machine learning classifier models from the transaction data and identify the transaction as agreeable or unfavorable. It will help to identify the reentrancy threat as well as the cause of it and help the developer to trace it from where the attack is generated. In the ML classifier for the framework, random forest and decision tree are used. The cumulative performance of both is 98 percent on 540 transactions.

John R. Graham, Jillian Grennan, Campbell R. Harvey, Shivaram Rajgopal

Culture is given credit for some of the greatest business successes and blamed for some of the biggest failures. Policymakers often point to dysfunctional corporate culture in banking as a first-order contributor to the recent financial crisis.1 Several books identify culture as a key driver of Google's success.2 What is corporate culture? How important is corporate culture? What mechanisms underlie the creation and effectiveness of corporate culture?4 How do other formal institutions (e.g., governance or compensation) reinforce or work against culture? Do companies think their culture is effective and if not, what deters firms from having an effective corporate culture? Are the upside benefits of an effective culture greater than the downside costs of ineffective culture? What aspects of business performance does corporate culture affect? Does culture impact firm value, productivity, corporate risk-taking, growth, M&A, financial and tax reporting, whether employees take a long-run view, and/or corporate ethics? How can corporate culture be measured? We try to answer these questions in multiple ways. First, we surveyed 1348 chief executives and financial officers (CEOs and CFOs, referred to interchangeably as executives or managers) across a wide range of North American public and private firms. The details underlying the survey evidence and an econometric investigation into the effects of culture on business outcomes are reported in an accompanying paper5 by the same four authors that supplement this paper; referred to henceforth as GGHR. Second, the survey contained several open-ended questions. We analyze the text of these questions to enhance our understanding of the survey respondents' views of the corporate culture. Third, we conducted in-depth interviews with business executives representing over 20% of the US equity market capitalization. The purpose of this paper is to discuss the interview evidence and the open-ended responses from the survey. We summarize the survey statistics to provide context for the interviews and open-ended responses. Survey evidence offers a number of insights into corporate culture. Briefly, the survey shows that managers are largely united in believing that corporate culture is one of the most important forces behind value creation and the ultimate success or failure of a firm. The majority of executives consider corporate culture to be a top three value driver at their companies. Almost every officer believes that improving their corporate culture would increase their firm's value. The current CEO is seen as the most influential person responsible for setting the firm's current culture. The interviews offer insight into how other firm policies and practices may reinforce or work against the effectiveness of the culture. Boards affect culture not via active management but primarily via CEO choice. The finance function may influence the culture, especially when it serves an internal governance role by acting as steward of integrity. Incentive compensation and hiring, firing, and promotion decisions also may modify the effectiveness of a firm's culture. 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Sunyoung Park

2022년 5월 알고리즘 스테이블코인 테라의 폭락은 국내 규제당국자들과 일반 대중에게 가상자산과 DeFi의 위험성을 알려준 계기가 되었을 뿐 아니라 국내 가상자산 규제도입 속도를 높이는 데 기여하였다. DeFi란 탈중앙화 금융(decentralized finance)의 약자로서 블록체인 기술을 기반으로 스마트 계약(smart contract)을 이용하여 전통 금융에서 제공하는 것과 유사한 상품을 중개기관 없이 자동화된 시스템으로 제공하고자 하는 서비스를 통틀어서 일컫는다. 2020년부터 급격하게 성장한 DeFi 생태계는 글로벌 가상자산 시장에서 핵심적인 역할을 수행하고 있으나, 국내에는 DeFi에 대한 연구는 부족한 실정이다. 본 논문에서는 DeFi의 개념과 구조, 종류와 현황, 구조적 취약성과 테라 사태, 글로벌 규제 동향을 살펴봄으로써 국내 규제의 시사점을 도출하고자 한다.

Rasmeet Kaur, A. Ali, Md Faisal

The emergence of “smart contracts” has been aided by rapid advancements in the expanding field of blockchain technology. A smart contract works similarly to a regular agreement but without the need for a third party to be involved. To rectify or upgrade the smart contract is not an easy task for security updates once it has been put on the blockchain, so developers should include robust security techniques before distribution to mitigate any later manipulation. Smart contracts that incorporate blockchain methodology can work in real-time at fewer expenses and with a higher level of security. The first section of the chapter presents the basic introduction and operating principles of smart contracts. The following section elaborates on the various security issues. The third section provides smart contract use cases; finally, the study discusses the challenges of smart contracts in a real-life scenario.