Tao Yan, Shengnan Li, Benjamin Kraner, Luyao Zhang · 5 authors
Ethereum 2.0, as the preeminent smart contract blockchain platform, guarantees the precise execution of applications without third-party intervention. At its core, this system leverages the Proof-of-Stake (PoS) consensus mechanism, which utilizes a stochastic process to select validators for block proposal and validation, consequently rewarding them for their contributions. However, the implementation of blockchain technology often diverges from its central tenet of decentralized consensus, presenting significant analytical challenges. Our study collects consensus reward data from the Ethereum Beacon chain and conducts a comprehensive analysis of reward distribution and evolution, categorizing them into attestation, proposer and sync committee rewards. To evaluate the degree of decentralization in PoS Ethereum, we apply several inequality indices, including the Shannon entropy, the Gini Index, the Nakamoto Coefficient, and the Herfindahl-Hirschman Index (HHI). Our comprehensive dataset is publicly available on Harvard Dataverse, and our analytical methodologies are accessible via GitHub, promoting open-access research. Additionally, we provide insights on utilizing our data for future investigations focused on assessing, augmenting, and refining the decentralization, security, and efficiency of blockchain systems.
Document management in the rental market is a critical process to ensure the accuracy of financial transactions and regulatory compliance in the sector. In Portugal, the challenges include the complexity of legislation, particularly GDPR non-compliance, lack of transparency, and bureaucratic process inefficiency. With this in mind, a solution based on Hyperledger Fabric, a blockchain platform, is presented for the implementation of a document management system for the rental process. This system oversees the rental process, which consists of three phases: the application for a property by the prospective tenant through the upload of necessary documents, acceptance/rejection by the landlord of various received applications, and the creation of a report by the system, which only the auditor can request and view. The system smart contract records metadata associated with the documents (hash, owner) and coordinates requests for file access by landlords to prospective tenants. Thus, the system is responsible for creating immutable and traceable records of the entire process. The underlying platform serves as the foundation for conducting future audits. After the landlord verifies the files and accepts the rental proposal, any authorised auditor can request a report for a property by accessing the records through the final report, which includes all events that occurred during the process.
In this paper, we studyhow to optimize existing non-fungible token (NFT) incentives. Upon exploring a large number of NFT-related standards and real-world projects, we uncover an unexpected finding: current NFT incentive mechanisms, often organized in an isolated and one-time-use fashion, tend to overlook their potential for scalable organizational structures. To address this, we propose, analyze, and implement a novelreference incentivemodel, inherently structured as a directed acyclic graph (DAG)-based NFT network. Leveraging the Stackelberg game framework and deep reinforcement learning (DRL), this model aims to maximize connections (or references) between NFTs, enabling isolated NFTs to expand their networks and accumulate rewards from subsequent or subscribed ones. Through both theoretical and practical analyses, we demonstrate the optimal utility of the proposed model.
Renan Lima Baima, Loïck Chovet, Johannes Sedlmeir, Miguel A. Olivares-Méndez · 5 authors
In the emerging space economy, autonomous robotic missions with specialized goals such as mapping and mining are gaining traction, with agencies and enterprises increasingly investing resources. Multirobot systems (MRS) research has provided many approaches to establish control and communication layers to facilitate collaboration from a technical perspective, such as granting more autonomy to heterogeneous robotic groups through auction-based interactions in mesh networks. However, stakeholders' competing economic interests often prevent them from cooperating within a proprietary ecosystem. Related work suggests that distributed ledger technology (DLT) might serve as a mechanism for enterprises to coordinate workflows and trade services to explore space resources through a transparent, reliable, non-proprietary digital platform. We challenge this perspective by pointing to the core technical weaknesses of block chains, in particular, increased energy consumption, low throughput, and full transparency through redundancy. Our objective is to advance the discussion in a direction where the benefits of DLT from an economic perspective are weighted against the drawbacks from a technical perspective. We finally present a possible DLT-driven heterogeneous MRS for map exploration to study the opportunities for economic collaboration and competitiveness.
This research introduces innovative features tailored to capture distinctive characteristics of ransomware activity within the cryptocurrency ecosystem. The study employs a multifaceted analysis to delve into ransomware-related data encompassing transaction metadata, ransom analysis, behavioral patterns, and financial aspects. A feature selection algorithm is explored to discern ransomware transactions in Bitcoin (BTC) and the United States Dollar (USD) using the UGRansome dataset. This comprehensive dataset of ransomware-related transactions facilitates the proposal of novel features designed to capture the unique traits of ransomware activity. The correlation matrix and temporal analysis of these features contribute to a nuanced understanding of the dynamic nature of ransomware threats. The research presents the Ransomware Feature Selection Algorithm (RFSA) based on Gini Impurity and Mutual Information (MI) to effectively select crucial ransomware features. Evaluation metrics such as precision, recall, accuracy, and F1 score highlight the effectiveness of the RFSA. The analysis reveals that approximately 68% of ransomware incidents involve BTC transactions ranging from 1.46 to 2.56, with an average of 2.01 BTC transactions per attack. Moreover, ransomware causes financial damages ranging from 4.38 to 172.36 USD, with an average damage of 88.37 USD. The RFSA identifies 17 ransomware types and their associated malware to shed light on their characteristics. The study investigates the pricing of ransomware and reveals that TowerWeb is associated with the highest fee, amounting to 135.26 BTC, while CryptoLocker has the lowest fee, recorded at 10.51 BTC. Additionally, the impact of ransomware duration on financial gains and network flow is investigated, disclosing a correlation between extended duration and higher financial gains. The research achieves outstanding performance metrics, including an MI score of 95%, accuracy of 93%, recall of 92%, and precision of 89%. These results showcase the superiority of the proposed approach over existing studies, emphasizing the dynamic and adaptable nature of ransomware demands. The findings suggest that there is no fixed amount for specific cyberattacks. This underscores the importance of adapting to the evolving landscape of ransomware threats.
Ludmila Courtillat--Piazza, Thibault Pirson, Louis Golard, David Bol
Bitcoin mining is regularly pointed out for its massive energy consumption and associated greenhouse gas emissions, hence contributing significantly to climate change. However, most studies ignore the environmental impacts of producing mining equipment, which is problematic given the short lifespan of such highly specific hardware. In this study, we perform a cradle-to-gate life cycle assessment (LCA) of dedicated Bitcoin mining equipment, considering their specific architecture. Our results show that the application-specific integrated circuit designed for Bitcoin mining is the main contributor to production-related impacts. This observation applies to most impact categories, including the global warming potential. In addition, this finding stresses out the necessity to carefully consider the specificity of the hardware. By comparing these results with several usage scenarios, we also demonstrate that the impacts of producing this type of equipment can be significant (up to 80% of the total life cycle impacts), depending on the sources of electricity supply for the use phase. Therefore, we highlight the need to consider the production phase when assessing the environmental impacts of Bitcoin mining hardware. To test the validity of our results, we use the Sphera LCA and ecoinvent databases for the background modeling of our system. Surprisingly, it leads to results with variations of up to 4 orders of magnitude for toxicity-related indicators, despite using the same foreground modeling. This database mismatch phenomenon, already identified in previous studies, calls for better understanding, consideration and discussion of environmental impacts in the field of electronics, going well beyond climate change indicators.
The current blockchain system for cryptocurrency exchanges primarily employs elliptic curve cryptography (ECC) for generating key pairs in wallets, and elliptic curve digital signature algorithms (ECDSA) for generating signatures in transactions. Consequently, with the maturation of quantum computing technology, the current blockchain system faces the risk of quantum computing attacks. Quantum computers may potentially counterfeit signatures produced by ECDSA. Therefore, this study analyzes the vulnerabilities of the current blockchain system to quantum computing attacks and proposes a post-quantum cryptography (PQC)-based blockchain system to enhance security by addressing and improving each identified weakness. Furthermore, this study proposes PQC-based wallets and PQC-based transactions, utilizing PQC digital signature algorithms to generate PQC-based signatures for the inputs in PQC-based transactions, thereby preventing signatures from being counterfeited by quantum computing. Experimental results demonstrate that the efficiency of the Module-Lattice-Based Digital Signature Algorithm (ML-DSA), a PQC digital signature algorithm, in producing wallets, generating signatures, and verifying signatures surpasses that of ECDSA in the current blockchain system. Furthermore, the ML-DSA also exhibits a higher security level.
Crypto donations now represent a significant fraction of charitable giving worldwide. Nonfungible token (NFT) charity fundraisers, which involve the sale of NFTs of artistic works with the proceeds donated to philanthropic causes, have emerged as a novel development in this space. A unique aspect of NFT charity fundraisers is the significant potential for donors to reap financial gains from the rising value of purchased NFTs. Questions may arise about donors' motivations in these charity fundraisers, potentially resulting in a negative social image. NFT charity fundraisers thus offer a unique opportunity to understand the economic consequences of a donor's social image. We investigate these effects in the context of a large NFT charity fundraiser. We identify the causal effect of purchasing an NFT within the charity fundraiser on a donor's later market outcomes by leveraging random variation in transaction processing times on the blockchain. Further, we demonstrate a clear pattern of heterogeneity based on an individual's decision to relist (versus hold) the purchased charity NFTs (a sign of perceived strategic generosity) and based on an individual's social exposure within the NFT marketplace. We show that charity-NFT 're-listers' experience significant penalties in the market regarding the prices they can command for their other NFTs, particularly among those who are more socially exposed. Finally, we report the results of a scenario-based online experiment, which again support our findings, highlighting that the re-listing a charity NFT for sale at a profit leads others to perceive their initial donation as strategic generosity and reduces those others' willingness to purchase NFTs from the donor. Our study underscores the growing importance of digital visibility and traceability, features that characterize crypto-philanthropy, and online philanthropy more broadly.
Web3 provides users and service providers several benefits not found in Web2. However, despite the benefits provided, Web3 faces several obstacles that prevent the paradigm from gaining widespread adoption. Developers should understand the benefits and limitations of the technology in order to create more accessible Web3 smart applications.
Christian Ziegler, Marcos Luiz Cavalcanti de Miranda, Guangye Cao, Gustav Arentoft · 5 authors
Our study demonstrates the effective use of Large Language Models (LLMs) for automating the classification of complex datasets. We specifically target proposals of Decentralized Autonomous Organizations (DAOs), as the clas-sification of this data requires the understanding of context and, therefore, depends on human expertise, leading to high costs associated with the task. The study applies an iterative approach to specify categories and further re-fine them and the prompt in each iteration, which led to an accuracy rate of 95% in classifying a set of 100 proposals. With this, we demonstrate the po-tential of LLMs to automate data labeling tasks that depend on textual con-text effectively.
Abayomi Agbeyangi, Ayodeji Makinde, Isaac Odun-Ayo
Nigeria's remarkable information and communication technology (ICT) journey spans decades, playing a pivotal role in economic sustainability, especially as the nation celebrates its Republic at Sixty. This paper provides an overview of Nigeria's ICT journey, underscoring its central role in sustainable economic prosperity. We explore the potential of artificial intelligence, blockchain, and the Internet of Things (IoT), revealing the remarkable opportunities on the horizon. We stress the urgency of achieving digital inclusivity, bridging the urban-rural gap, and reducing the technological divide, all of which are critical as Nigeria marks its sixtieth year. We intend to prove the invaluable opportunities of ICT for policymakers, business leaders, and educational institutes as Nigeria looks towards enduring economic development in this digital age. Specifically, we envision a dynamic landscape where emerging technologies are set to redefine industries, supercharge economic growth, and enhance the quality of life for every Nigerian.
No one can dispute the disruptive impact of blockchain technology, which has long been considered one of the major revolutions of contemporary times. Its integration into the healthcare ecosystem has helped overcome numerous difficulties and constraints faced by healthcare systems. This has been notably demonstrated in the meticulous management of electronic health records (EHR) and their access rights, as well as in its capabilities in terms of security, scalability, flexibility, and interoperability with other systems. This article undertakes the study and analysis of the most commonly adopted approaches in healthcare data management systems using blockchain technology. An evaluation is then conducted based on a set of observed common characteristics, distinguishing one approach from the others. The results of this analysis highlight the advantages and limitations of each approach, thus facilitating the choice of the method best suited to the readers' specific case study. Furthermore, for effective implementation in the context of e-health, we emphasize the existence of crucial challenges, such as the incomplete representation of major stakeholders in the blockchain network, the lack of regulatory flexibility to ensure legal interoperability by country, and the insufficient integration of an official regulatory authority ensuring compliance with ethical and legal standards. To address these challenges, it is necessary to establish close collaboration between regulators, technology developers, and healthcare stakeholders.
The precise characterization and modeling of Cyber-Physical-Social Systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the ``6A-goal" of ACS and propose potential avenues for future research.
Abstract Decentralized applications (DApps) built on blockchain platforms such as Ethereum and coded in languages such as Solidity, have recently gained attention for their potential to disrupt traditional centralized systems. Despite their rapid adoption, limited research has been conducted to understand the underlying code structure of these applications. In particular, each DApp is composed of multiple smart contracts, each containing a number of functions that can be called to trigger a specific event, e.g., a token transfer. In this paper, we reconstruct and analyse the network of contracts and functions calls within the DApp, which is helpful to unveil vulnerabilities that can be exploited by malicious attackers. We show how decentralization is architecturally implemented, identifying common development patterns and anomalies that could influence the system’s robustness and efficiency. We find a consistent network structure characterized by modular, self-sufficient contracts and a complex web of function interactions, indicating common coding practices across the blockchain community. Critically, a small number of key functions within each DApp play a central role in maintaining network connectivity, making them potential targets for cyber attacks and highlighting the need for robust security measures.
Juan Ignacio Ibañez, Aayush Ladda, Paolo Tasca, Logan Aldred
The environmental impact of Bitcoin mining has become a significant concern, prompting several governments to consider or implement bans on cryptocurrency mining. However, these well-intentioned policies may lead to unintended consequences, notably the redirection of mining activities to regions with higher carbon intensities. This study aims to quantify the environmental effectiveness of Bitcoin mining bans by estimating the resultant carbon emissions from displaced mining operations. Our findings indicate that, contrary to policy goals, Bitcoin mining bans in low-emission countries can result in a net increase in global carbon emissions, a form of aggravated carbon leakage. We further explore the policy implications of these results, suggesting that more nuanced approaches may be required to mitigate the environmental impact of cryptocurrency mining effectively. This research contributes to the broader discourse on sustainable cryptocurrency regulation and provides a data-driven foundation for evaluating the true environmental costs of Bitcoin regulatory policies.
Decentralized Autonomous Organizations (DAOs) are blockchain-based organizations that facilitate decentralized governance. Today, DAOs not only hold billions of dollars in their treasury but also govern many of the most popular Decentralized Finance (DeFi) protocols. This paper systematically analyses security threats to DAOs, focusing on the types of attacks they face. We study attacks on DAOs that took place in the past, attacks that have been theorized to be possible, and potential attacks that were uncovered and prevented in audits. For each of these (potential) attacks, we describe and categorize the attack vectors utilized into four categories. This reveals that while many attacks on DAOs take advantage of the less tangible and more complex human nature involved in governance, audits tend to focus on code and protocol vulnerabilities. Thus, additionally, the paper examines empirical data on DAO vulnerabilities, outlines risk factors contributing to these attacks, and suggests mitigation strategies to safeguard against such vulnerabilities.
This paper examines the complex legal landscape surrounding digital assets, analysing how they are defined and regulated as property across various jurisdictions. As digital assets such as cryptocurrencies and non-fungible tokens (NFTs) increasingly integrate with global economies, their intangible nature presents unique challenges to traditional property law concepts, necessitating a re-evaluation of legal definitions and ownership frameworks. This research presents a comparative analysis, reviewing how different legal systems classify and manage digital assets within property law, highlighting the variations in regulatory approaches and their implications on ownership, transfer, and inheritance rights. By examining seminal cases and regulatory developments in major jurisdictions, including the United States, the European Union, and Singapore, this paper explores the emerging trends and potential legal evolutions that could influence the global handling of digital assets. The study aims to contribute to the scholarly discourse by proposing a harmonized approach to digital asset regulation, seeking to balance innovation with legal certainty and consumer protection.
Cryptocurrencies have evolved into an important asset class, providing a variety of benefits. However, they also present significant risks, such as market volatility and the potential for misuse in illegal activities. These risks underline the urgent need for a comprehensive regulatory framework to ensure consumer protection, market integrity, and financial stability. Yet, the global landscape of cryptocurrency regulation remains complex, marked by substantial variations in regulatory frameworks among different countries. This paper aims to study these differences by investigating the regulatory landscapes across various jurisdictions. We first discuss regulatory challenges and considerations, and then conduct a comparative analysis of international regulatory stances, approaches, and measures. We hope our study offers practical insights to enhance the understanding of global trends in cryptocurrency regulation.
Md Arif Hassan, Mohammad Behdad Jamshidi, Bui Duc Manh, Nam H. Chu · 12 authors
Web 3.0 represents the next stage of Internet evolution, aiming to empower users with increased autonomy, efficiency, quality, security, and privacy. This evolution can potentially democratize content access by utilizing the latest developments in enabling technologies. In this paper, we conduct an in-depth survey of enabling technologies in the context of Web 3.0, such as blockchain, semantic web, 3D interactive web, Metaverse, Virtual reality/Augmented reality, Internet of Things technology, and their roles in shaping Web 3.0. We commence by providing a comprehensive background of Web 3.0, including its concept, basic architecture, potential applications, and industry adoption. Subsequently, we examine recent breakthroughs in IoT, 5G, and blockchain technologies that are pivotal to Web 3.0 development. Following that, other enabling technologies, including AI, semantic web, and 3D interactive web, are discussed. Utilizing these technologies can effectively address the critical challenges in realizing Web 3.0, such as ensuring decentralized identity, platform interoperability, data transparency, reducing latency, and enhancing the system's scalability. Finally, we highlight significant challenges associated with Web 3.0 implementation, emphasizing potential solutions and providing insights into future research directions in this field.
This note and agenda serve as a cause for thought for scholars interested in researching Decentralized Autonomous Organizations (DAOs), addressing both the opportunities and challenges posed by this phenomenon. It covers key aspects of data retrieval, data selection criteria, issues in data reliability and validity such as governance token pricing complexities, discrepancy in treasuries, Mainnet and Testnet data, understanding the variety of DAO types and proposal categories, airdrops affecting governance, and the Sybil problem. The agenda aims to equip scholars with the essential knowledge required to conduct nuanced and rigorous academic studies on DAOs by illuminating these various aspects and proposing directions for future research.
In the PoS blockchain landscape, the challenge of achieving full decentralization is often hindered by a disproportionate concentration of staked tokens among a few validators. This study analyses this challenge by first formalizing decentralization metrics for weighted consensus mechanisms. An empirical analysis across ten permissionless blockchains uncovers significant weight concentration among validators, underscoring the need for an equitable approach. To counter this, we introduce the Square Root Stake Weight (SRSW) model, which effectively recalibrates staking weight distribution. Our examination of the SRSW model demonstrates notable improvements in the decentralization metrics: the Gini index improves by $37.16 \%$ on average, while Nakamoto coefficients for liveness and safety see mean enhancements of $101.04 \%$ and $80.09 \%$, respectively. This research is a pivotal step toward a more fair and equitable distribution of staking weight, advancing the decentralization in blockchain consensus mechanisms.
The burgeoning interest in both the circular economy and blockchain technology has spurred numerous proposed integrations. Despite this enthusiasm, empirical research examining the practical feasibility and critical assessment of blockchain's potential within the circular economy remains limited. This study engages with eleven distinguished blockchain experts to critically analyze the prospects of technology integration across various facets of the circular economy, aiming to predict potential outcomes. Utilizing the Delphi method, this research seeks to attain a consensus on the experts' visions and opinions. The findings suggest a nuanced perspective: while certain integrations in the circular economy may face challenges and are unlikely to succeed, others could prove effective in the long term, provided specific conditions are met. When appropriately designed Tokenomics are in place, and the necessary level of digitalization is achieved, blockchain technology can significantly incentivize circular economy practices. However, the complete disintermediation of circular practices through blockchain is viewed as less feasible, owing to its reliance on external data providers.
Sarah A. Flanery, Kamalesh Mohanasundar, Christiana Chamon, Srujan Kotikela · 5 authors
With the natural evolution of the web, the need for decentralization has rendered the current centralized education system out of date. The student does not "own" their credentials, as the only way their accomplishments are directly linked to their person and considered valuable is by verification through a stamp of an expensive, prestigious institution. However, going to a university is no longer the only way to acquire an education; open-source learning material is widely available and accessible through the internet. However, our society does not deem these methods of education as verifiable if they do not include a degree or certificate. Additionally, a valid certificate for the vast majority of open-source courses costs a few hundred dollars to obtain. The centralized nature of education inadvertently places students in underprivileged communities at a disadvantage in comparison to students in economically advantaged communities, thus a decentralized approach to education would eliminate the vast majority of such discrepancies. In the present paper, we integrate Decentralized Identity (DID) with Web 3.0 to upload credentials linked directly to the user. Each credential is appended to an Ethereum blockchain that, by design, cannot be altered once uploaded. We include DID document based access controls to display the candidate's upload and verification history. Finally, we utilize TLS protocols to provide a secure connection to the internet for ensuring non-fungibility of credentials and authentication of users.
NFTs (Non-Fungible Tokens) have seen significant growth since they first captured public attention in 2021. However, the NFT market is plagued by fake transactions and economic bubbles, e.g., NFT wash trading. Wash trading typically refers to a transaction involving the same person or two colluding individuals, and has become a major threat to the NFT ecosystem. Previous studies only detect NFT wash trading from the financial aspect, while the real-world wash trading cases are much more complicated (e.g., not aiming at inflating the market value). There is still a lack of multi-dimension analysis to better understand NFT wash trading. Therefore, we present the most comprehensive study of NFT wash trading, analyzing 8,717,031 transfer events and 3,830,141 sale events from 2,701,883 NFTs. We first optimize the dataset collected via the OpenSea API. Next, we identify three types of NFT wash trading and propose identification algorithms. Our experimental results reveal 824 transfer events and 5,330 sale events (accounting for a total of \$8,857,070.41) and 370 address pairs related to NFT wash trading behaviors, causing a minimum loss of \$3,965,247.13. Furthermore, we provide insights from six aspects, i.e., marketplace design, profitability, NFT project design, payment token, user behavior, and NFT ecosystem.