Blockchain Papers

S. B. Indra, S. Harshini, R. Sabitha

No abstract is available for this record.

Eman Daraghmi, Shadia Jayousi, Yousef‐Awwad Daraghmi, Raed S. M. Daraghma · 5 authors

The agriculture sector stands as one of the most significant sectors sustaining 70 percent of the world’s population. In this sector, the supply consists of a series of interconnected stages, spanning from farming through production to the final delivery of goods to the end customer. A lack of transparency within the supply chain presents the largest gap between suppliers and retailers, such as ensuring the true value of products or services. This research introduces AgroChain, a Blockchain-based system that is designed to support the Agricultural Supply Chain (ASC) process. For scalability purposes, the proposed AgroChain solution comply with a process model that separates the registry of agricultural records from the record itself. The development of the AgroChain prototype along with its smart contracts that establish a transparent, yet secure, environment within the ASC under Quorum which is Ethereum oriented network is illustrated in this research. This research demonstrates that Blockchain networks offer a solution to manage the ASC ensuring traceability, privacy and integrity. Moreover, the research indicates that there is a pressing need to promote the standardization of ASC smart contracts, incorporating secure and straightforward process. Smart contracts have to ideally be implemented in consortium environments, enabling reliable validation of transactions by independent third parties without necessitating access to their content. Moreover, investigating the accountability for illegal activities become challenging.

Zulfiqar Ali Khan, Akbar Siami Namin

Ethereum Blockchain technology introduced a competitive environment in the financial sector. Consequently, new technologies emerged, such as Smart Contracts (SCs), which preclude code corrections due to their immutable nature. But the incorrect and faulty uploaded SCs led to uninvited penetrations into SCs’ accounts, resulting in considerable customer losses. This SC’s drawback requires tools to test the SCs and paves the way for research on vulnerability detection techniques. Our survey paper comprehensively reviews 41 SC tools and presents the vulnerability detection techniques (VDTs) of the several previously discussed tools by dividing them into general and specific classes. Finally, we also perform a classification of detection techniques to standardize the approaches. Thus, our study will help SC developers and security analysts to streamline the security of SCs and reduce the chances of malicious monetary transfers.

Ujkan Q. Bajra, Ermir Rogova, Sefer Avdiaj

No abstract is available for this record.

Hanfang Chen, Niankun Wei, Leyao Wang, Wael Mobarak · 6 authors

Blockchain has been a vibrant technology in the past decade, with a wide variety of applications across different industrial sectors. The concept of blockchain has been widely recognized as an enabler for cryptocurrency-based decentralized payments, with two major decentralized payment systems such as Bitcoin and Ethereum. However, the global acceptance of blockchain as a cryptocurrency sums up significant challenges that hinder the fast adaptation of cryptocurrency as a payment service enabler. In this survey, we explore the advantages of blockchain and its technical capabilities beyond cryptocurrency. We focus on the technical potential to ensure trust, data governance, and automation of the financial application domain utilizing the fundamental security features of blockchain, including consensus, digital signatures, and transparency. The significant subcomponents of trust, data management, and automation in banking and financial systems are also identified and discussed, including how blockchain and smart contracts can achieve the anticipated features of each subcomponent through their technical capabilities. In addition, we shed light on the position of blockchain-based applications in key application sectors of the banking and financing domain with a mapping of technical features with the application domains. Thereafter, the applicability of blockchain-based applications is evaluated with relevant regulatory definitions. Finally, we discuss open research challenges and potential future works with the blockchain in the domain of financial systems.

Thi-Thu-Huong Le, Jeunhui Kim, Sangmyeong Lee, Howon Kim

The rapid expansion of blockchain technology, particularly Ethereum, has driven widespread adoption of smart contracts. However, the security of these contracts remains a critical concern due to the increasing frequency and complexity of vulnerabilities. This paper presents a comprehensive approach to detecting vulnerabilities in Ethereum smart contracts using pre-trained Large Language Models (LLMs). We apply transformer-based LLMs, leveraging their ability to understand and analyze Solidity code to identify potential security flaws. Our methodology involves fine-tuning eight distinct pre-trained LLM models on curated datasets varying in types and distributions of vulnerabilities, including multi-class vulnerabilities. The datasets-SB Curate, Benmark Solidity Smart Contract, and ScrawID-were selected to ensure a thorough evaluation of model performance across different vulnerability types. We employed over-sampling techniques to address class imbalances, resulting in more reliable training outcomes. We extensively evaluate these models using precision, recall, accuracy, F1 score, and Receiver Operating Characteristics (ROC) curve metrics. Our results demonstrate that the transformer encoder architecture, with its multi-head attention and feed-forward mechanisms, effectively captures the nuances of smart contract vulnerabilities. The models show promising potential in enhancing the security and reliability of Ethereum smart contracts, offering a robust solution to challenges posed by software vulnerabilities in the blockchain ecosystem.

Lucas Nuzzi, Kyle Waters, Matias Andrade

Much has been hypothesized and feared about 51% attacks on Bitcoin and 34% attacks on Ethereum. However, the costs and benefits associated with perpetrating these attacks remain a mystery. In this paper, we present a novel model to quantify the costs to breach Byzantine fault tolerance thresholds in Bitcoin and Ethereum. We introduce a new metric called Total Cost to Attack (TCA) which encompasses the operational and capital expenditures associated with these attacks. We explore the motivations and expected utility of both profit-driven and ideologically-motivated actors. Our findings suggest that the current state of security in Bitcoin and Ethereum make attacks economically unfeasible and provide empirical evidence of Nash Equilibrium in these networks. This study also challenges the notion that there is a linear relationship between fee revenue and network security, an assumption frequently made when discussing Bitcoin’s declining subsidies. Instead, our findings suggest that block producers engage in speculative behavior ahead of fee cycles, which ends up increasing network security even when fees are low and trending downwards. Our analysis contributes to the discourse around the long term viability of deflationary monetary policies used by Bitcoin and Ethereum and their impact on miner incentives and network security.

Heesang Kim, Dohoon Kim

This study presents a comprehensive framework for optimizing gas fees in decentralized finance (DeFi) pools on the Ethereum blockchain, aimed at enhancing both transaction efficiency and security. The proposed Theory of Gas Fee Minimization strategically optimizes parameters such as the initial token supply, transaction volumes, and gas fees to achieve significant cost reductions and increased transaction throughput. Our computational simulations demonstrate that by addressing factors like market volatility, network congestion, and impact cost factors, the framework effectively minimizes gas fees while reducing the profitability of sandwich attacks, thereby enhancing the security of DeFi ecosystems. The introduction of the Gas Cost Surface provides a novel approach to dynamically managing gas fees, offering insights into the complex interactions between swap amounts and market volatility. This research underscores the importance of rigorous optimization techniques in DeFi protocol design, contributing to the development of more efficient, secure, and user-friendly decentralized financial systems. The findings provide valuable guidance for developers, researchers, and stakeholders seeking to improve the performance and resilience of DeFi platforms, setting new standards for efficiency and security in the blockchain ecosystem.

Zeinab Alipanahloo, Abdelhakim Hafid, Kaiwen Zhang

Maximal Extractable Value (MEV) represents a pivotal challenge within the Ethereum ecosystem; it impacts the fairness, security, and efficiency of both Layer 1 (L1) and Layer 2 (L2) networks. MEV arises when miners or validators manipulate transaction ordering (e.g., front-running) to extract additional value, often at the expense of other network participants. This not only affects user experience by introducing unpredictability and potential financial losses but also threatens the underlying principles of decentralization and trust. Given the growing complexity of blockchain applications, particularly with the increase of Decentralized Finance (DeFi) protocols, it is crucial to address the issue and reduce the impact of MEV. This paper presents a comprehensive survey of MEV mitigation techniques as applied to both Ethereum’s L1 and various L2 solutions. We provide a novel categorization of mitigation strategies. We also describe the challenges, ranging from transaction sequencing and cryptographic methods to reconfiguring decentralized applications (DApps) to reduce front-running opportunities. We investigate their effectiveness, implementation challenges, and impact on network performance. By synthesizing current research, real-world applications, and emerging trends, this paper aims to provide a detailed roadmap for researchers, developers, and policymakers to understand and combat MEV in an evolving blockchain landscape.

Marios Touloupou, Klitos Christodoulou, Marinos Themistocleous

In the evolving domain of blockchain, a critical challenge lies in the performance analysis of blockchains under controlled test conditions. This paper focuses on validating the Blockchain Benchmarking Framework (BBF), developed for the evaluation of blockchain protocols in a controlled environment. The BBF’s robustness and versatility are demonstrated through its application to the official Docker clients of Ripple’s XRP Ledger (XRPL) and Ethereum, deployed in private, local and controlled environments. These deployments are utilized to simulate network dynamics, transaction throughput, and resilience in a variety of scenarios. Our methodology encompasses tests ranging from standard operational conditions to adverse scenarios, including node failures and simulated double-spend attacks. These controlled environments are essential for evaluating the BBF’s efficacy in stress testing blockchain protocols and assessing their stability and robustness. The BBF’s ability to accurately capture and analyze performance characteristics is highlighted, providing insights into the operational mechanics, scalability, and resilience of these blockchain clients. The findings emphasize the BBF’s adaptability and effectiveness in managing different blockchain protocols, reaffirming its potential for broader application in pre-launch testing and analysis of blockchain performance. This study contributes to the understanding of how blockchain clients can be preliminarily assessed before mainnet deployment as well as to validate all the design decisions made by the protocol under different settings and synthetic scenarios.

Hao Sui, Jiale Zhang, Bing Chen, Di Wu · 6 authors

No abstract is available for this record.

Alexandr Kuznetsov, Alex Rusnak, Anton Yezhov, Dzianis Kanonik · 6 authors

Blockchain technology has emerged as a revolutionary tool in ensuring data integrity and security in digital transactions. However, the current approaches to data verification in blockchain systems, particularly in Ethereum, face challenges in terms of efficiency and computational overhead. The traditional use of Merkle Trees and cryptographic hash functions, while effective, leads to significant resource consumption, especially for large datasets. This highlights a gap in existing research: the need for more efficient methods of data verification in blockchain networks. Our study addresses this gap by proposing an innovative aggregation scheme for Zero-Knowledge Proofs within the structure of Merkle Trees. We develop a system that significantly reduces the size of the proof and the computational resources needed for its generation and verification. Our approach represents a paradigm shift in blockchain data verification, balancing security with efficiency. We conducted extensive experimental evaluations using real Ethereum block data to validate the effectiveness of our proposed scheme. The results demonstrate a drastic reduction in proof size and computational requirements compared to traditional methods, making the verification process more efficient and economically viable. Our contribution fills a critical research void, offering a scalable and secure solution for blockchain data verification. The implications of our work are far-reaching, enhancing the overall performance and adaptability of blockchain technology in various applications, from financial transactions to supply chain management.

Dirk G. Baur, Jonathan R. Karlsen

This paper analyses the transition of Ethereum (ETH) from the energy-intensive Proof-of-Work (PoW) to the less energy-intensive Proof-of-Stake (PoS). We analyze returns, volatility, return correlations and volume of ETH, ETC and Bitcoin for all events in the lead-up to the actual change from PoW to PoS also labelled "the merge." The analysis suggests that some investors value the less energy-intensive mining mechanism and invest in ETH. However, since the overall effect is weak, we conclude that despite all the media attention and the stated concerns about the high energy-intensity of Bitcoin and PoW, most investors do not react to the change with an increased investment in Ethereum.

Bin Liu, Tina Prodromou, Sandy Suardi, Caihong Xu

No abstract is available for this record.

Hyung-Eun Choi

No abstract is available for this record.

Alani Kuye, Brian Smocovich

No abstract is available for this record.

C. Vinoth Kumar, Poongundran Selvaprabhu, Nivetha Baska, Vivek Menon U · 7 authors

The Know Your Customer (KYC) process is a fundamental prerequisite for any financial institution’s compliance with the regulatory framework. Blockchain technology has emerged as a revolutionary solution to enhance the effectiveness of the KYC procedure. It ensures that the KYC process is transparent, secure, and immutable, thereby offering a robust solution to combat fraudulent activities. The potential of blockchain technology in revolutionizing the KYC process has been acknowledged globally. Blockchain technology provides a decentralized platform for storing customer data, enabling financial institutions to access the information seamlessly. Using ethereum blockchain technology in KYC procedures can enhance the efficiency of financial institutions, significantly reducing the time and cost associated with the process. This work aims to provide a viable and sustainable solution to the challenges that banks experience in implementing KYC procedures and onboarding new customers. The proposed solution involves the central bank maintaining a comprehensive register of all registered banks while closely monitoring their adherence to the existing regulations governing KYC and customer acquisition.

Cesare Fracassi, M. Anass Khoja, Fabian Schär

The regulatory treatment of cryptoassets depends primarily on three main governance characteristics: transparency, decentralized decision-making, and the effect of governance on token prices. We offer the first comprehensive analysis of the decision-making process of Ethereum, the leading programmable blockchain. We find that its governance is open and transparent, with all Ethereum Improvement Proposals (EIPs) disclosed and discussed in public venues, engaging thousands of people. At the same time, EIPs are predominantly shaped by a core group of influential authors: 10 individuals are responsible for proposing 68% of all implemented Core EIPs. The success of these proposals is significantly associated with key attributes of the proposers, including their social outreach, community engagement, and company affiliation. Furthermore, we observe a notable concentration in client development, where on average 10 people per client implementation are responsible for 80% of all software changes, and identify stablecoin issuers and oracle providers as potential governance centralization vectors. The governance concentration has been slowly decreasing over time, with the Ethereum Foundation still playing an important role. Finally, we find that governance decisions influence crypto prices: Ether price increases 12% leading to the final discussion of Core EIPs.

Mary C. Lacity, Erran Carmel

Abstract This chapter has two purposes. First, we describe how information system (IS) scholars approach privacy research and summarize major findings. IS scholars are concerned with information privacy and have discovered that individuals have serious information privacy concerns. These concerns, however, do not prevent individuals from disclosing personal identifiable information (PII) with centralized platform providers, a phenomenon called the privacy paradox . We highlight four common explanations for the privacy paradox: privacy calculus, privacy fatigue, trust, and lack of choice. Most IS research investigated Web2 applications. Web2 is the foundation for today’s global economy. With Web2, users rely on centralized platforms for online searching, shopping, banking, data storage, social media, and other services. Second, we introduce readers to the new paradigm of Web3. Privacy protection has been the paramount logic behind the grand design of Web3 applications. Web3 is the era of the Internet that is based on decentralized infrastructures and applications, like Bitcoin and Ethereum. Web3 applications enhance information privacy compared to Web2 because individuals can access services without disclosing PII to a central authority. The privacy objective is achieved technically through a combination of digital wallets, cryptography, and distributed ledgers (a.k.a blockchain). While Web3 is still in its early days, education is an important driver of adoption.

Douglas J. Cumming, Niclas Dombrowski, Wolfgang Drobetz, Paul P. Momtaz

Coordination frictions prevent the efficient adoption and governance of blockchain-based platforms. Crypto funds (CFs) create value by smoothing frictions on decentralized digital platforms (DDPs). CF-backed DDPs obtain higher valuations in the primary token market, outperform their peers after issuing tokens, and benefit from token price appreciation around CF investment disclosure in the secondary market. Primary transaction data from the Ethereum ledger shows that the valuations of DDPs with meager adoption and a higher centralization of token ownership benefit more from CF backing. The positive valuation and performance effects for CF-backed DDPs are more pronounced for CFs that are more central in investor networks.

Denys Yu. Lukianchuk

The article analyzes the differences between centralized and decentralized exchanges in the cryptocurrency market. The author notes the impact of bankruptcies of centralized representatives who provided services in the cryptocurrency market on the interaction of users with decentralized finance instruments. The publication considers the key representatives of decentralized finance, their capitalization, available capital, and technological developments. It substantiates the advantages and risks of using decentralized finance instruments and studies the differences between centralized, decentralized, and algorithmic stablecoins. To assess the capitalization of decentralized finance instruments, the asset value indicator TVL (Total Value Locked) is used. TVL represents the amount of assets currently placed in a particular decentralized finance instrument or protocol. The RWA narrative is significant in the crypto space as it demonstrates increased interconnectedness. DeFi, previously isolated from TradFi, has now become an integral part of a more holistic financial ecosystem. Blockchain technology has demonstrated its potential for transformation through real-world use cases. Real-world assets (RWAs) are an attractive option due to the large traditional finance market. While they offer benefits such as portfolio diversification and enhanced returns, it is crucial to mitigate default risk. Platforms like Goldfinch have a proven track record. Tokenizing RWAs can increase market participation and financial inclusivity. The study's results indicate significant development of decentralized finance instruments over the past three years. This is evidenced by the amount of capital invested in these instruments and the number of users, despite the technological and regulatory risks associated with them. The study's conclusions indicate that despite the technological novelty, users are increasingly interested in interacting with decentralized finance instruments. However, users face difficulties in understanding how these instruments work and in gaining experience with these products. The comparative analysis by Saif Ahmed Abdulhakeem and Qiuling Hu titled "CeFi vs. DeFi — Comparing Centralized to Decentralized Finance" systematically contrasts Centralized Finance (CeFi) with Decentralized Finance (DeFi) across legal, economic, security, privacy, and market manipulation dimensions. It aims to provide a structured approach for distinguishing between CeFi and DeFi services, emphasizing DeFi's transparency and user control advantages. However, unresolved issues in decentralized finance, such as regulatory frameworks and risk assessment, necessitate further research. The study also underscores the importance of improving user experience design and overcoming adoption challenges for DeFi. In their academic discourse titled "Powered by Blockchain Technology, DeFi (Decentralized Finance) Strives to Increase Financial Inclusion of the Unbanked by Reshaping the World Financial System," Abdulhakeem and Hu analyze DeFi's potential to enhance financial inclusion for the unbanked. They highlight the pivotal role of blockchain, particularly Ethereum, in enabling DeFi. While acknowledging DeFi's decentralization benefits, the article suggests it as a complement rather than a replacement for traditional finance. It advocates for future research on integrating DeFi with global banking systems and improving user interface and security. Overall, while recognizing DeFi's transformative potential, the article underscores the need for ongoing research to address challenges and integrate DeFi into mainstream finance seamlessly.

Lee Song Haw Colin, P. Mohan, Jonathan Pan, Peter K. K. Loh

Smart contract vulnerabilities have led to substantial disruptions, ranging from the DAO attack to the recent Poolz Finance. While initially, the smart contract vulnerability definition lacked standardization, even with the advancements in Solidity, the potential for deploying malicious contracts to exploit legitimate ones persists. The Abstract syntax tree (AST), opcodes, and control flow graph (CFG) are the intermediate representations for Solidity contracts. In this paper, we propose an integrated and efficient smart contract vulnerability detection algorithm based on Multi-layer perceptron (MLP). We use feature vectors from the Opcodes and CFG for the machine learning (ML) model training. The existing ML-based approaches for analyzing the smart contract code are constrained by the vulnerability detection space, significantly varying Solidity versions, and no unified approach to verify against the ground truth. The primary contributions in this paper are (i) a standardized pre-processing method for smart contract training data, (ii) introducing bugs to create a balanced dataset of flawed files across Solidity versions using AST, and (iii) standardizing vulnerability identification using the Smart Contract Weakness Classification (SWC) registry. The ML models employed for benchmarking the proposed MLP, and a multi-input model combining MLP and Long short-term memory (LSTM) in our study are Random forest (RF), XGBoost (XGB), Support vector machine (SVM). The performance evaluation onreal-timesmart contracts deployed on the Ethereum Blockchain show an accuracy of up to 91% using MLP with the lowest average False Positive Rate (FPR) among all tools and models, measuring at 0.0125.

Alvena Ehsan, Zahid Iqbal, Suhaila Abuowaida, Mohammad Aljaidi · 7 authors

Blockchain has emerged as a groundbreaking security technology, playing a vital role in various industries such as banking, the Internet of Things (IoT), healthcare, education, and voting. However, the widespread adoption of this technology has introduced certain vulnerabilities, particularly in the form of exploitation by malicious entities. While existing research primarily focuses on identifying anomalous actor behavior, there has been limited exploration of precisely identifying hostile actors within the Ethereum network. This study aims to uncover malevolent actors operating on the Ethereum network and categorize attacks based on their actions. To achieve this research goal, a new dataset was constructed by consolidating data on malicious actors involved in illicit Ethereum activities. Key features were extracted from this dataset using advanced feature selection techniques, including Principal Component Analysis (PCA), Information Gain, and Ridge Regression. Machine learning classifiers such as LGBM, XGBoost, Random Forest, Extra Tree, Bagging, and K-Nearest Neighbors were applied to identify and classify malicious actors effectively. The results, achieving an impressive accuracy rate of 98%, underscore the effectiveness of Information Gain when coupled with LGBM and XGBoost. Notably, XGBoost demonstrates efficiency by completing the analysis in a mere 13.72 seconds. In addition to identifying fraudulent activities, this research classifies them into distinct categories, enhancing blockchain security and addressing trust concerns. This study’s outcomes fortify the Ethereum network’s resilience and contribute to the broader discourse on bolstering reliability in blockchain systems.

Giacomo Ibba, Sabrina Aufiero, Silvia Bartolucci, Rumyana Neykova · 7 authors

This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our toolchain combines the power of ANTLR4 and Abstract Syntax Tree (AST) traversal techniques to transform the architecture and interactions within smart contracts into a specialized bipartite graph. This enables advanced network analytics to highlight operational efficiencies within the DApp’s architecture. The bipartite graph generated by the proposed tool comprises two sets of nodes: one representing smart contracts, interfaces, and libraries, and the other including functions, events, and modifiers. Edges in the graph connect functions to smart contracts they interact with, offering a granular view of interdependencies and execution flow within the DApp. This network-centric approach allows researchers and practitioners to apply complex network theory in understanding the robustness, adaptability, and intricacies of decentralized systems. Our work contributes to the enhancement of security in smart contracts by allowing the visualisation of the network, and it provides a deep understanding of the architecture and operational logic within DApps. Given the growing importance of smart contracts in the blockchain ecosystem and the emerging application of complex network theory in technology, our toolchain offers a timely contribution to both academic research and practical applications in the field of blockchain technology.