Md Al Amin, Hemanth Tummala, Seshamalini Mohan, Indrajit Ray
This paper addresses the critical challenge of ensuring healthcare policy compliance in the context of Electronic Health Records (EHRs). Despite stringent regulations like HIPAA, significant gaps in policy compliance often remain undetected until a data breach occurs. To bridge this gap, we propose a novel blockchain-powered, smart contract-based access control model. This model is specifically designed to enforce patient-provider agreements (PPAs) and other relevant policies, thereby ensuring both policy compliance and provenance. Our approach integrates components of informed consent into PPAs, employing blockchain smart contracts to automate and secure policy enforcement. The authorization module utilizes these contracts to make informed access decisions, recording all actions in a transparent, immutable blockchain ledger. This system not only ensures that policies are rigorously applied but also maintains a verifiable record of all actions taken, thus facilitating an easy audit and proving compliance. We implement this model in a private Ethereum blockchain setup, focusing on maintaining the integrity and lineage of policies and ensuring that audit trails are accurately and securely recorded. The Proof of Compliance (PoC) consensus mechanism enables decentralized, independent auditor nodes to verify compliance status based on the audit trails recorded. Experimental evaluation demonstrates the effectiveness of the proposed model in a simulated healthcare environment. The results show that our approach not only strengthens policy compliance and provenance but also enhances the transparency and accountability of the entire process. In summary, this paper presents a comprehensive, blockchain-based solution to a longstanding problem in healthcare data management, offering a robust framework for ensuring policy compliance and provenance through smart contracts and blockchain technology.
We present a comprehensive analysis of the implications of artificial latency in the Proposer-Builder Separation framework on the Ethereum network. Focusing on the MEV-Boost auction system, we analyze how strategic latency manipulation affects Maximum Extractable Value yields and network integrity. Our findings reveal both increased profitability for node operators and significant systemic challenges, including heightened network inefficiencies and centralization risks. We empirically validates these insights with a pilot that Chorus One has been operating on Ethereum mainnet. We demonstrate the nuanced effects of latency on bid selection and validator dynamics. Ultimately, this research underscores the need for balanced strategies that optimize Maximum Extractable Value capture while preserving the Ethereum network's decentralization ethos.
Decentralized Finance (DeFi), propelled by Blockchain technology, has revolutionized traditional financial systems, improving transparency, reducing costs, and fostering financial inclusion. However, transaction activities i n these systems fluctuate significantly and the throughput can be effected. To address this issue, we propose a Dynamic Mining Interval (DMI) mechanism that adjusts mining intervals in response to block size and trading volume to enhance the transaction throughput of Blockchain platforms. Besides, in the context of public Blockchains such as Bitcoin, Ethereum, and Litecoin, a shift towards transaction fees dominance over coin-based rewards is projected in near future. As a result, the ecosystem continues to face threats from deviant mining activities such as Undercutting Attacks, Selfish Mining, and Pool Hopping, among others. In recent years, Dynamic Transaction Storage (DTS) strategies were proposed to allocate transactions dynamically based on fees thereby stabilizing block incentives. However, DTS’ utilization of Merkle tree leaf nodes can reduce system throughput. To alleviate this problem, in this paper, we propose an approach for combining DMI and DTS. Besides, we also discuss the DMI selection mechanism for adjusting mining intervals based on various factors.
Blockchain is a digital transaction technology adopting the peer-to-peer concept. The implementation of blockchain on Internet of Things (IoT) aims to secure the possibility of potential attacks against devices or transactions taking place on the IoT system. At practical levels, blockchain uses smart contracts to automate programs according to predetermined terms and conditions. This research is aimed at implementing an ethereum-based smart home Smart Contract by modifying the device components, dashboards, and consensus used in Xu et al.’s research. The consensus modification was performed by using Proof of Authority (PoA) aiming to improve block verification performance on the system. The Denial of Service (DoS) attacks and Single Point of Failure (SpoF) vulnerability were performed to evaluate the proposed system. The evaluation was performed with TCP Flood Attack, with request packets of 81,519 packets on port 8545 and ICMP Floods by sending 11,481,703 PING packets. The attack caused some application services running on the Ethereum Node 3 to stop, but did not stop the geth application. As for the Single Point of Failure (SPoF) vulnerability, the Ethereum network is still running and there were no obstacles in the mining process or block verification.
Non-Fungible tokens (NFTs) are a special type of token that has a unique ID and can be held or traded as a crypto asset by Ethereum users. For the current NFT standard, NFT owner’s account address is stored in plaintext by blockchain. Once a user’s real identity and account address is known, his NFT holdings are also exposed. In practice, one may consider the NFT holdings to be private. In this paper, we propose the first solution to achieve anonymous NFT on Ethereum in a trustless environment. The owner address of an NFT will be hidden while the NFT can be continuously traded without revealing the addresses of buyers and sellers. Furthermore, we prove that our scheme preserves privacy against all entities in the trading system and builds an implementation to evaluate its performance. The result shows our solution is suitable for application.
Mohammad Masoud, Yousef Jaradat, Ahmad Manasrah, Mohammad Alia · 6 authors
This work carried out a measurement study of the Ethereum Peer-to-Peer (P2P) network to gain a better understanding of the underlying nodes. Ethereum was applied because it pioneered distributed applications, smart contracts, and Web3. Moreover, its application layer language “Solidity” is widely used in smart contracts across different public and private blockchains. To this end, we wrote a new Ethereum client based on Geth to collect Ethereum node information. Moreover, various web scrapers have been written to collect nodes’ historical data from the Internet Archive and the Wayback Machine project. The collected data has been compared with two other services that harvest the number of Ethereum nodes. Our method has collected more than 30% more than the other services. The data trained a neural network model regarding time series to predict the number of online nodes in the future. Our findings show that there are less than 20% of the same nodes daily, indicating that most nodes in the network change frequently. It poses a question of the stability of the network. Furthermore, historical data shows that the top ten countries with Ethereum clients have not changed since 2016. The popular operating system of the underlying nodes has shifted from Windows to Linux over time, increasing node security. The results have also shown that the number of Middle East and North Africa (MENA) Ethereum nodes is neglected compared with nodes recorded from other regions. It opens the door for developing new mechanisms to encourage users from these regions to contribute to this technology. Finally, the model has been trained and demonstrated an accuracy of 92% in predicting the future number of nodes in the Ethereum network.
To empower smart contracts with the promising capabilities of cryptography, Ethereum officially introduced a set of cryptographic APIs that facilitate basic cryptographic operations within smart contracts, such as elliptic curve operations. However, since developers are not necessarily cryptography experts, requiring them to directly interact with these basic APIs has caused real-world security issues and potential usability challenges. To guide future research and solutions to these challenges, we conduct the first empirical study on Ethereum cryptographic practices. Through the analysis of 91,484,856 Ethereum transactions, 500 crypto-related contracts, and 483 StackExchange posts, we provide the first in-depth look at cryptographic tasks developers need to accomplish and identify five categories of obstacles they encounter. Furthermore, we conduct an online survey with 78 smart contract practitioners to explore their perspectives on these obstacles and elicit the underlying reasons. We find that more than half of practitioners face more challenges in cryptographic tasks compared to general business logic in smart contracts. Their feedback highlights the gap between low-level cryptographic APIs and high-level tasks they need to accomplish, emphasizing the need for improved cryptographic APIs, task-based templates, and effective assistance tools. Based on these findings, we provide practical implications for further improvements and outline future research directions.
This study explores the integration of Fast Healthcare Interoperability Resources (FHIR) standards in a system designed for secure and efficient management of Personal Health Records (PHRs). PHRs are crucial for patients to have control over their healthcare information and make informed decisions. Ensuring the security of this sensitive data is vital, and blockchain technology offers robust protection. However, the high cost of storing PHRs on the blockchain has led us to investigate the use of the Interplanetary File System (IPFS) alongside blockchain. Our proposed system comprises a PHR Decentralized Application (DAPPS), IPFS, Metamask, and the Ethereum Blockchain. Users input their PHR data through the DAPPS, which is stored in IPFS, and its location is registered on the Ethereum Blockchain via Metamask. Comprehensive testing validates the system's performance, with success across all test cases, confirming the feasibility of utilizing the Interplanetary File System and Ethereum Blockchain for secure PHR management while adhering to FHIR standards, fostering interoperability in healthcare data exchange.
Abstract. Due to the transparent nature of blockchain, all transaction information and smart contract code is recorded on the public blockchain. It is easy for existing static analysis tools to analyze and exploit vulnerabilities in smart contract code. To mitigate this risk, we propose HermHD, an automated security enhancement tool that protects smart contracts on the Ethereum network. HermHD employs six obfuscation patterns that can rewrite the bytecode of a smart contract without affecting its functionality. By applying these obfuscation techniques, we aim to prevent reverse static analysis tools from cracking the contract and thereby enhance the security of smart contracts. To validate the effectiveness of HermHD, we conducted experiments on 121 smart contracts from a public dataset. 54The evaluation results demonstrate that all the protected smart contracts are resistant to two popular reverse engineering tools, and the additional gas cost incurred is minimal.
A lo largo de más de una década, el mercado de criptoactivos ha logrado atraer a una amplia base de usuarios a nivel mundial. Con el crecimiento de este ecosistema digital, han surgido especulaciones cada vez más frecuentes acerca del considerable consumo energético asociado y su correlación con el daño ambiental. En este contexto, planteamos la siguiente interrogante: ¿cómo se muestra el consumo energético de las principales criptomonedas en el cambio climático? Con el fin de abordar esta interrogante, se estableció como objetivo primordial examinar el consumo energético derivado del uso de estos instrumentos. Para este propósito, se llevó a cabo una revisión bibliográfica descriptiva basada en artículos científicos e informes de centros de estudios especializados que analizaron su influencia en la huella de carbono. Por último, examinamos cómo la minería de Bitcoin supera en consumo energético a naciones enteras, como Finlandia o Bélgica, mientras que Ethereum ha logrado mitigar sus emisiones de gases de efecto invernadero mediante la transición al protocolo de consenso “Proof of Stake” (prueba de participación), evidenciando así un enfoque más sostenible para el desarrollo.
With the popularity of Non-Fungible Tokens (NFTs), which has now become a financial market that has attracted extensive attention worldwide. A large number of investors and creators are flocking to this emerging market in search of investment opportunities. Nowadays, many studies have analysed this phenomenon from an economic perspective. However, we know little about the players and ecosystem characteristics of this market. To fill this knowledge gap, we first provide a processed large-scale dataset of the Ethereum blockchain-based NFT market, containing more than 80 million NFT transaction records from January 2018 to April 2022. Second, we constructed the NFT creator graph (NCG) and NFT holder graph (THG) to delve into the characteristics of the NFT market. Further, we analyse the market preferences and trends using statistical methods to reveal the development trends of the NFT market. Finally, we focus on predicting the transaction volume of the NFT market and analyse the influence factors. This study provides data support for participants and researchers to explore the NFT market, while our analysis promotes a deeper understanding of the NFT market among the public.
Ahmad Anwar Zainuddin, Hariz Syahmi Hairo Rose Sidi, Muhammad Dini Aulia Shamsudin, Khaleel Ahmad · 8 authors
In recent times, attention has surged towards entities with the potential to revolutionize various sectors. The integration of Internet of Things (IoT) and blockchain technologies, known as IoT-blockchain, offers numerous advantages, including heightened security, privacy, traceability, transparency, and reduced costs. This abstract delves into the taxonomy and prominent platforms of blockchain applications for IoT in networking systems, exploring recent advancements, obstacles, and future research avenues. IoT blockchain's crucial aspect lies in establishing decentralized networks, enabling secure collaboration and data interchange among diverse devices without a central governing entity. Platforms like Ethereum, Hyperledger, and IOTA facilitate the creation and management of these networks. Recent developments focus on enhancing security, scalability, and efficiency through novel consensus mechanisms and cryptographic techniques. Challenges persist, including the need for improved interoperability, integration with existing systems, efficient governance, regulatory structures, and the identification of use cases and business models for widespread adoption. The examination of successful governance, regulatory frameworks, and potential adoption catalysts completes the discourse on IoT blockchain technology.
In recent years, there has been a growing interest in real estate investments that utilize blockchain technology. Traditional real estate investments usually involve third-party intermediaries for verifying and recording real estate informal transactions. This paper proposes a blockchain-based real estate investment model and presents a detailed description of the real estate register authentication aspect of the model. The model uses blockchain technology to create tamper-evident records of real estate transactions and provide secure authentication and verification of real estate informal transactions. Meanwhile, each real estate transaction is recorded in a block, and all transaction records are kept on the blockchain. This means that inventors can access these transaction records and verify their authenticity and validity. The system can also use smart contracts to automate the process of real estate transactions, which further improves transaction efficiency and reduces costs. Further, the model's timestamp and authentication mechanism can eliminate third-party intermediaries and ensure the authenticity and validity of real estate transactions through distributed ledgers and verification mechanisms. Overall, blockchain-based real estate systems offer advantages of security, transparency, efficiency, and cost reduction. With ongoing blockchain advancements, these systems are expected to play a crucial role in future real estate investment transactions.
In this paper, to estimate the risk of economic loss incurred by both parties in production order transactions, we propose a scheme that enables escrow and confirmation of the results without relying on a third party. In such transactions, both parties risk incurring economic losses if the other party behaves dishonestly. Generally, the risk can be reduced with an escrow service provided by a trusted third party. However, there is a risk of fraud by the third party; in some cases, the third party may not be available for the buyer or seller. Several existing schemes utilize fair exchange and blockchain to disburse the deposited payment upon the delivery of specific data. However, in production order transactions, some cases cannot be handled only by completion of delivery, such as disputes that arise when the data does not meet the quality expected by the buyer. In such cases, before the transaction starts, a party would confirm the counterparty’s behavior in past transactions to estimate the risk of a dispute occurring. In this paper, we propose a scheme that records the history of past transaction processes while utilizing blockchain-based escrow and allows future counterparties to confirm the history as a reference for estimating risk. By the opportunity loss that a history of dishonest behavior causes and applying blockchain-based escrow, the scheme motivates sellers and buyers to behave in good faith. We implemented a prototype system on top of Ethereum and verified its feasibility. By expanding the scope of transactions, we expect that it will be possible to determine whether transactions between individuals over the Internet are feasible without relying on a specific escrow service.
This research paper discusses virtual currency and the blockchain technology that underpins it. Virtual money, frequently referred to cryptocurrency, is a digital method of payment that is not regulated by traditional financial institutions. It enables individuals to perform peer-to-peer transactions in a secure and efficient manner by using encrypted digital records. Cryptocurrencies like Bitcoin and Ethereum have garnered popularity due to their promise to transform financial institutions by enabling international and decentralized payments. Blockchain technology facilitates the operation of virtual currency. A blockchain is an immutable and decentralized digital ledger which keeps track of every single transaction in an easily accessible and tamper-resistant manner. Each transaction is organized into a block and linked to the one before it, forming a chain of blocks. This paper explores virtual currency and its foundation, blockchain technology. Cryptocurrency, a digital payment method, enables secure peer-to-peer transactions without traditional financial oversight. Prominent examples like Bitcoin and Ethereum offer potential for global and decentralized payments. Blockchain, an immutable digital ledger, supports virtual currency, recording tamper-resistant transactions in linked blocks.
In this paper, we conducted an empirical investigation of the realized volatility of cryptocurrencies using an econometric approach. This work’s two main characteristics are: (i) the realized volatility to be forecast filters jumps, and (ii) the benefit of using various historical/implied volatility indices from brokers as exogenous variables was explicitly considered. We feature a jump-robust extension of the REGARCH-MIDAS-X model incorporating realized beta GARCH processes and MIDAS filters with monthly, daily, and hourly components. First, we estimated six jump-robust estimators of realized volatility for Bitcoin and Ethereum that were retained as the dependent variable. Second, we inserted ten Bitcoin and Ethereum volatility indices gathered from various exchanges as an exogenous variable, each at a time. Third, we explored their forecasting ability based on the MSE and QLIKE statistics. Our sample spanned the period from May 2018 to January 2023. The main result featured the best predictors among the volatility indices for Bitcoin and Ethereum derived from 30-day implied volatility. The significance of the findings could mostly be attributable to the ability of our new model to incorporate financial and technological variables directly into the specification of the Bitcoin and Ethereum volatility dynamics.
Ethereum introduced Transaction Access Lists (TALs) in 2020 to optimize gas costs during transaction execution. In this work, we present a comprehensive analysis of TALs in Ethereum, focusing on adoption, quality, and gas savings. Analyzing a full month of mainnet data with 31,954,474 transactions, we found that only 1.46% of transactions included a TAL, even though 42.6% of transactions would have benefited from it. On average, access lists can save around 0.29% of gas costs, equivalent to approximately 3,450 ETH (roughly US$ 5 Mio) per year. However, 19.6% of TALs included by transactions contained imperfections, causing almost 11.8% of transactions to pay more gas with TAL than without. We find that these inaccuracies are caused by the unknown state at the time of the TAL computation as well as imperfect TAL computations provided by all major Ethereum clients. We thus compare the gas savings when calculating the TAL at the beginning of the block vs. calculating it on the correct state, to find that the unknown state is a major source of TAL inaccuracies. Finally, we implement an ideal TAL computation for the Erigon client to highlight the cost of these flawed implementations.
A growing number of products use layer 2 solutions to expand the capabilities of primary blockchains like Ethereum, where computation is off-loaded from the root chain, and the results are published to it in bulk. Those include optimistic and zero-knowledge rollups, information oracles, and app-specific chains. This work presents an analysis of layer 2 blockchain strategies determining the optimal times for publishing transactions on the root chain. There is a trade-off between waiting for a better layer 1 gas price and the urgency to finalize layer 2 transactions. We present a model for the problem that captures this trade-off, generalizing previous works, and we analyze the properties of optimal publishing strategies. We show that such optimal strategies hold a computable simple form for a large class of cost functions.
Despite the growth in the number of decentralized applications (DApps) supported by the Ethereum blockchain, we can observe the narrow scope of these DApps, concentrated within the fintech and games areas. A cause for the lack of range of DApps lies in the fees for transactions sent to backing smart contracts. While consistent steps have been made to overcome cost efficiency problems, introducing rollups as a secondary layer solution, intertwined accessibility and security drawbacks still persist. Measures addressing some of these issues like account abstraction were independently proposed. These solutions bring changes in transaction handling that often exceed the scope of smart contracts, where the core of DApp logic resides. Integrating such measures often requires the use of new frameworks and understanding the changes in the transaction flow, which can prove challenging to a DApp developer. A question is whether the current landscape of solutions proposed for increasing usability is capable of producing a consistent impact on DApp scope trends. In this position paper we try to answer this, raising also the matter of impact on DApp engineering.
Blockchain technologies have gained widespread use in security-sensitive applications due to their robust data protection. However, as blockchains are increasingly integrated into critical data management systems, they have become attractive targets for attackers. Among the various attacks on blockchain systems, distributed denial of service (DDoS) attacks are one of the most significant and potentially devastating. These attacks render the systems incapable of processing transactions, causing the blockchain to come to a halt. To address the challenge of detecting DDoS attacks on blockchains, existing visualization schemes have been developed. However, these schemes often fail to provide early DDoS detection since they typically display only past and current system status. In this paper, we present a novel visualization scheme that not only portrays past and current values but also forecasts future expected system statuses. We achieve these future predictions by utilizing polynomial regression with blockchain data. Additionally, we offer an alternative DDoS detection method employing statistical analysis, specifically the coefficient of determination, to enhance accuracy. Through our experiments, we demonstrate that our proposed scheme excels at predicting future blockchain statuses and anticipating DDoS attacks with minimal error. Our work empowers system managers of blockchain-based applications to identify and mitigate DDoS attacks at an earlier stage.
A decentralised distributed ledger system called Blockchain Technology (BCT) enables safe, open, and impenetrable transactions without the need for a central authority. The technology was initially created for the Bitcoin cryptocurrency, but it has subsequently been applied to other areas such as voting procedures, supply chain management, and digital identity management. The technology is increasingly becoming accepted in the academic setting for a variety of purposes, including the creation and storage of academic records. There are numerous platforms accessible for this usage, though. When numerous decision-makers are engaged in the selection process, picking an appropriate platform can be a contentious affair. For decision makers, selecting among a wide range of acceptable options might be difficult. It is possible to overcome these difficulties by using Multi-criteria Decision-Making (MCDM) techniques. When there are numerous elements to take into account, one technique for making judgments is MCDM. The process entails assessing multiple options according to pre-established standards in order to identify the optimal selection. In essence, when there are several variables to consider, MCDM assists in selecting the option. The Fuzzy Analytic Hierarchy Process (FAHP) is one of the various MCDMs which this paper uses to choose the best BCT platform for academic records based on three choices (IBM, Ethereum, and Hyperledger Fabric) and five factors (cost, degree of acceptance, simplicity of use, data security, and level of customization). The analysis's findings indicate that data security is the most crucial factor, with a weight of 0.645, and that IBM is the best BCT platform, with a value of 0.448. By comparing the FAHP results to those of AHP, IBM's suitability as a platform was confirmed.
This paper investigates the fundamental trade-offs between block safety, confirmation latency, and transaction throughput of proof-of-work (PoW) longest-chain fork-choice protocols, also known as PoW Nakamoto consensus. New upper and lower bounds are derived for the probability of block safety violations as a function of honest and adversarial mining rates, a block propagation delay limit, and confirmation latency measured in both time and block depth. The results include the first non-trivial closed-form finite-latency bound applicable across all delays and mining rates up to the ultimate fault tolerance. Notably, the gap between these upper and lower bounds is narrower than previously established bounds for a wide range of parameters relevant to Bitcoin and its derivatives, including Litecoin and Dogecoin, as well as Ethereum Classic. Additionally, the study uncovers a fundamental trade-off between transaction throughput and confirmation latency, ultimately determined by the desired fault tolerance and the rate at which block propagation delay increases with block size.
I study the price dynamics of non-fungible tokens (NFTs) and propose a deep learning framework for dynamic valuation of NFTs. I use data from the Ethereum blockchain and OpenSea to train a deep learning model on historical trades, market trends, and traits/rarity features of Bored Ape Yacht Club NFTs. After hyperparameter tuning, the model is able to predict the price of NFTs with high accuracy. I propose an application framework for this model using zero-knowledge machine learning (zkML) and discuss its potential use cases in the context of decentralized finance (DeFi) applications.
Carlos A. Estrada, S. Naranjo, Veronica J. Toasa, Sang Guun Yoo
In the context of today's digital era, blockchain technology has established itself as one of the transformative innovations that pushes the boundaries of data management and security. Given this situation, the present work carries out a systematic literature review of this technology. It examines three essential aspects of the blockchain world. First of all, the various fields of application of this technology are analyzed, which go beyond the field of cryptocurrencies and extend to other industries such as the internet of things, supply chains, health, identity management, business, and much more. Secondly, the most used platforms for the development of blockchain applications are studied, such as Ethereum, Hyperledger Fabric, Solana among others; each platform has its particular characteristics, compatible programming languages and recommended application areas. Finally, an analysis of the consensus protocols is carried out, such as Proof of Work, Proof of Stake, Proof of Authority, RAFT, among others. This literature review provides a comprehensive overview of blockchain, shedding light on its versatility, challenges, and transformative potential in a variety of industries. It offers a solid foundation for those interested in exploring and taking advantage of the blockchain revolution in the 21st century.