This study investigates the co-movement patterns of Asia technology stock indices and cryptocurrencies during the COVID-19 pandemic. The analysis examines Bitcoin and Ethereum, Chinaâs Tech index (XA90), and Indiaâs Tech index (NSEIT) from 2017 to 2021, representing both before and during COVID-19. To visually explore the co-movement between these variables, a bi-wavelet method is employed. This approach allows for an examination of how these variables move together over time coherently. There were noticeable changes in the co-movement patterns between technology stock indices and cryptocurrencies during COVID-19 compared to before the pandemic. The duration of co-movements decreased significantly after the emergence of COVID-19. The previous financial crisis had a longer time horizon for joint movement, lasting 256 days. However, during the pre-COVID-19 period, XA90 exhibited a strong co-movement with Bitcoin over this extended period but weakened afterward when COVID-19 emerged. Conversely, NSEIT showed a significant co-movement with both Ethereum and Bitcoin in the initial stages of the pandemic. Before that period, NSEIT had muted price movements along with BTC. These changes in price co-movements suggest shifts in herding behavior due to the pandemic. Notably, cryptocurrency markets have demonstrated faster recovery compared to technology stock markets.
Abstract The cryptocurrency crash on the 5th of September, 2018, resulted in price decreases in 95 of the 100 leading digital currencies. We obtained millisecond data of some of the more prominent cryptocurrenciesâbitcoin, ethereum, ripple, bitcoin cash and eosâand some of the smaller cryptocurrenciesâneo, nem, omg, tezos and liskâthat were most affected in the crash and investigated what caused the digital market to collapse. We find that the behaviour of the more prominent cryptocurrencies and bitcoin, in particular, was the dominant factor behind the crash. We also find that smaller cryptocurrencies followed the behaviour of the larger ones in the crash. Furthermore, our empirical findings show that the trading behaviour of cryptocurrency traders (CTs) did not trigger the digital market crash. We propose the introduction of a single-cryptocurrency circuit breaker most prominent largest cryptocurrencyâbitcoinâthat will halt trading during market disruptions.
As approaching the era of Ethereum 2.0, the already unique and innovative cryptocurrency will witness a game-changing upgrade, and in this context, there is a lively discussion of the Proof of Work (PoW) and Proof of Stake (PoS) consensus mechanism. Moving from a PoW consensus mechanism to a PoS consensus mechanism is one of the most anticipated changes in this update. A close comparison of the two most popular consensus mechanisms, PoW and PoS, provides some strengths and drawbacks to these mechanisms. This comparison then becomes the building block to identifying the reasons behind Ethereum's upgrade to Proof of Stake. With the help of the comparison, this paper identifies a few drawbacks of the PoW consensus mechanism that Ethereum is currently facing. This paper finds that Ethereum's shift to PoS has indeed reduced the drawbacks of the Proof of Work consensus mechanism, mainly in terms of energy consumption, transaction cost, and confirmation speed.
Nur Khairunnisa Noorhizama, Zubaile Abdullah, Shahreen Kasim, Isredza Rahmi A. Hamid ¡ 5 authors
One of the major challenges the university faces is to provide real-time verification of their student's degree certification upon request by other parties. Conventional verification systems are typically costly, time-consuming and bureaucratic against certificate credential misconduct. In addition, the forgery of graduation degree certificates has become more efficient due to easy-to-use scanning, editing, and printing technologies. Therefore, this research proposes verifying Ph.D. certificates using QR codes on the Ethereum blockchain to address certificate verification challenges. Blockchain technology ensures tamper-proof and decentralized management of degree certificates as the certificates stored on the blockchain are replicated across the network. The issuance of certificates requires the use of the issuer's private key, thus preventing forgery. The system was developed using Solidity for the smart contract, PHP, HTML/CSS for the web-based implementation, and MetaMask for blockchain integration. User testing confirmed the successful implementation and functionality of the system. Users can add, update, and delete certificates, generate and scan QR codes, and receive instant verification feedback. The verification system effectively meets all requirements, providing a robust solution for validating Ph.D. certificates. Future research may focus on scalability and adoption, privacy and data protection, user experience, and integration with existing systems. Other researchers can optimize the verification system for widespread adoption and utilization by exploring these areas. This research contributes to securing and efficiently verifying academic certificates using QR codes on the Ethereum blockchain. Ultimately, this work advances the field of certificate verification and promotes trust in academic credentials.
Phuong Duy Huynh, Thisal De Silva, Son Hoang Dau, Xiaodong Li ¡ 6 authors
We investigate in this work a recently emerged type of scam ERC-20 token called Trapdoor, which has cost investors billions of US dollars on Uniswap, the largest decentralised exchange on Ethereum, from 2020 to 2023. In essence, Trapdoor tokens allow users to buy but preventing them from selling by embedding logical bugs and/or owner-only features in their smart contracts. By manually inspecting a number of Trapdoor samples, we established the first systematic classification of Trapdoor tokens and a comprehensive list of techniques that scammers used to embed and conceal malicious codes, accompanied by a detailed analysis of representative scam contracts. In particular, we developed TrapdoorAnalyser, a fine-grained detection tool that generates and crosschecks the error-log of a buy-and-sell test and the list of embedded Trapdoor indicators from a contract-semantic check to reliably identify a Trapdoor token. TrapdoorAnalyser not only outperforms the state-of-the-art commercial tool GoPlus in accuracy, but also provides traces of malicious code with a full explanation, which most of the existing tools lack. Using TrapdoorAnalyser, we constructed the very first dataset of about 30,000 Trapdoor and non-Trapdoor tokens on UniswapV2, which allows us to train several machine learning algorithms that can detect with very high accuracy even Trapdoor tokens with no available Solidity source codes.
BACKGROUND: Blockchain technology has revolutionized the healthcare sector, including emergency medicine, by integrating AI, machine learning, and big data, thereby transforming traditional healthcare practices. The increasing utilization and accumulation of personal health data also raises concerns about security and privacy, particularly within emergency medical settings. METHOD: Our review focused on articles published in databases such as Web of Science, PubMed, and Medline, discussing the revolutionary impact of blockchain technology within the context of the patient journey through the ED. RESULTS: A total of 33 publications met our inclusion criteria. The findings emphasize that blockchain technology primarily finds its applications in data sharing and documentation. The pre-hospital and post-discharge applications stand out as distinctive features compared to other disciplines. Among various platforms, Ethereum and Hyperledger Fabric emerge as the most frequently utilized options, while Proof of Work (PoW) and Proof of Authority (PoA) stand out as the most commonly employed consensus algorithms in this emergency care domain. The ED journey map and two scenarios are presented, exemplifying the most distinctive applications of emergency medicine, and illustrating the potential of blockchain. Challenges such as interoperability, scalability, security, access control, and cost could potentially arise in emergency medical contexts, depending on the specific scenarios. CONCLUSION: Our study examines the ongoing research on blockchain technology, highlighting its current influence and potential future advancements in optimizing emergency medical services. This approach empowers frontline medical professionals to validate their practices and recognize the transformative potential of blockchain in emergency medical care, ultimately benefiting both patients and healthcare providers.
This study explores the stylized facts, volatility clustering, other highly irregular behaviour, and risk measures of cryptocurrenciesâ returns. By analysing bitcoin, ripple, and ethereum daily data we establish evidence of strong dependencies among analysed cryptocurrencies. This paper provides new insights about cryptocurrency behaviour and the main measures of risk and detailed comparative analysis with tech-stocks. Comprehensive research on stylized facts confirmed high risk for both cryptocurrencies and tech-stocks with cryptocurrencies being even riskier. Empirical research findings are useful in developing dependence and risk strategies for investment and hedging purposes, especially during more volatile periods in the markets as there was confirmed existence of volatility clusters when high volatility periods are followed by low volatility periods. Sensitivity analysis and measures of Value-at-Risk (VaR) and Expected Shortfall (ES) show the amount of losses investors can expect in the worst case scenario. Our results confirm the existence of predictability, volatility clustering, and possibilities for arbitrage opportunities. Findings could be beneficial for investors and policymakers as well as for scientific purposes as findings give us a better understanding of the behaviour of cryptocurrencies.
Web 3.0 is the basis on which the proposed metaverse, a seamless virtual world enabled by computers and interconnected devices, hopes to interact with its users, but beyond the high-level project overview of what Web 3.0 applications try to achieve, the implementation is still down to low-level coding details. This article aims to analyze the low-level implementations of key components of Web 3.0 using a variety of frameworks and tools as well as several JVM-based languages. This paper breaks down the low-level implementation of smart contracts and semantic web principles using three frameworks, Corda and Ethereum for smart contracts and Jeda for semantic web, using both Scala and Java as implementing languages all while highlighting differences and similarities between the frameworks used.
Muhammed Siraj, Mohd Izuan Hafez Ninggal, Nur Izura Udzir, Muhammad Daniel Hafiz Abdullah ¡ 5 authors
Sensitive records stored in the cloud such as healthcare records, private conversation and credit card information are targets of hackers and privacy abuse. Current information and record management systems have difficulties achieving privacy protection of such sensitive records in a secure, transparent, decentralized and trustless environment. The Blockchain technology is a nascent and a promising technology that facilitates data sharing and access in a secure, decentralized and trustless environment. The technology enables the use of smart contracts that can be leveraged to complement existing traditional systems to achieve security objectives that were never possible before. In this paper, we propose a framework based on Blockchain technology to enable privacy-preservation in a secured, decentralized, transparent and trustless environment. We name our framework SmartCoAuth. It is based on Ethereum Smart Contract functions as the secure, decentralized, transparent authentication and authorization mechanism in the framework. It also enables tamper-proof auditing of access to the protected records. We analysed how SmartCoAuth could be integrated into a cloud application to provide reliable privacy-preservation among stakeholders of healthcare records stored in the cloud. The proposed framework provides a satisfactory level of data utility and privacy preservation.
Jiachi Chen, Jiang Hu, Xin Xia, David Lo ¡ 7 authors
Decentralized Finance (DeFi) uses blockchain technologies to transform traditional financial activities into\ndecentralized platforms that run without intermediaries and centralized institutions. Smart contracts are\nprograms that run on the blockchain, and by utilizing smart contracts, developers can more easily develop\nDeFi applications. Some key features of smart contracts â self-executed and immutability â ensure the\ntrustworthiness, transparency and efficiency of DeFi applications, and have led to a fast-growing DeFi market.\nHowever, misbehaving developers can add traps or backdoor code snippets to a smart contract, which are\nhard for contract users to discover. We call these code snippets in a DeFi smart contract as âDeFi Contract\nTraps" (DCTs). In this paper, we identify five DeFi contract traps and introduce their behaviors, describe\nhow attackers use them to make unfair profits, and analyse their prevalence in the Ethereum platform. We\npropose a symbolic execution tool, DeFiDefender, to detect such traps and use a manually labeled small-scale\ndataset that consists of 700 smart contracts to evaluate it. Our results show that our tool is not only highly\neffective but also highly efficient. DeFiDefender only needs 0.48s to analyze one DeFi smart contract and\nobtains a high average accuracy (98.17%), precision (99.74%), and recall (89.24%). Among the five DeFi contract\ntraps introduced in this paper, four of them can be detected through contract bytecode without the need for\nsource code. We also apply DeFiDefender to a large-scale dataset that consists of 20,679 real DeFi related\nEthereum smart contracts. We found that 52.13% of these DeFi smart contracts contain at least one contract\ntrap. Although a smart contract that contains contract traps is not necessarily malicious, our finding suggests\nthat DeFi related contracts have many centralized issues in a zero-trust environment and in the absence of a\ntrusted part
We provide a game-theoretic analysis of the problem of front-running attacks. We use it to distinguish attacks from legitimate competition among honest users for having their transactions included earlier in the block. We also use it to introduce an intuitive notion of the severity of front-running attacks. We then study a simple commit-reveal protocol and discuss its properties. This protocol has costs because it requires two messages and imposes a delay. However, we show that it prevents the most severe front-running attacks while preserving legitimate competition between users, guaranteeing that the earliest transaction in a block belongs to the honest user who values it the most. When the protocol does not fully eliminate attacks, it nonetheless benefits honest users because it reduces competition among attackers (and overall expenditure by attackers). This paper was accepted by Joshua Gans, business strategy. Funding: The authors gratefully acknowledge the financial support of the Ethereum Foundation [Grant FY22-0840].
Hamzah M. Marhoon, Noorulden Basil, Alfian Maâarif
Blockchain technology is relatively young but has the potential to disrupt several industries. Since the emergence of Bitcoin, also known as Blockchain 1.0, there has been significant interest in this technology. The introduction of Ethereum, or Blockchain 2.0, has expanded the types of data that can be stored on blockchain networks. The increasing popularity of blockchain technology has given rise to new challenges, such as user privacy and illicit financial activities, but has also facilitated technical advancements. Blockchain technology utilizes cryptographic hashes of user input to record transactions. The public availability of blockchain data presents a unique opportunity for academics to analyze it and gain a better understanding of the challenges in blockchain communications. Researchers have never had access to such an opportunity before. Therefore, it is crucial to highlight the research problems, accomplishments, and potential trends and challenges in blockchain network data analysis and communications. This article aims to examine and summarize the field of blockchain data analysis and communications. The review encompasses the fundamental data types, analytical techniques, architecture, and operations related to blockchain networks. Seven research challenges are addressed: entity recognition, privacy, risk analysis, network visualization, network structure, market impact, and transaction pattern recognition. The latter half of this section discusses future research directions, opportunities, and challenges based on previous research limitations.
Solana has quickly emerged as a popular platform for building decentralized applications (DApps), such as marketplaces for non-fungible tokens (NFTs). A key reason for its success are Solana's low transaction fees and high performance, which is achieved in part due to its stateless programming model. Although the literature features extensive tooling support for smart contract security, current solutions are largely tailored for the Ethereum Virtual Machine. Unfortunately, the very stateless nature of Solana's execution environment introduces novel attack patterns specific to Solana requiring a rethinking for building vulnerability analysis methods. In this paper, we address this gap and propose FuzzDelSol, the first binary-only coverage-guided fuzzing architecture for Solana smart contracts. FuzzDelSol faithfully models runtime specifics such as smart contract interactions. Moreover, since source code is not available for the large majority of Solana contracts, FuzzDelSol operates on the contract's binary code. Hence, due to the lack of semantic information, we carefully extracted low-level program and state information to develop a diverse set of bug oracles covering all major bug classes in Solana. Our extensive evaluation on 6049 smart contracts shows that FuzzDelSol's bug oracles find bugs with a high precision and recall. To the best of our knowledge, this is the largest evaluation of the security landscape on the Solana mainnet.
Ethereum is a major public blockchain. Besides being the second-largest digital currency by market capitalization for its cryptocurrency, the Ether (Î), it is also the foundation of Web3 and decentralized applications, or DApps, that are fuelled by Smart Contracts. At the time of this writing, Ethereum still uses Proof of Work (PoW) consensus algorithm to ensure the integrity of the blockchain and to prevent double spend. PoW requires the participation of miners, who are incentivized to assemble blocks of transactions by being rewarded with cryptocurrency paid by transaction originators and by the blockchain network itself via newly minted Î. Network fees for transaction submissions are called gas, by analogy to the fuel used by cars, and are negotiable. They are also highly volatile and hence it is critical to predict the direction they are heading into, so that one can time transaction submissions, when feasible. There have been several efforts to predict gas prices, including usage of large Mempools, analysis of committed blocks, and more recent ones using Facebook's Prophet model [Taylor, S. J., & Letham, B. (2017). Forecasting at scale. PeerJ Preprints, 5, e3190v2. https://doi.org/10.7287/peerj.preprints.3190v2]. In this study, we introduce an innovative approach that employs the DeepAR [Salinas, D., Flunkert, V., Gasthaus, J., & Januschowski, T. (2020). Deepar: Probabilistic forecasting with autoregressive recurrent networks. International Journal of Forecasting, 36(3), 1181â1191. https://doi.org/10.1016/j.ijforecast.2019.07.001] model, known for its superior forecasting accuracy over conventional methods by virtue of its ability to learn from multiple related time series. This methodology not only offers immediate advantages but also holds promise for ongoing enhancements. We substantiate our claims through empirical testing, utilizing data extracts from the Ethereum blockchain and cryptocurrency price feeds. This document is an extended version of our ICCS 2022 paper on the same topic. In this paper, we dive deeper into the internals of DeepAR forecasting algorithm [Salinas, D., Flunkert, V., Gasthaus, J., & Januschowski, T. (2020). Deepar: Probabilistic forecasting with autoregressive recurrent networks. International Journal of Forecasting, 36(3), 1181â1191. https://doi.org/10.1016/j.ijforecast.2019.07.001], analyse the correlation between the on-chain/off-chain sample data, and describe additional experiments that empirically prove our findings and, finally, perform a comparison of our outputs with those from the Prophet [Taylor, S. J., & Letham, B. (2017). Forecasting at scale. PeerJ Preprints, 5, e3190v2. https://doi.org/10.7287/peerj.preprints.3190v2] model.
Aryan Soltani Mohammadi, Moein Karami, Amir Pasha Motamed, Behnam Bahrak
The properties of tokens within the Ethereum blockchain, such as their current prices, trade volumes, and potential future values, have been the subjects of numerous studies. Employing social networks and graphs, as powerful tools for modeling connections within groups or communities would provide valuable guidance for analyzing these properties. This study mainly focuses on creating and examining networks related to two major decentralized exchanges including Uniswap Version 2 (UniswapV2) and SushiSwap. We have discovered that the distribution of nodes' degrees follows a power law that makes them scale-free networks, in addition, the centrality of tokens in exchange graphs provides valuable insights into their price and significance in cryptocurrency markets. These measures of centrality can be used to detect anomalies in cryptocurrency markets and prices. Notably, these networks exhibit remarkably similar structures, hinting at exciting research opportunities for modeling such networks.
Mehak Maqbool Memon, Manzoor Ahmed Hashmani, Filmann Taput Simpao, Anthony C. Sales ¡ 6 authors
Blockchain's core attributes, including decentralization, transparency, and immutability, have positioned it as a pioneering technology in the realm of financial technology (fintech) and have rendered it highly applicable across diverse industries. The current enterprise ecosystem has faced setbacks primarily due to a lack of trust in the existing infrastructure. This issue can be traced back to the centralized management of healthcare data, making it vulnerable to tampering and fraudulent activities, resulting in financial losses. The existing enterprise ecosystem failed due to the lack of trust in the currently in-place infrastructure. This problem can be attributed to the centralized healthcare data management, which is prone to tampering and fraudulent activities leading to capital loss. The present study relates to a comprehensive survey conducted in timespan from 2018 to 2022 on the implementation of blockchain technology in the healthcare industry, identifying and discussing the key challenges facing the healthcare industry, such as fraud, and scams against healthcare data. It is found that there is an enormous inclination towards the decentralization of patient-centric data. However, a rapid decline is reported due to the privacy and security concerns of the confidential and sensitive data. Moreover, it is noticed that most of the implementations utilized either Ethereum or Hyperledger. Based on the survey's findings, the study proposed a blockchain-based healthcare framework that can address the identified challenges by providing a secure and transparent platform for collecting, storing, and sharing patient health data while prioritizing security and privacy.
Fake news and misinformation are prevalent on the Internet in this day and age. The popularity of social media such as Facebook, Instagram, TikTok has encouraged the people to share news or information over Internet without knowing whether it is a truth or fake information. The outbreak of COVID-19 affected the social activities of all levels of society as people were asked to stay at home to self-quarantine. It indirectly encourages the growth of the social activities online. Even though COVID- 19 is no longer a big threat to the world, people already used to rely on the Internet for the daily activities. Therefore, the trustworthy of the information on the Internet is getting crucial. ETHERST is a blockchain- based PKI that implemented rewarding and punishment mechanism using Ethereum ECR-20 token named PKIToken to improve the trustworthiness of information published by the blockchain nodes. In this paper, we implement an Ethereum-based distributed application (dapp) that allowed the community members to act on trusting and untrusting on information provided by any of the members. With the ETHERST framework as the backend, the ETHERSTWEB is equipped with the rewarding and punishment mechanism to keep the community from misusing the trusting and untrusting action to maintain the trustworthiness of information of a member. With the PKIToken amount level implemented in the backend, it provides an index to the trustworthiness of a member in the community. It has the advantages over the existing rating or review systems that are commonly implemented in many traditional web applications.
Blockchain-based smart contracts are self-running computer programs that can automate a variety of commercial activities. Currently, the majority of these decentralized applications are developed using smart contract platforms like Polkadot, Cardano, and Ethereum. In addition to analyzing current technology developments and prospective future applications, this article provides a historical review of smart contract platforms. The study emphasizes the significance of smart contract platforms for supporting blockchain-based applications and enabling decentralized finance (DeFi). It also looks at the emergence of layer-2 scaling solutions, the introduction of non-fungible tokens (NFTs), and the growing need of interoperability among different smart contract platforms. The article also looks at the potential for multi-chain smart contracts, the effects of quantum computing, the integration of AI and ML technologies with smart contract platforms, and the potential for smart contract platforms to support decentralized autonomous organizations (DAOs). The difficulties of expanding smart contract platforms, the requirement for uniformity in the creation of smart contracts, and the potential for smart contract platforms to revolutionize sectors like healthcare, real estate, and supply chain management are also covered. The paper emphasizes the significance of ongoing innovation and development in smart contract platforms for the expansion of the blockchain ecosystem as it draws to a close.
This paper highlighted the Strengths, Weaknesses, Opportunities, and Threats to blockchain technology in financial services. Blockchain is still an evolving and therefore immature technology; it is hard to predict how successful it would be outside its only proven use domain of cryptocurrencies. History teaches us that radically new technologies take many decades to realize their full potential. Thus it is perfectly possible that blockchain would prove revolutionary in the years to come despite its patchy success so far. What is certain is that businesses should be looking at this technology and understanding it because its underlying ideas are powerful and likely to be influential. Policymakers might support the creation of teaching materials on blockchain technology. Users might be able to avoid frequent blockchain frauds, and businesses might find additional capacity to deploy the technology. Policymakers may use blockchain technology to accomplish their own unique goals. This could help organisations in public, and private sectors decide whether the technology can help solve particular issues. Organisations attempting to integrate blockchain technology with their current systems may find this to be more accessible as a result. Based on blockchain technology, policy- makers could explain current laws and regulations or create new ones. This paper presents a comprehensive overview on blockchain technology in the area of Blockchain funding, Platform finance, financial big data, financial engineering financial technology, Financial innovation, Digital economy. blockchain; FinTech; payment services; deposits and lending; financial services; Bitcoin; SWOT Analysis, Ethereum; Hyperledger, smart contract; digital wallet, Quorum, RippleNet and Stellar Network, Algorand Blockchain and Pundi-X. Blockchain technology is a mode of decentralization, which is the next key disrupting technology and worldwide computing paradigm following the mainframe, perso
Cryptocurrencies are rapidly expanding and becoming vital in digital financial markets. However, the rise in cryptocurrency-related illicit activities has led to significant losses for users. To protect the security of these platforms, it is critical to identify illicit accounts effectively. Current detection methods mainly depend on feature engineering or are inadequate to leverage the complex information within cryptocurrency transaction networks, resulting in suboptimal performance. In this paper, we present DIAM, an effective method for detecting illicit accounts in cryptocurrency transaction networks modeled by directed multi-graphs with attributed edges. DIAM first features an Edge2Seq module that captures intrinsic transaction patterns from parallel edges by considering edge attributes and their directed sequences, to generate effective node representations. Then in DIAM, we design a multigraph Discrepancy (MGD) module with a tailored message passing mechanism to capture the discrepant features between normal and illicit nodes over the multigraph topology, assisted by an attention mechanism. DIAM integrates these techniques for end-to-end training to detect illicit accounts from legitimate ones. Extensive experiments, comparing against 15 existing solutions on 4 large cryptocurrency datasets of Bitcoin and Ethereum, demonstrate that DIAM consistently outperforms others in accurately identifying illicit accounts. For example, on a Bitcoin dataset with 20 million nodes and 203 million edges, DIAM attains an F1 score of 96.55%, markedly surpassing the runner-up's score of 83.92%. The code is available at https://github.com/TommyDzh/DIAM.
Abstract A rising number of educational solutions based on blockchain technology have been designed. Students and other authorities responsible for verifying certificates are very concerned about the authenticity of academic credentials, either because the institutions that issue them no longer exist or because they do not keep adequate records. Blockchain technology has much to offer in education, including its high level of security, improved data access control, low cost, improved accountability, identity authentication, transparency, increased trust, and improved efficiency in managing student records. We proposed a decentralized blockchainâbased secure platform for the storage of academic certificates and student assessments with double encryption. Apart from speeding up the verification process, it will increase the safety of personal education data and assessments of all kinds of misuse. The data would only be accessed using a stakeholder's private key, and storing documents on a blockchain would increase security. We proposed a framework to offer a secure channel for educational resources. We are storing documents over blockchain utilizing an IPFS distributed data server. We give a thorough explanation of the system development, design, and evaluation of the suggested solution in terms of security and cost. Finally, we put the proposed framework to the test by deploying a smart contract prototype on the Ethereum TESTNET network in a Windows environment. The study's findings revealed that the proposed method is effective and feasible.
Felipe Condon, Patricia Franco, JosĂŠ Manuel MartĂnez, Ali M. Eltamaly ¡ 6 authors
The widespread adoption of distributed energy resources (DERs) and the progress made in internet of things (IoT) and cloud computing technologies have enabled and facilitated the development of various smart grid applications and services. This study aims to develop and implement a peer-to-peer (P2P) energy trading platform that allows local energy trading between consumers and prosumers within a microgrid which combines IoT and blockchain technologies. The proposed platform comprises an IoT-cloud home energy management system (HEMS) responsible for gathering and storing energy consumption data and incorporates a blockchain framework that ensures secure and transparent energy trading. The proposed IoTâblockchain architecture utilizes a Chainlink oracle network and a private Ethereum blockchain. Through the use of smart contracts, consumers and prosumers can participate in an open auction to trade energy, while the settlement process involves acquiring external energy data from an API through the oracle network. The performance of the platform is evaluated through a testbed scenario using real-world energy data from a real house in Valparaiso, Chile, while storing those measurements in AWS cloud, validating the feasibility of the proposed architecture in enabling local energy trading. This work contributes to the development of energy management systems by providing a real-world implementation of an IoTâblockchain architecture for local energy trading. The integration of these technologies will allow for a more efficient and secure energy trading system that can benefit prosumers, consumers, and utilities.
Ethereum recently unveiled its upcoming roadmap's \textit{Splurge} phase, highlighting the integration of EIP-\hlhref{https://eips.ethereum.org/EIPS/eip-3074}{4337} as a foundational standard for account abstraction (AA). AA aims to enhance user accessibility and facilitate the expansion of functionalities. Anticipatedly, the deployment of AA is poised to attract a broad spectrum of new users and ignite further innovation in DApps. In this paper, we elucidate the underlying operating mechanisms of this new concept, as well as provide a review of concurrent advancements in accounts, wallets, and standards related to its development. We step further by conducting a preliminary security evaluation to qualitatively assess the extent of security enhancements achieved through AA updates.