A vaccine passport serves as documentary proof, providing passport holders with greater freedom while roaming around during pandemics. It confirms vaccination against certain infectious diseases like COVID-19, Ebola, and flu. The key challenges faced by the digital vaccine passport system include passport forgery, unauthorized data access, and inaccurate information input by vaccination centers. Privacy concerns also need to be addressed to ensure that the user's personal identification information (PII) is not compromised. Additionally, it is necessary to track vaccine vials or doses to verify their authenticity, prevent misuse and illegal sales, as well as to restrict the illicit distribution of vaccines. To address these challenges, we propose a Blockchain-Enabled Secure Vaccine Passport System, leveraging the power of smart contracts. Our solution integrates off-chain and on-chain cryptographic computations, facilitating secure communication among various entities. We have utilized the InterPlanetary File System (IPFS) to store encrypted vaccine passports of citizens securely. Our prototype is built on the Ethereum platform, with smart contracts deployed on the Sepolia Test network, allowing for performance evaluation and validation of the system's effectiveness. By combining IPFS as a distributed data storage platform and Ethereum as a blockchain platform, our solution paves the way for secure, efficient, and globally interoperable vaccine passport management, supporting comprehensive vaccination initiatives worldwide.
Олег Гарасимчук, Юрій Наконечний, Тарас Луковський, Роман Андріїв · 5 authors
Постійне збільшення обсягів даних породжує проблеми, пов'язані з вибором ефективних методів та засобів зберігання, а також забезпеченням захисту цих даних від несанкціонованого доступу. У статті детально розглянуто критичну тему збереження та захисту важливої інформації в умовах зростання обсягів даних і численності кібератак. Необхідність надійного збереження і захисту даних наростає, особливо у контексті підвищеної загрози з боку зловмисників. Висвітлюється, як блокчейн-технології, особливо на базі платформи Ethereum, можуть вирішити проблеми надійного збереження і безпеки даних. Ethereum пропонує альтернативу традиційній клієнт-серверній моделі, децентралізуючи зберігання даних за допомогою розподіленої мережі вузлів. Ця технологія значно підвищує безпеку, ускладнюючи несанкціонований доступ до інформації, оскільки для злому приватного ключа потрібні значні обчислювальні ресурси. Смарт-контракти на Ethereum дозволяють створювати застосунки, які виконуються точно відповідно до заздалегідь визначених умов, без можливості втручання третіх осіб. Це особливо важливо для месенджерів, де конфіденційність і доступність даних мають принципове значення. Вартість транзакцій в блокчейні, хоча й висока, компенсується високою надійністю та безпекою зберігання даних. Застосована методологія підтверджує, що використання публічного (децентралізованого) сховища даних є безпечним, оскільки зламати приватний ключ Ethereum практично неможливо.
Sri Sai Durga Mani Vasireddy, Supriya Yalagala, Jayasri Sikha, Rani Vullaganti · 7 authors
The primary objective of this project is to develop a robust and secure system that uses blockchain technology as well as Ethereum and IoT sensors to create a transparent and automated irrigation management solution for farmers. The key components of this innovative system include IoT sensors for real-time data collection, smart contracts on the Ethereum blockchain for transparent and immutable record keeping, and a user-friendly interface for farmers to monitor and control their irrigation systems remotely. The blockchain will provide data security to avoid the problem of data manipulation; because the IoT components will produce large volumes of data, the data must be securely maintained.
Azreen Shafieqah Asri, Faizatul Fitri Boestamam, Haslizaidi Zakaria, Mohammad Amir Alam Rahim Omar · 6 authors
With the rapid expansion of the Industrial Internet of Things (IIoT), integrating devices, machines, and systems to optimize operations and enable data-driven decision-making, ensuring robust security measures is essential. While blockchain has shown the potential to upgrade traditional authentication methods in IIoT environments, vulnerabilities persist. This paper introduces two innovative methods to enhance blockchain-based authentication in IIoT: first, integrating AI-driven anomaly and threat detection into the blockchain authentication scheme; second, implementing Ethereum smart contracts for enhanced authentication with a two-factor authentication (2FA) system and GFE algorithms. By combining AI for anomaly detection with decentralized smart contracts and blockchain-based 2FA, and leveraging GFE algorithms to enhance blockchain capabilities, the proposed scheme aims to significantly fortify security measures. This integration offers a resilient defense against evolving threats, ensuring transparency, adaptability, and heightened security in IIoT applications.
Frederico Baptista, Marina Dehez-Clementi, Jonathan Detchart
The integration of Unmanned Aircraft Systems (UASs) into the current airspace poses significant challenges in terms of safety, security, and operability. As an example, in 2019, the European Union defined a set of rules to support the digitalization of UAS traffic management (UTM) systems and services, namely the U-Space regulations. Current propositions opted for a centralized and private model, concentrated around governmental authorities (e.g., AlphaTango provides the Registration service and depends on the French government). In this paper, we advocate in favor of a more decentralized and transparent model in order to improve safety, security, operability among UTM stakeholders, and legal compliance. As such, we propose DFly, a publicly auditable and privacy-preserving UAS traffic management system on Blockchain, with two initial services: Registration and Flight Authorization. We demonstrate that the use of a blockchain guarantees the public auditability of the two services and corresponding service providers’ actions. In addition, it facilitates the comprehensive and distributed monitoring of airspace occupation and the integration of additional functionalities (e.g., the creation of a live UAS tracker). The combination with zero-knowledge proofs enables the deployment of an automated, distributed, transparent, and privacy-preserving Flight Authorization service, performed on-chain thanks to the blockchain logic. In addition to its construction, this paper details the instantiation of the proposed UTM system with the Ethereum Sepolia’s testnet and the Groth16 ZK-SNARK protocol. On-chain (gas cost) and off-chain (execution time) performance analyses confirm that the proposed solution is a viable and efficient alternative in the spirit of digitalization and offers additional security guarantees.
Yustynn Panicker, Ezekiel Soremekun, Sudipta Chattopadhyay, Sumei Sun
Smart contracts are increasingly used in critical use cases (e.g., financial transactions). Thus, it is pertinent to ensure that end-users understand the transfer risks in smart contracts. To address this, we investigate end-user comprehension of risks in the most popular Ethereum smart contract (i.e., USD Tether (USDT)) and their prevalence in the top ERC-20 smart contracts. We focus on five transfer risks with severe impact on transfer outcomes and user objectives, including users being blacklisted, contract being paused, and contract being arbitrarily upgraded. Firstly, we conducted a user study investigating end-user comprehension of smart contract transfer risks with 110 participants and USDT/MetaMask. Secondly, we performed manual and automated source code analysis of the next top (78) ERC-20 smart contracts (after USDT) to identify the prevalence of these risks. Results show that end-users do not comprehend real risks: most (up to 71.8% of) users believe contract upgrade and blacklisting are highly severe/surprising. More importantly, twice as many users find it easier to discover successful outcomes than risky outcomes using the USDT/MetaMask UI flow. These results hold regardless of the self-rated programming and Web3 proficiency of participants. Furthermore, our source code analysis demonstrates that the examined risks are prevalent in up to 19.2% of the top ERC-20 contracts. Additionally, we discovered (three) other risks with up to 25.6% prevalence in these contracts. This study informs the need to provide explainable smart contracts, understandable UI and relevant information for risky outcomes.
In traditional blockchains under the Proof-of-Work consensus algorithm, such as Bitcoin and the initial Ethereum, temporal fluctuations of block generation time follow an exponential distribution.Since September 15, 2022, Ethereum has changed its consensus algorithm to Proof of Stake to become Ethereum 2, which qualitatively changes the nature of the fluctuations.Careful analysis reveals that block creation time of Ethereum 2 also slightly fluctuates around 12 seconds, but the origin of this fluctuations is not well understood theoretically.This research contributes to the understanding of this fluctuations, especially focusing on Ethereum 2, by considering a mathematical model on broadcast communications between validator nodes theoretically.As a result, we find that this fluctuation directly comes from the time that it takes for the broadcast communications between validator nodes and it follows a Gumbel distribution.We also show some results of real data analysis which supports our theoretical findings.As an application of the theoretical findings, furthermore, we formulat a blockchain trilemma inequality to explain trade-offs between transaction processing performance, security, and decentralization.
In addressing the significant challenges caused by the expansion of data storage needs in blockchain systems, this paper explores the integration of the InterPlanetary File System (IPFS) with Substrate-based blockchain. By leveraging IPFS for off-chain storage and Substrate for on-chain operations, this system addresses the key challenges such as bloated storage, inefficiency, and accessibility while preserving data distribution and privacy. Through a comparative analysis with an Ethereum-based system, this study reveals significant advantages of the Substrate-IPFS solution. There is a significant reduction in data storage size and faster block confirmation times, leading to potentially lower transaction costs. The proposed approach enhances data privacy through the use of the Blake2 hashing algorithm. Overall, this research showcases the potential of Substrate-IPFS integration in overcoming the limitations of traditional blockchain storage approaches. Further exploration into the storage cost optimisation within the Substrate framework and additional functionalities using modular pallets could pave the way for significant advancements in the distributed data storage.
Falk, Brett, Tasneem Pathan, Andrew Rigas, Gerry Tsoukalas
In this note, we examine voting on four major blockchain DAOs: Aave, Compound, Lido and Uniswap. Using data directly collected from the Ethereum blockchain, we examine voter activity. We find that in most votes, the "minimal quorum," i.e., the smallest number of active voters who could swing the vote is quite small. To understand who is actually driving these DAOs, we use data from the Ethereum Name Service (ENS), Sybil.org, and Compound, to divide voters into different categories.
Khadija Begum, Md Ariful Islam Mozumder, Moon-Il Joo, Hee‐Cheol Kim
The Internet of Medical Things (IoMT) has significantly advanced healthcare, but it has also brought about critical security challenges. Traditional security solutions struggle to keep pace with the dynamic and interconnected nature of IoMT systems. Machine learning (ML)-based Intrusion Detection Systems (IDS) have been increasingly adopted to counter cyberattacks, but centralized ML approaches pose privacy risks due to the single points of failure (SPoFs). Federated Learning (FL) emerges as a promising solution, enabling model updates directly on end devices without sharing private data with a central server. This study introduces the BFLIDS, a Blockchain-empowered Federated Learning-based IDS designed to enhance security and intrusion detection in IoMT networks. Our approach leverages blockchain to secure transaction records, FL to maintain data privacy by training models locally, IPFS for decentralized storage, and MongoDB for efficient data management. Ethereum smart contracts (SCs) oversee and secure all interactions and transactions within the system. We modified the FedAvg algorithm with the Kullback-Leibler divergence estimation and adaptive weight calculation to boost model accuracy and robustness against adversarial attacks. For classification, we implemented an Adaptive Max Pooling-based Convolutional Neural Network (CNN) and a modified Bidirectional Long Short-Term Memory (BiLSTM) with attention and residual connections on Edge-IIoTSet and TON-IoT datasets. We achieved accuracies of 97.43% (for CNNs and Edge-IIoTSet), 96.02% (for BiLSTM and Edge-IIoTSet), 98.21% (for CNNs and TON-IoT), and 97.42% (for BiLSTM and TON-IoT) in FL scenarios, which are competitive with centralized methods. The proposed BFLIDS effectively detects intrusions, enhancing the security and privacy of IoMT networks.
In this thesis, the aim is to understand the possibilities and limitations of Zero Knowledge Proofs (ZKP) in blockchain technology. The first chapters focus on the presentation of distributed ledger systems and the tools that will be used, with particular reference to Remix, the IDE of choice for programming smart contracts in Solidity, and Sepolia, the Ethereum Testnet where the smart contracts were deployed. Subsequently, zero knowledge proofs are defined, their characteristics are explained, and the difference between interactive and non-interactive proofs is discussed; the latter will be emphasized as they are the most interesting in this context. The thesis then moves on to possible theoretical application contexts, with a particular focus on verifiable computation. Zokrates, a framework used to implement the non-interactive ZKP protocol, will be presented, explaining its language, features, functioning, and differences compared to other programming languages. A focal point for explaining how to implement verifiable computation will be introducing the various representations of an arithmetic circuit, fundamentally of textual and matrix types. Through various tests, the limitations of Zokrates and, to some extent, the entire arithmetic circuits sector for ZKP were highlighted. The thesis concludes with a possible implementation on the subject and an attack that this technology may be able to avoid.
Cheick Tidiane Bâ, Richard G. Clegg, Benjamin A. Steer, Matteo Zignani
In the dynamic landscape of the Web, we are witnessing the emergence of the Web3 paradigm, which dictates that platforms should rely on blockchain technology and cryptocurrencies to sustain themselves and their profitability. Cryptocurrencies are characterised by high market volatility and susceptibility to substantial crashes, issues that require temporal analysis methodologies able to tackle the high temporal resolution, heterogeneity and scale of blockchain data. While existing research attempts to analyse crash events, fundamental questions persist regarding the optimal time scale for analysis, differentiation between long-term and short-term trends, and the identification and characterisation of shock events within these decentralised systems. This paper addresses these issues by examining cryptocurrencies traded on the Ethereum blockchain, with a spotlight on the crash of the stablecoin TerraUSD and the currency LUNA designed to stabilise it. Utilising complex network analysis and a multi-layer temporal graph allows the study of the correlations between the layers representing the currencies and system evolution across diverse time scales. The investigation sheds light on the strong interconnections among stablecoins pre-crash and the significant post-crash transformations. We identify anomalous signals before, during, and after the collapse, emphasising their impact on graph structure metrics and user movement across layers. This paper pioneers temporal, cross-chain graph analysis to explore a cryptocurrency collapse. It emphasises the importance of temporal analysis for studies on web-derived data and how graph-based analysis can enhance traditional econometric results. Overall, this research carries implications beyond its field, for example for regulatory agencies aiming to safeguard users from shocks and monitor investment risks for citizens and clients.
Diogo S. Antunes, Afonso N. Oliveira, André Breda, Matheus Guilherme Franco · 6 authors
Traditional Byzantine Fault Tolerance (BFT) state machine replication protocols assume a partial synchrony model, leading to a design where a leader replica drives the protocol and is replaced after a timeout. Recently, we witnessed a surge of asynchronous BFT protocols, which use randomization to remove the need for bounds on message delivery times, making them more resilient to adverse network conditions. However, existing research proposals still fall short of gaining practical adoption, plausibly because they are not able to combine good performance with a simple design that can be readily understood and adopted. In this paper, we present Alea-BFT, a simple and highly efficient asynchronous BFT protocol, which is gaining practical adoption, namely in Ethereum distributed validators. Alea-BFT brings the key design insight from classical protocols of concentrating part of the work on a single designated replica and incorporates this principle in a simple two-stage pipelined design, with an efficient broadcast led by the designated replica, followed by an inexpensive binary agreement. The evaluation of our research prototype implementation and two real-world integrations in cryptocurrency ecosystems shows excellent performance, improving on the fastest protocol (Dumbo-NG) in terms of latency and displaying good performance under faults.
The first generation of cryptocurrencies introduced revolutionary concepts, yet faced challenges in privacy and regulatory compliance. While subsequent cryptocurrencies aimed to address privacy concerns (like Zcash and Monero), they often conflicted with regulatory frameworks, hindering broader adoption. In response, inspired by recent researches about privacy and accountability and incentive techniques in Blockchain, we propose IdentityChain as a novel framework that integrates privacy and accountability principles, leading to a robust system equipped with adaptable rules. IdentityChain is a KYC (Know Your Customer) service on top of a public Blockchain (e.g., Ethereum, Ton, Polygon). The goal is to maintain privacy while ensuring compliance with existing regulations. Privacy is one of the key characteristics of IdentityChain, it's crucial for preventing conflicts of interests further discussed how. Accountability is also one of the main characteristics of IdentityChain and prevents from misbehave of users. Privacy and accountability together wouldn't be possible unless advancements in cryptography.
Zhiyang Chen, Ye Liu, Sidi Mohamed Beillahi, Yi Li · 5 authors
Smart contracts, self-executing programs on the blockchain, facilitate reliable value exchanges without centralized oversight. Despite the recent focus on dynamic analysis of their transaction histories in both industry and academia, no open-source tool currently offers comprehensive tracking of complete transaction information to extract user-desired data such as invariant-related data. This paper introduces OpenTracer, designed to address this gap. OpenTracer guarantees comprehensive tracking of every execution step, providing complete transaction information. OpenTracer has been employed to analyze 350,800 Ethereum transactions, successfully inferring 23 different types of invariant from predefined templates. The tool is fully open-sourced, serving as a valuable resource for developers and researchers aiming to extract or validate new invariants from transaction traces. A demonstration video of OpenTracer is available at https://youtu.be/vTdmjWdYd30. The source code of OpenTracer is available at https://github.com/jeffchen006/OpenTracer.
The advent of blockchain technology and its adoption across various sectors have raised critical discussions about the need for regulatory mechanisms to ensure consumer protection, maintain financial stability, and address privacy concerns without compromising the foundational principles of decentralization and immutability inherent in blockchain platforms. We examine the existing mechanisms for smart contract termination across several major blockchain platforms, including Ethereum, BNB Smart Chain, Cardano, Solana, Hyperledger Fabric, Corda, IOTA, Apotos, and Sui. We assess the compatibility of these mechanisms with the requirements of the EU Data Act, focusing on aspects such as consumer protection, error correction, and regulatory compliance. Our analysis reveals a diverse landscape of approaches, from immutable smart contracts with built-in termination conditions to upgradable smart contracts that allow for post-deployment modifications. We discuss the challenges associated with implementing the so-called smart contract "kill switches," such as the balance between enabling regulatory compliance and preserving the decentralized ethos, the technical feasibility of such mechanisms, and the implications for security and trust in the ecosystem.
Ikechi Saviour Igboanusi, Chigozie Athanasius Nnadiekwe, Joseph Uche Ogbede, Dong‐Seong Kim · 5 authors
This work proposes a Blockchain-enabled Organ Matching System (BOMS) designed to manage the process of matching, storing, and sharing information. Biological factors are incorporated into matching and the cross-matching process is implemented into the smart contracts. Privacy is guaranteed by using patient-associated blockchain addresses, without transmitting or using patient personal records in the matching process. The matching algorithm implemented as a smart contract is verifiable by any party. Clinical records, process updates, and matching results are also stored on the blockchain, providing tamper-resistance of recipient's records and the recipients' waiting queue. The system also is capable of handling cases in which there is a donor without an immediate compatible recipient. The system is implemented on the Ethereum blockchain and several scenarios were tested. The performance of the proposed system is compared to other existing organ donation systems, and ours outperformed any existing organ matching system built on blockchain. BOMS is tested to ascertain its compatibility with public, private, and consortium blockchain networks, checks for security vulnerabilities and cross-matching efficiency. The implementation codes are available online.
Hulin Yang, Mingzhe Li, Jin Zhang, Alia Asheralieva · 6 authors
The advent of Ethereum 2.0 has introduced significant changes, particularly the shift to Proof-of-Stake consensus. This change presents new opportunities and challenges for arbitrage. Amidst these changes, we introduce BriDe Arbitrager, a novel tool designed for Ethereum 2.0 that leverages Bribery-driven attacks to Delay block production and increase arbitrage gains. The main idea is to allow malicious proposers to delay block production by bribing validators/proposers, thereby gaining more time to identify arbitrage opportunities. Through analysing the bribery process, we design an adaptive bribery strategy. Additionally, we propose a Delayed Transaction Ordering Algorithm to leverage the delayed time to amplify arbitrage profits for malicious proposers. To ensure fairness and automate the bribery process, we design and implement a bribery smart contract and a bribery client. As a result, BriDe Arbitrager enables adversaries controlling a limited (< 1/4) fraction of the voting powers to delay block production via bribery and arbitrage more profit. Extensive experimental results based on Ethereum historical transactions demonstrate that BriDe Arbitrager yields an average of 8.66 ETH (16,442.23 USD) daily profits. Furthermore, our approach does not trigger any slashing mechanisms and remains effective even under Proposer Builder Separation and other potential mechanisms will be adopted by Ethereum.
Cryptocurrency is a form of decentralized digital currency. Ethereum is the second-largest cryptocurrency by market capitalization and the largest altcoin. Cryptocurrencies including Ethereum are highly volatile. Hence, shortterm directional forecasts in the cryptocurrency market have become a widely discussing topic. Candlestick charts are useful visualizations of the open, high, low and close prices which can identify patterns and gauge the near-term direction of prices. This research explores the effectiveness of forecasting hourly Ethereum closing price direction based on candlestick charts within a short time horizon. The proposed forecasting algorithm incorporates clustering methods such as fuzzy K-means, K-means and partition around medoids clustering to cluster candlestick chart properties namely upper shadow length, body length and lower shadow length. Classification methods such as random forest, support vector machine and K-nearest neighbour were used to forecast closing price direction using 16 different predictor variable sets including open, high, low and close prices, candlestick chart price direction, USL, BL and LSL. The accuracy for all considered cases was around 50%. Clustering improved the accuracy slightly and including the CPD with the predictor variable sets under consideration can increase the accuracy slightly. However, this approach is performing better in predicting the Down cases to the total number of actual Down cases because there is a higher sensitivity of 81.20% based on the SVM with Open, High, Low and Close at t in the clustering ignored method.
Imran Khan, Qazi Ejaz Ali, Hassan Jalil Hadi, Naveed Ahmad · 7 authors
A supply chain (SC) encompasses a network of businesses, individuals, events, data, and resources orchestrating the movement of goods or services from suppliers to customers. Leveraging a blockchain-based platform, smart contracts play a pivotal role in aligning business logic and tracking progress within supply chain activities. Employing two distinct ledgers, namely Hyperledger and Ethereum, introduces challenges in handling the escalating volume of data and addressing the technical expertise gap related to supply chain management (SCM) tools in blockchain technology. Within the domain of blockchain-based SCM, the growing volume of data activities introduces challenges in the efficient regulation of data flow and the assurance of privacy. To tackle these challenges, a straightforward approach is recommended to manage data growth and thwart unauthorized entries or spam attempts within blockchain ledgers. The proposed technique focuses on validating hashes to ensure blockchain integrity. Emphasizing the authentication of sensitive data on the blockchain to bolster SCM, this approach compels applications to shoulder increased accountability. The suggested technique involves converting all data into textual format, implementing code encryption, and establishing permission-based access control. This strategy aims to address inherent weaknesses in blockchain within SCM. The results demonstrate the efficacy of the proposed technique in providing security and privacy for various types of data within SCM. Overall, the approach enhances the robustness of blockchain-based SCM, offering a comprehensive solution to navigate evolving challenges in data management and privacy assurance.
U ovom diplomskom radu implementiran je decentralizirani sustav kreditiranja i štednje koristeći tehnologiju raspodijeljene glavne knjige. Rad počinje uvodom u osnovne koncepte raspodijeljene glavne knjige, kriptografiju i konsenzusne mehanizme. Analiziran je Ethereum lanac blokova, transakcije i razvoj pametnih ugovora koristeći Solidity i Hardhat. Glavni dio rada fokusira se na implementaciju pametnih ugovora za kreditiranje i štednju, uključujući izdavanje kredita s kolateralom i štednju stabilnih kriptovaluta uz kamate. Razvijeni su vanjski servisi za likvidaciju i ažuriranje kamatnih stopa, te interaktivno korisničko sučelje izrađeno s React.js i TypeScriptom.
Solidity compiler plays a key role in enabling the development of smart contract applications on Ethereum by governing the syntax of a domain-specific language called Solidity and performing compilation and optimization of Solidity code. The correctness of Solidity compiler is critical in fostering transparency, efficiency, and trust in industries reliant on smart contracts. However, like other software systems, Solidity compiler is prone to bugs, which may produce incorrect bytecodes on blockchain platforms, resulting in severe security concerns. As a domain-specific compiler for smart contracts, Solidity compiler differs from other compilers in many perspectives, posing unique challenges to detect its bugs. To understand the bugs in Solidity compiler and benefit future research, in this paper, we present the first systematic study on 533 Solidity compiler bugs. We carefully examined their characteristics (including symptoms, root causes, and distribution), and their triggering test cases. Our study leads to seven bug-revealing takeaways for Solidity compiler. Moreover, to study the limitations of Solidity compiler fuzzers and bring our findings into practical scenarios, we evaluate three Solidity compiler fuzzers on our constructed benchmark. The results show that these fuzzers are inefficient in detecting Solidity compiler bugs. The inefficiency arises from their failure to consider the interesting bug-inducing features, bug-related compilation flags, and test oracles.
This paper examines the efficiency and asymmetric multiracial features of NFTs (Mana, Tezos), and traditional assets (EGX30, Oil index) using Asymmetric Multiracial Cross-Correlations Analysis covering the period from January 2020 to May 2021. Considering the full sample with a significant variation among asset classes. (Oil-Tezos)and (Mana-Tezos) is the most efficient.Since their inception, the blockchain-based digital asset classes have received immense interest from investors and portfolio managers as an alternative investment platform. Along with other established traditional cryptocurrencies such as Bitcoin, Litecoin, Ripple, and Ethereum, new blockchain asset classes such as Decentralized Finance (DeFi) and Non-Fungible Tokens (NFTs) have made a considerable contribution tothe asset market’s recent expansion (Aharon & Demir, 2021; Alam, Chowdhury, Abdullah, & Masih, 2023; Maouchi, Charfeddine, & el Montasser, 2021; Yousaf & Yarovaya, 2022).Fundamentally, NFTs and DeFi differ from traditional cryptocurrencies as they are not virtual currency. Where NFTs are non-transferable cryptographic digital assetscreated by Ethereum smart contracts and can be sold and traded, the interchangeability of NFTs when comparing the other cryptocurrencies is very low (Karim, Lucey, Naeem, & Uddin, 2022; Q. Wang, Li, Wang, & Chen, 2021; Y. Wang, 2022).The NFTs and DeFi are relatively contemporary and unexplored asset classes, but their market capitalization has grown substantially as risk minimizing assets, particularly during the COVID-19 period. In the NFT space, the KeywordsVolatility, NFTs, Traditional Financial Assets, and MGARCH
Michał Król, Onur Ascigil, Sergi Reñé, Alberto Sonnino · 8 authors
The Ethereum Global Network (EGN) hosts a complete ecosystem of decentralized services, including blockchains such as Ethereum mainnet but also exchange markets, content delivery networks, and many more. Service discovery is a fundamental mechanism in the EGN, allowing new nodes to look up and connect to other nodes already participating in one of these services. The current service discovery of the EGN, DISCv5, is not scalable and efficient enough to support the current and future needs of the ecosystem. We present DISC-NG, a novel service discovery protocol for the EGN that is scalable, efficient, and secure. DISC-NG leverages the EGN-wide DHT to allow service participation advertisements to meet service discovery requests. DISC-NG compensates the unbalance in service popularity and minimizes the potential for abuse by malicious nodes. We implement DISC-NG in devp2p, the network stack used by the majority of clients connecting to the EGN, as well as in a large-scale simulator. DISC-NG can discover services in the EGN faster than DISCv5 while being more robust to malicious nodes. DISC-NG is now in a staging phase and scheduled for deployment as an improvement to DISCv5.