The majority of NFTs utilize the Ethereum blockchain platform to facilitate smart contracts. In this paper, we execute various econometric analyses to determine if this technical dependence induces a financial linkage to the risk, return, and prices of assets. For robustness, we also test the same relation between Bitcoin and NFTs. Empirical analyses are conducted through SADF bubbles test, DCC-GARCH time-varying correlation analysis, Bootstrap causality tests and spillover analysis. According to the results of various price, return, and volatility analyses, we find that NFTs do not demonstrate idiosyncratic features in their price developments and thus they cannot be considered as a separate asset class. Additionally, NFTs do not possess a specific financial linkage with Ethereum from using its infrastructure. Finally, we suggest NFT investors use alternative financial instruments, rather than Ether and Bitcoin in portfolio diversification, due to the presence of significant time-varying relationships and interactions.
Blockchain has widespread applications in the financial field but has also attracted increasing cybercrimes. Recently, phishing fraud has emerged as a major threat to blockchain security, calling for the development of effective regulatory strategies. Nowadays network science has been widely used in modeling Ethereum transaction data, further introducing the network representation learning technology to analyze the transaction patterns. In this paper, we consider phishing detection as a graph classification task and propose an end-to-end Phishing Detection Graph Neural Network framework (PDGNN). Specifically, we first construct a lightweight Ethereum transaction network and extract transaction subgraphs of collected phishing accounts. Then we propose an end-to-end detection model based on Chebyshev-GCN to precisely distinguish between normal and phishing accounts. Extensive experiments on five Ethereum datasets demonstrate that our PDGNN significantly outperforms general phishing detection methods and scales well in large transaction networks.
Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Taief Alaa Al-Amiedy · 7 authors
Ethereum attracts more investors, researchers, and even scammers for many reasons; this is the first platform that enables the new Decentralized Applications (DApps) to run on top of the blockchain network. However, the rich semantics and applications of DApps inevitably introduce many security issues that have grabbed significant attention from industry and academics due to their destructive impact on DApps in recent years. Therefore, there is a vital need to study the applicability of Intrusion Detection System in detecting Ethereum-based attacks. Hence, this paper is among the first comprehensive review that studies the applicability of IDS in detecting Ethereum-based attacks. In addition, this paper lists all the potential attacks on Ethereum passing through the vulnerabilities that cause those attacks and ending with the consequences of each attack. Besides, this paper analyses all the IDS-based related works of Ethereum attacks detection since the Ethereum platform was launched in 2015. Finally, this paper discusses the open issues regarding vulnerabilities and attacks, challenges, and future directions.
The Ethereum blockchain is a fascinating platform that uses innovative smart contract capability to empower decentralized applications in almost all major business sectors. Pioneered by Vitalik Buterin and several cofounders, Ethereum has gone through the milestones of initial launch, stable coins, ICO (Initial Coin Offering), DeFi (Decentralized Finance), DAO (Decentralized Autonomous Organization), NFT (nonfungible tokens), and L2 (Layer 2) for scalability. The Ethereum blockchain and infrastructure are transitioning to POS (proof of stake) with sharding and are on the way to impose big impacts on CBDC (Central Bank Digital Currency) and enterprise blockchains with promising potential. After years of astronomical growth, Ethereum has reached a market cap of $400 billion, just trailing behind Bitcoin. Compared with bitcoin, the Ethereum blockchain has advantages such as supporting the Ethereum Virtual Machine (EVM) and smart contracts, supporting more diverse use cases, and being more nimble by changing consensus from POW to POS to save energy costs.
There is a growing demand for transparency along the agri-food chain, both from customers and governments. The adoption of blockchain technology to enable secure traceability for the management of the agri-food chain, provide information such as the provenance of a food product and prevent food fraud, is emerging rapidly, due to the inherent trust and inalterability provided by this technology. However, developing the right smart contracts for these use cases is even more of a challenge than it is for those used in other fields. Several management systems for the agri-food chain based on blockchain technology and smart contract have been proposed, all however ad-hoc for a specific product or production process and difficult to generalize. In this paper, we propose a new approach to easily customize and compose general Ethereum-based smart contracts designed for the agri-food industrial domain, to be able to reuse the code and modules and automate the process to shorten development times, while keeping it safe and reliable. Starting from the definition of the real production process, we aim to automatically generate both the smart contracts to manage the system and the user interfaces to interact with them, thus producing a system that works semi-automatically. Additionally, we describe a honey production case study to show how our approach works. Future work will first extend the scope of the approach to other supply chains, furthermore, while the current platform used is Ethereum, in the future our approach will be easily extended to other blockchain platforms.
Arkan Hammoodi Hasan Kabla, Mohammed Anbar, Selvakumar Manickam, Shankar Karupayah
Recently, the rapid flourish of blockchain technology in the financial field has attracted many cybercriminals’ attention to launch blockchain-based attacks such as Ponzi schemes, Scam wallets, and phishing scams. Currently, Ethereum is the most prominent blockchain-based platform and the first that supports smart contracts. However, the number of phishing scam accounts are reportedly more than 50% of all cybercrimes in Ethereum. In contrast, this paper proposes a detection mechanism called Ethereum Phishing Scam Detection (Eth-PSD) that attempts to detect phishing scam-related transactions using a novel machine learning-based approach. Eth-PSD tackles some of the limitations in the existing works, such as the use of imbalanced datasets, complex feature engineering, and lower detection accuracy. We also investigated the aspects of constructing a new updated and balanced dataset that can be used for evaluating Eth-PSD effectively. Our experimental results indicate that Eth-PSD could efficiently detect the phishing scam on Ethereum with a detection accuracy of 98.11%, with a very low False Positive Rate of 0.01. Taken together, Eth-PSD showed a superior advantage compared to the existing works in reducing the dimensionality of the dataset by feature engineering and achieved an overall detection accuracy with an improvement of at least 6% compared to other existing solutions from the related work.
Blockchain technology has the characteristics of decentralization, traceability and tamper-proof, which creates a reliable decentralized trust mechanism, further accelerating the development of blockchain finance. However, the anonymization of blockchain hinders market regulation, resulting in increasing illegal activities such as money laundering, gambling and phishing fraud on blockchain financial platforms. Thus, financial security has become a top priority in the blockchain ecosystem, calling for effective market regulation. In this paper, we consider identifying Ethereum accounts from a graph classification perspective, and propose an end-to-end graph neural network framework named Ethident, to characterize the behavior patterns of accounts and further achieve account de-anonymization. Specifically, we first construct an Account Interaction Graph (AIG) using raw Ethereum data. Then we design a hierarchical graph attention encoder named HGATE as the backbone of our framework, which can effectively characterize the node-level account features and subgraph-level behavior patterns. For alleviating account label scarcity, we further introduce contrastive self-supervision mechanism as regularization to jointly train our framework. Comprehensive experiments on Ethereum datasets demonstrate that our framework achieves superior performance in account identification, yielding 1.13% ~ 4.93% relative improvement over previous state-of-the-art. Furthermore, detailed analyses illustrate the effectiveness of Ethident in identifying and understanding the behavior of known participants in Ethereum (e.g. exchanges, miners, etc.), as well as that of the lawbreakers (e.g. phishing scammers, hackers, etc.), which may aid in risk assessment and market regulation.
On September 15, 2022, the Ethereum network adopted a proof-of-stake (PoS) consensus mechanism. We study the impact on the network and competing platforms in a two month event window around the Beacon chain merge. We find that the transition to PoS has reduced energy consumption by 99.98%. Miners have not transformed into validators, and total block reward income (in USD) has fallen by 97%, though transaction fees (in ETH) for Ether have increased nearly 10%. The Herfindahl index for the top 10 is 1,009; the network is 19% less concentrated after the merge. Ethereum supply growth has been deflationary since the merge. The time between consecutive blocks is now steady at 12 seconds and transactions per day are up 7.0%. On Polygon, Matic fees rose but token fees fell. Polygon also slows, processing 3.3% fewer transactions per day. Solana's fees fall by $0.0003, and transactions per day are down 48%. Stablecoin transfer volumes fall on Ethereum and Polygon, but rise on Solana.
Blockchain technology and its applications are gaining popularity day by day. It is a ground-breaking technology that allows users to communicate without the need of a trusted middleman. A smart contract (self-executable code) is deployed on the blockchain and auto executes due to a triggering condition. In a no-trust contracting environment, smart contracts can establish trust among parties. Terms and conditions embedded in smart contracts will be imposed immediately when specified criteria have been fulfilled. Due to this, the malicious assailants have a special interest in smart contracts. Blockchains are immutable means if some transaction is deployed or recorded on the blockchain, it becomes unalterable. Thus, smart contracts must be analyzed to ensure zero security vulnerabilities or flaws before deploying the same on the blockchain because a single vulnerability can lead to the loss of millions. For analyzing the security vulnerabilities of smart contracts, various analysis tools have been developed to create safe and secure smart contracts. This paper presents a systematic review on Ethereum smart contracts analysis tools. Initially, these tools are categorized into static and dynamic analysis tools. Thereafter, different sources code analysis techniques are studied such as taint analysis, symbolic execution, and fuzzing techniques. In total, 86 security analysis tools developed for Ethereum blockchain smart contract are analyzed regardless of tool type and analysis approach. Finally, the paper highlights some challenges and future recommendations in the field of Ethereum smart contracts.
Blockchain is a revolutionary technology that enables users to communicate in a trust-less manner. It revolutionizes the modes of business between organizations without the need for a trusted third party. It is a distributed ledger technology based on a decentralized peer-to-peer (P2P) network. It enables users to store data globally on thousands of computers in an immutable format and empowers users to deploy small pieces of programs known as smart contracts. The blockchain-based smart contract enables auto enforcement of the agreed terms between two untrusted parties. There are several security vulnerabilities in Ethereum blockchain-based smart contracts, due to which sometimes it does not behave as intended. Because a smart contract can hold millions of dollars as cryptocurrency, so these security vulnerabilities can lead to disastrous losses. In this paper, a systematic review of the security vulnerabilities in the Ethereum blockchain is presented. The main objective is to discuss Ethereum smart contract security vulnerabilities, detection tools, real life attacks and preventive mechanisms. Comparisons are drawn among the Ethereum smart contract analysis tools by considering various features. From the extensive depth review, various issues associated with the Ethereum blockchain-based smart contract are highlighted. Finally, various future directions are also discussed in the field of the Ethereum blockchain-based smart contract that can help the researchers to set the directions for future research in this domain.
Sanal Kripto Para kavramı Bitcoin ile birlikte 2009 yılında dikkat çekmeye başlamış ve özellikle 2013 yılındaki fiyat artışı ile popülaritesi artmıştır. Sanal Kripto Para birimlerinin ilki ve öncüsü olan Bitcoin ile 2. En büyük piyasa değerine sahip olan Ethereum tasarımsal yapıları ve amaçları bakımından birbirlerinden oldukça farklıdır. Sanal bir para birimi olması için tasarlanan Bitcoin ile üzerinde akıllı kontratlar çalışmasına olanak vermek için tasarlanan Ethereum birçok alanda olduğu gibi iktisat alanında da oldukça dikkat çekmiş ve literatürde birçok çalışmaya konu olmuştur. Bu çalışmanın amacı Türkiye GSYH’sı, M2 Tanımı ile para arzı ve tüketici güven endeksinin Bitcoin ve Ethereum fiyatına olan etkilerini karşılaştırmalı olarak tahmin etmektir. Bu amaçla, Bitcoin ve Etherum’un Türk Lirası cinsinden fiyatlarını bağımlı değişken alan iki farklı model kurulmuştur. Kurulan modeller, Ocak 2016 ile Aralık 2020 dönemini kapsayan aylık veriler kullanılarak, zaman serisi analizi kapsamında, Johansen Eşbütünleşme Testi ve Tam Uyarlanmış En Küçük Kareler Yöntemi (FMOLS) kullanılarak uzun dönemde sınanmıştır. Yapılan analizin sonucunda hem Bitcoin hem de Ethereum’un Türk lirası cinsinden fiyatları, GSYH ve tüketici güven endeksi ile pozitif ilişkili, M2 para arzı ile negatif ilişkili bulunmuştur. Çalışmanın bulgularından bir diğeri ise toplam piyasa değeri Bitcoin’e göre daha düşük olan Ethereum’un tüm değişkenlerden daha çok etkilendiğidir. Elde edilen sonuçlar bu çalışmanın türetildiği Yüksek Lisans Tezindeki bulgular ile örtüşmekte ve birbirini desteklemektedir.
As cryptocurrencies gain global traction, concerns over user privacy and transaction traceability have intensified. Public blockchains like Bitcoin and Ethereum inherently expose transactional data, compromising user anonymity. In response, various privacy-preserving cryptographic techniques have been developed to conceal user identities, transaction amounts, and flow paths without sacrificing security or decentralization. This paper explores key cryptographic solutions including ring signatures, zero-knowledge proofs (ZKPs), stealth addresses, and homomorphic encryption as applied in privacy-focused cryptocurrencies such as Monero and Zcash. The study evaluates the effectiveness, scalability, and regulatory implications of these protocols, providing insights into the future of anonymous digital finance.
Antonio Welligton Abreu, Emanuel Ferreira Coutinho, Carla Bezerra
Blockchain is an emerging technology, with a decentralized infrastructure avoiding third party dependency. Smartcontracts are one of the features of Ethereum blockchain, capable of running distributed applications in unreliableenvironments, enabling process automation and being one of the most sought technologies due to the highcustomization added to transactions. However, little is known about predicting the cost and execution time behavior of blockchain-based system transactions. This work aims to evaluate the performance of an Ethereum network through an application designed to analyze the cost and time of transactions that store characters in the blockchain. To meet the proposed objective, we designed an application for performing transactions with data inclusion and query on a blockchain, collecting time and cost data. As main conclusions of this work we have: the Ethereum platform proved to be inconstant in relation to the processing time of transactions on the blockchain and the application developed based on blockchain can provide a mechanism to evaluate text-type operations on Ethereum network.
Yeonggwang Kim, Seungmin Oh, Junchurl Yoon, Tai‐Won Um
The NFT (Non-Fungible Token) market has soared in recent years. The concept of NFT originally originated from Ethereum’s token standard and aims to distinguish each token with a distinguishable symbol. Tokens of this type can bind virtual/digital attributes to unique identification items. These features can be used to bind AI learning outcomes to unique identification items. A simple load forecast learning model can be produced with simple PC performance. However, if the structure is complicated or the number of learning epoch increases, the value and importance of the model are made difficult. This study was conducted to promote developer participation in complex model development and to protect works.
Xiaoyang Shi, Hang Xiao, Weifeng Liu, Xi Chen · 7 authors
The distributed consensus mechanism is the backbone of the rapidly developing blockchain network. Blockchain platforms consume vast amounts of electricity based on the current consensus mechanism of Proof-of-Work (PoW). Here, we point out a different consensus mechanism named Proof-of-Stake (PoS) that can eliminate the extensive energy consumption of the current PoW-based blockchain. We comprehensively elucidate the current and projected energy consumption and carbon footprint of the PoW- and PoS-based Bitcoin and Ethereum blockchain platforms. The model of energy consumption of PoS-based Ethereum blockchain can lead the way toward the prediction of other PoS-based blockchain technologies in the future. With the widespread adoption of blockchain technology, if the current PoW mechanism continues to be employed, the carbon footprint of Bitcoin and Ethereum will push the global temperature above 1.5 °C in this century. However, a PoS-based blockchain can reduce the carbon footprint by 99% compared to the PoW mechanism. The small amount of carbon footprint from PoS-based blockchain could make blockchain an attractive technology in a carbon-constrained future. The study sheds light on the urgency of developing the PoS mechanism to solve the current sustainability problem of blockchain.
This paper focuses on the political genealogy of one of the most promising and influential IT technologies of our time: the blockchain (or distributed registry). We point at important commonalities between the principles of blockchain projects and models of republican governance. In contrast to techno-anarchist and democratic ideas, the republican genealogy of blockchain has so far failed to attract the attention of researchers. After examining the basic technical properties and ideological images of blockchain, we explore how the four main principles of classical republicanism (personal freedom and autonomy of the individual; civic virtues; common good; recognition of great causes) are realized in influential blockchain projects — Bitcoin (developed by the pseudonymous Satoshi Nakamoto) and Ethereum (developed by Vitalik Buterin). The functioning of blockchain nodes is supported by a community of miners, who are free, but at the same time agree to act for the development of a common thing. What the republic and the blockchain have in common is that it is impossible to have a community without cooperative action. At the same time, blockchain is a vivid illustration of Bruno Latour's argument on the role of non-humans in social relations: his code seeks to replace untrustworthy humans with rule-acting nodes, and to create a cryptographic society where untrustworthy human relations are replaced by computers' relations. This article is an invitation to begin a discussion of the political ideas that are embedded in new technologies and the models of governance that are mobilized through them, often without proper reflection on the nature of such ideas by their creators.
The blockchain as the tool was invented together with the Bitcoin and evolving. Despite the fact that new blockchains appeared, like Ethereum and other, the first one was not explored enough from the perspective of understanding dependencies between its elements. Mathematical and cryptographic dependencies are well described in the scientific literature, but dependencies exploration and description in relation to its economical usage of it is still missing. The blockchain structure and mechanics provide that transaction registered within the blockchain are not free for the final user. The transaction price in the Blockchain exists. This transaction price can be decisive for the implementation of a project using blockchain. Understanding factors, which affect this price forming helps to understand frames, when usage of the blockchain is effective. Taking into account all above mentioned, one of the targets of this article is to analyze the life cycle of transactions in the blockchain and determine the factors that have a significant impact on the formation of the transaction price in the Bitcoin Blockchain. From the other hand blockchain assumed as the competitor or even “killer” of the traditional payment systems. There is the list of elements, which should be taken in account comparing both approaches for the transaction execution. This list includes comparing deficits and advantages of both systems, like security issues, transaction speed issues and so on. From this perspective based on the comparing the transactional price forming in both systems, author assess the prospects for using transactions in the Blockchain in comparing with the traditional payment systems.
Bu çalışma 2011 yılından itibaren temel olarak “belirsizlik” ve “ekonomi” anahtar kelimelerini içeren tweetlerin baz alınarak oluşturulduğu Twitter Bazlı Belirsizlik Endeksinin, son yılların gözde yatırım araçlarından olan kripto paraların volatilitesine etkisini incelemeyi amaçlamaktadır. Piyasa değeri en yüksek, Binance, Bitcoin, Cardano, Ethereum, Ripple ve Tether kripto paralar 18/01/2018- 11/07/2021 dönemi için günlük verilerle ARCH-GARCH ailesi modelleri ile incelenmiştir. Çalışmada öncelikle ortalama denklemi oluşturulan modellerin ARCH-GARCH modellerine uygunluğu sınanmış ve incelenen dönemde Bitcoin ve Ethereum için ARCH etkisinin olmadığı ancak Binance, Cardano, Ripple ve Tether için volatilite modellerinin kullanımının uygun olduğu bulgusu elde edilmiştir. Binance için GARCH (1,1), Cardano için GARCH-M (1,1), Ripple için ARCH (2) modeli volatiliteyi en iyi yakalayan model olarak seçilmiştir. Twitter Bazlı Belirsizlik Endeksinin bu modellerin hepsinde istatistiki olarak anlamlı ve pozitif bir etkiye sahip olduğu tespit edilmiştir. Bu sonuçlara göre bir sosyal medya platformu olan Twitter’da yer alan belirsizlik ve ekonomi içerikli tweetlerin kripto varlıkların volatilitesini etkilediğini söylemek mümkündür.
Data sharing is a crucial step in the research community to make the most of the prior effort. Platforms for sharing data currently in use rely on trustworthy third parties (TTP). Such systems lack immutability, security, transparency, and trust because of TTP’s involvement. In order to address these problems, the proposed system approaches an Interplanetary File System (IPFS)-based blockchain-based secure data sharing platform. The user uploads a data file to the IPFS server, which is subsequently split up into several secret shares. By carrying out the access responsibilities that the user has specified in the smart contract, the suggested scheme accomplishes security and access control. This scenario combines encryption, Ethereum blockchain technology, decentralized storage, and incentive systems. Solidity smart contracts are created and deployed on a local Ethereum test network in order to carry out the suggested scenario. Transparency, Security, Access control, Owner authenticity, and Data quality are all achieved by the suggested plan.
Blockchain is one of the technologies provided by the global distribution of computing power. Simply put, the blockchain is the digital ledger in which transactions are recorded. It all started with a desire to see a new form of security system for transferring confidential files. It aims to achieve many goals like decreasing the process time for transferring files to the other party, and reducing the overall expenses as the files are only transferred across the blockchain network with no need for the files to be uploaded and downloaded to the drive. More effective applications have the ability to share files via the technology of Blockchain. The great challenge is to build a private blockchain environment to send files and distribute them securely between parties, such as military institutions and others. In this paper, a private blockchain is built to overcome the side of the security through a secured file-sharing network. This private Blockchain can be utilized at various institutions. A high scale of security is obtained through using an important algorithm that takes into consideration a critical part of the field of cryptography to robustly encrypt the files. The latter ensures that no individual except for the receiver has the ability to access the files. As well, a sufficient speed was obtained when transferring the files, as compared to Ethereum with FTP. Finally, smart contracts have been designed to suit the transfer of files between nodes.
Sanjib Kumar Nayak, Sarat Chandra Nayak, Subhranginee Das
Artificial neural networks (ANNs) are suitable procedures for predicting financial time series (FTS). Cryptocurrencies are good investment assets; therefore, the effective prediction of cryptocurrencies has become a trending area of research. Capturing inherent uncertainties associated with cryptocurrency FTS with conventional methods is difficult. Though ANNs are the better alternative, fixing the optimal parameters of ANNs is a tedious job. This article develops a hybrid ANN through Rao algorithm (RA + ANN) for the effective prediction of six popular cryptocurrencies such as Bitcoin, Litecoin, Ethereum, CMC 200, Tether, and Ripple. Six comparative models such as GA + ANN, PSO + ANN, MLP, SVM, LSE, and ARIMA are developed and trained in a similar way. All these models are evaluated through the mean absolute percentage of error (MAPE) and average relative variance (ARV) metrics. It is found that the proposed RA + ANN generated the lowest MAPE and ARV values, statistically different as compared with existing methods mentioned above, and hence can be recommended as a potential financial instrument for predicting cryptocurrencies.
The objective of this paper is to assess the performances of dimensionality reduction techniques to establish a link between cryptocurrencies. We have focused our analysis on the two most traded cryptocurrencies: Bitcoin and Ethereum. To perform our analysis, we took log returns and added some covariates to build our data set. We first introduced the pearson correlation coefficient in order to have a preliminary assessment of the link between Bitcoin and Ethereum. We then reduced the dimension of our data set using canonical correlation analysis and principal component analysis. After performing an analysis of the links between Bitcoin and Ethereum with both statistical techniques, we measured their performance on forecasting Ethereum returns with Bitcoin s features.