Blockchain Papers

Henrik Axelsen, Omri Ross

No abstract is available for this record.

Xiaoyin Wang, Jiaze Sun, Chunyang Hu, Panpan Yu · 6 authors

With the development of Internet of Things technology, the use of Internet of Things is expanding, and its security risk will become an important factor restricting the development of Internet of Things technology. The application of blockchain technology in the security field of the Internet of Things can improve security problems, and the blockchain has immutable characteristics. Therefore, it is particularly important to ensure the security of blockchain smart contracts. However, the order of transaction in smart contracts is easy to be operated by miners, and there is a relative lack of tools to detect TOD (transaction‐ordering dependent) vulnerabilities. The current smart contract vulnerability detection methods have the problems of low efficiency and low accuracy. Therefore, based on the study of TOD vulnerability principle, this paper creatively highlights a mutation fuzzy testing method EtherFuzz to specifically detect TOD vulnerability in smart contracts. Use the intelligent contract ABI (application binary interface) to generate test cases, test the byte code of the intelligent contract, use TOD to test oracle to detect TOD vulnerabilities, and then, mutate the tested data to generate new test cases. Finally, the behavior of smart contract operation is recorded, and the fuzzy test process is controlled until the vulnerability is detected. The experimental results show that when 987 token contracts are selected as Ethereum test objects, the false‐positive rate, detection time overhead, and detection storage overhead of EtherFuzz are reduced by 74.4%, 30.1%, and 28.1%, respectively. Therefore, EtherFuzz has high speed, efficiency, and accuracy in detecting TOD vulnerabilities and has excellent application value.

ike, BarefootDev

The Ethereum blockchain permits the development and deployment of smart contracts which can store and execute code 'on-chain' - that is, entirely on nodes in the blockchain's network. Smart contracts have traditionally been used for financial purposes, but since smart contracts are Turing-complete, their algorithmic scope is broader than any single domain. To that end, we design, develop, and deploy a comprehensive 3D rendering engine programmed entirely in Ethereum smart contracts, called Shackled. Shackled computes a 2D image from a 3D scene, executing every single computation on-chain, on Ethereum. To our knowledge, Shackled is the first and only fully on-chain 3D rendering engine for Ethereum. In this work, we 1) provide three unique datasets for the purpose of using and benchmarking Shackled, 2) execute said benchmarks and provide results, 3) demonstrate a potential use case of Shackled in the domain of tokenised generative art, 4) provide a no-code user interface to Shackled, 5) enumerate the challenges associated with programming complex algorithms in Solidity smart contracts, and 6) outline potential directions for improving the Shackled platform. It is our hope that this work increases the Ethereum blockchain's native graphics processing capabilities, and that it enables increased use of smart contracts for more complex algorithms, thus increasing the overall richness of the Ethereum ecosystem.

Srinjoy Mahato, Tanmoy Khatua, Tathagata Roy Chowdhury

Here we discuss about different cryptocurrencies those are very much important in network security market. As we know cryptocurrencies are digital assets which can be designed to work as exchange that can use strong cryptography to protect all the transactions, here the main Two aspects of those: Bitcoin and Ethereum, is discussed with their all functionalities, their methods of work, their advantages over each and other and more over their concepts of architecture.

Yanyu Chen, Zhangjie Fu

As a typical representative of web 2.0, Ethereum has significantly boosted the development of blockchain finance. However, due to the anonymity and financial attributes of Ethereum, the number of phishing scams is increasing rapidly and causing massive losses, which poses a serious threat to blockchain financial security. Phishing scam address identification enables to detect phishing scam addresses and alerts users to reduce losses. However, there are three primary challenges in phishing scam address recognition task: 1) the lack of publicly available large datasets of phishing scam address transactions; 2) the use of multi-order transaction information requires a large number of queries and computations; and 3) the extraction of phishing scam address features relies on machine learning methods excessively, which leads to the loss of practical meaning and is harmful to the research of phishing scam addresses. This paper proposes a systematic phishing scam address recognition scheme, to simultaneously overcome the three challenges in phishing scam address recognition. In this paper, a systematic phishing scam address recognition scheme is proposed to addresses these issues. Specifically, due to the insufficient number of address tagged in the existing publicly available Ethereum phishing scam address transaction dataset, we first construct a transaction dataset involving over 10000 tagged addresses. To the best of our knowledge, this is the largest dataset of tagged addresses for Ethereum phishing scam detection. Then, we design a new heuristic rule to implement feature extraction of address nodes by analysing the traditional financial involved accounts combined with information specific to Ethernet transactions. After that, a novel adaptive feature importance filtering method is designed to adaptively adjust the filtering threshold based on the final classification results, which reduce the feature dimensionality while ensuring a certain detection performance. Finally, random forest is used to classify whether the addresses is a phishing scam address or not. Extensive experiments on real Ethereum datasets show that our approach (98.89% Precision, 98.35% Recall, 98.62% F1) achieves state-of-the-art performance.

Yazeed Essam Khaled Althunibat

The Non-Fungible Token (NFT) market has been exploding in the past years. The notion of NFT originated with Ethereum's token standard, which aimed to differentiate each token using distinguishing signals. Tokens of this type can be associated with virtual or digital properties to serve as unique identifiers. Using NFTs Non-Fungible Token (NFT) is a new technology gaining traction in the Blockchain industry. In this article, we examine state-of the art NFT systems that have the potential to reshape the market for digital virtual assets. We will assess the security of existing NFT systems and expand on the opportunities and prospective uses for the NFT idea. Finally, we discuss existing research challenges that must be overcome before mass-market penetration may occur. We hope that this paper provides an up-to-date analysis and summary of existing and proposed solutions and projects, making it easier for newcomers to stay current.

Brian Sanya Mondoh, Sara M. Johnson, Matthew Green, Aris Georgopoulos

No abstract is available for this record.

Wisnu Uriawan, Youakim Badr, Omar Hasan, Lionel Brunie

International audience

Lavina Pahuja, Ahmad Kamal

Cryptocurrencies continue to captivate businesses and investors despite market fluctuations. The number of crypto users have risen rapidly in the last few years, and alarmingly, many appear to be unaware of the risks involved. These risks aren't confined to market hazards but include very sophisticated cybercrimes related to cryptocurrencies. As cryptocurrencies have become a breeding ground for a variety of cybercrimes, resulting in enormous financial losses, it hinders user adoption limiting the utility of the blockchain technology. It has become crucial to spot such scams and devise intelligent techniques to make this technology a safer place for investors. This study proposes a classification model to handle fake account problem over Ethereum blockchain, and its contribution is multi-faceted; firstly, available imbalanced Ethereum dataset has been balanced to enhance the accuracy of the classification model. Secondly, correlation-based feature selection technique has been applied to retain best discriminating features. Thirdly, an effective machine learning based model has been presented for the identification of fake accounts over the Ethereum system. A comparative study of ten machine learning techniques has been presented consisting of both individual and ensemble classifiers. Experimental results showed that ensemble classifiers appear to yield better performance measures over individual classifiers and among all, LightGbm-based classification model outperformed with 99.2% accuracy.

Fokke Heikamp, Lei Pan, Rolando Trujillo-Rasúa, Sushmita Ruj · 5 authors

No abstract is available for this record.

Francesco Maria De Collibus, Alberto Partida, Matija Piškorec

We analyse the transaction networks of four representative ERC-20 tokens that run on top of the public blockchain Ethereum and can be used as collateral in DeFi: Ampleforth (AMP), Basic Attention Token (BAT), Dai (DAI) and Uniswap (UNI). We use complex network analysis to characterize structural properties of their transaction networks. We compute their preferential attachment and we investigate how critical code-controlled nodes ( smart contracts , SC) executed on the blockchain are in comparison to human-owned nodes ( externally owned accounts , EOA), which are be controlled by end users with public and private keys or by off-blockchain code. Our findings contribute to characterise these new financial networks. We use three network dismantling strategies on the transaction networks to analyze the criticality of smart contract and known exchanges nodes as opposed to EOA nodes. We conclude that smart contract and known exchanges nodes play a structural role in holding up these networks, theoretically designed to be distributed but in reality tending towards centralisation around hubs. This sheds new light on the structural role that smart contracts and exchanges play in Ethereum and, more specifically, in Decentralized Finance (DeFi) networks and casts a shadow on how much decentralised these networks really are. From the information security viewpoint, our findings highlight the need to protect the availability and integrity of these hubs.

Atta ur Rehman Khan, Raja Wasim Ahmad

Recycling of electronic waste is a rapidly growing global issue that requires proper monitoring and tracing of electronic devices and the business transactions between the stakeholders. The majority of current systems that manage electronic devices throughout their supply chain stages are centralized and lack data transparency, immutability, and security. Specifically, such systems are incapable of handling problems like comprehensive coverage of the life cycle of e-products, access control for maintaining data security, reputation-aware selection of stakeholders, and large amounts of data generated during various stages of the supply chain processes. In this paper, we propose a blockchain-based IoT-enabled system for monitoring all post-production business processes, activities, and operations performed on an electronic device. The system is supported by five smart contracts that record the actions of users on the immutable distributed ledger that aid in ensuring that the business processes carried out by the participants are transparent, traceable, and secure. To store large files, such as images of e-waste materials, products, and licenses for stakeholders, we have integrated our system with a distributed storage system. The proposed system is tested on Ethereum blockchain to check the gas consumption of the functions of the smart contracts. The cost and security analysis shows that the proposed system is viable.

Chris Mao

Non-fungible tokens (“NFTs”) are an emerging digital asset that has captured global attention with multi-million-dollar price tags for seemingly basic pixelated JPEG files. In March 2021, British auction house Christie’s sold a digital artwork, ‘Everydays: The First 5,000 Days’, by artist Mike Winkelmann (“Beeple”) for the Ether equivalent of $69.3 million, making it the third-most expensive artwork by a living artist.1 Beeple’s sale was by no means alone—Sotheby's sold an NFT collection of 101 ‘Bored Apes’ for $24.4 million;2 CryptoPunk #7804, one of 10,000 unique ‘CryptoPunk’ NFTs sold for $7.56 million,3 and Twitter founder Jack Dorsey’s first-ever tweet sold for $2.9 million as an NFT.4 NFT sales in the first-half of 2021 have already exceeded $2.5 billion,5 and, as of October 2021, the total value of NFTs on the Ethereum blockchain is estimated to be at least $14.3 billion.6 On one hand, NFTs may be poised to revolutionize creative industries and drastically alter consumer interaction with digital media.7 On the other hand, the NFT market is simultaneously both ripe for speculative investment and vulnerable to criminal activity.8 To date, there appears to be no consensus on the regulation of NFTs, neither from the perspective of generally applicable laws, regulatory capture under existing financial market regulation, nor the implementation of new digital asset laws. This paper attempts to highlight several pertinent dangers of NFTs, from a profound misunderstanding of what an NFT transaction entails, their bubble-like pricing, to various criminal activity concerns. By illustrating how existing laws and regulations may not fully capture nor address these dangers, as well as the potential oversight of NFTs in newly proposed digital asset laws, this paper proposes a categorial approach to regulating NFTs, by reducing the current (and likely future) use-cases of NFTs to their constituent categories and in turn, suggesting the most appropriate regulatory approach to each. Ultimately, given the (potential) wide-ranging use-cases of NFTs, this paper proposes that the NFT’s intended use-case described in broad categorical terms, or more aptly, its underlying reference asset and simultaneous conveyance, or lack thereof, should dictate the regulatory approach.

Carlos Trucíos, James W. Taylor

Abstract Several procedures to forecast daily risk measures in cryptocurrency markets have been recently implemented in the literature. Among them, long‐memory processes, procedures taking into account the presence of extreme observations, procedures that include more than a single regime, and quantile regression‐based models have performed substantially better than standard methods in terms of forecasting risk measures. Those procedures are revisited in this paper, and their value at risk and expected shortfall forecasting performance are evaluated using recent Bitcoin and Ethereum data that include periods of turbulence due to the COVID‐19 pandemic, the third halving of Bitcoin, and the Lexia class action. Additionally, in order to mitigate the influence of model misspecification and enhance the forecasting performance obtained by individual models, we evaluate the use of several forecast combining strategies. Our results, based on a comprehensive backtesting exercise, reveal that, for Bitcoin, there is no single procedure outperforming all other models, but for Ethereum, there is evidence showing that the GAS model is a suitable alternative for forecasting both risk measures. We found that the combining methods were not able to outperform the better of the individual models.

Franck Cassez, Joanne Fuller, Horacio Mijail Antón Quiles

We present a methodology to develop verified smart contracts. We write smart contracts, their specifications and implementations in the verification-friendly language Dafny. In our methodology the ability to write specifications, implementations and to reason about correctness is a primary concern. We propose a simple, concise yet powerful solution to reasoning about contracts that have external calls. This includes arbitrary re-entrancy which is a major source of bugs and attacks in smart contracts. Although we do not yet have a compiler from Dafny to EVM bytecode, the results we obtain on the Dafny code can reasonably be assumed to hold on Solidity code: the translation of the Dafny code to Solidity is straightforward. As a result our approach can readily be used to develop and deploy safer contracts.

Sang Rae Kim

No abstract is available for this record.

Jiří Kukačka, Ladislav Krištoufek

Abstract The driving forces behind cryptoassets’ price dynamics are often perceived as being dominated by speculative factors and inherent bubble-bust episodes. Fundamental components are believed to have a weak, if any, role in the price-formation process. This study examines five cryptoassets with different backgrounds, namely Bitcoin, Ethereum, Litecoin, XRP, and Dogecoin between 2016 and 2022. It utilizes the cusp catastrophe model to connect the fundamental and speculative drivers with possible price bifurcation characteristics of market collapse events. The findings show that the price and return dynamics of all the studied assets, except for Dogecoin, emerge from complex interactions between fundamental and speculative components, including episodes of price bifurcations. Bitcoin shows the strongest fundamentals, with on-chain activity and economic factors driving the fundamental part of the dynamics. Investor attention and off-chain activity drive the speculative component for all studied assets. Among the fundamental drivers, the analyzed cryptoassets present their coin-specific factors, which can be tracked to their protocol specifics and are economically sound.

Zachary Stucke, Theodoros Constantinides, John Cartlidge

Transactions sent to a public blockchain network, such as Ethereum, are initially held in the mempool before they are accepted in a block. While waiting in the mempool, these ‘in-flight’ transactions are publicly visible and vulnerable to front-running attacks, such that malicious parties use information in the transaction for their own gain and at a direct cost to the transaction owner. In this work, we introduce open-source simulation software for identifying and mitigating these attacks on Ethereum blockchains. Designed for education and research, the software introduces simple smart contracts that elaborate front-running vulnerabilities such as displacement attacks, sandwich attacks, and priority gas auctions. Users can run these attacks in a safe environment, monitor the detailed mechanics of attacks, and mitigate attacks using the MEV-geth protocol for in-flight transaction privacy.

Ratna Ekawati, Yandra Arkeman, Suprihatin Suprihatin, Titi Candra Sunarti

The complex supply chain system for the sugar agroindustry supply chain involves many actors, resulting in the asymmetry of information data. It still leads to a lack of data transparency. In the past, data traceability could not be made efficient at every stage, so the record data transaction was not real-time, less accurate, and inefficient coordination between actors. Blockchain is one of the technologies in the 4.0 era as a distributed ledger technology. It can be transparency, traceability, security, immutability, and decentralization. This study aims to design a white sugar agroindustry system based on blockchain technology using the SDLC waterfall stage public. Ethereum is a proof-of-work convention based on the Ropsten test-net on the Metamask wallet. The sugar supply chain system that has been successfully developed allows consumers to track the purchased sugar products based on the transaction hash code sent by the seller. The data listed is the location of the plantation, the quantity (quintal) and quality of sugarcane (percentage), and the purchase price. A web-based blockchain application could be used as a model by national sugar factories to help them make enough sugar food for themselves.

Stefan More, Jakob Heher, Clemens Walluschek

Trust management systems often use registries to authenticate data, or form trust decisions. Examples are revocation registries and trust status lists. By introducing distributed ledgers (DLs), it is also possible to create decentralized registries. A verifier then queries a node of the respective ledger, e.g., to retrieve trust status information during the verification of a credential. While this ensures trustworthy information, the process requires the verifier to be online and the ledger node available. Additionally, the connection from the verifier to the registry poses a privacy issue, as it leaks information about the user's behavior. In this paper, we resolve these issues by extending existing ledger APIs to support results that are trustworthy even in an offline setting. We do this by introducing attestations of the ledger's state, issued by ledger nodes, aggregatable into a collective attestation by all nodes. This attestation enables a user to prove the provenance of DL-based data to an offline verifier. Our approach is generic. So once deployed it serves as a basis for any use case with an offline verifier. We also provide an implementation for the Ethereum stack and evaluate it, demonstrating the practicability of our approach.

Hyoungsung Kim, Hyun‐Sik Kim, Yong-Suk Park

Decentralized Finance (DeFi) is an emerging financial service model based on blockchain technology. DeFi composability denotes the ability for different DeFi services to interact with one another resulting in new forms of financial services. The DeFi ecosystem is largely based on ERC-20 tokens that can represent the value of an asset. Collateralized assets in DeFi composability are locked and additional profit cannot be generated. In this paper, we propose a method to generate profit from locked assets by using ERC-721 Non-Fungible Tokens (NFTs) and perpetual contracts. NFT represents the rights to a certain asset. A perpetual contract is a futures contract that does not have an expiration date. We propose perpetual contract NFT, a new form of NFT that can be used as collateral, which exploits perpetual futures contracts in the cryptocurrency derivatives market. Collateral needs to be provided to back the value of a perpetual contract. If the perpetual contract is minted as NFT, the resulting NFT represents the rights to the perpetual contract and its collateral. Therefore, the perpetual contact NFT itself can be used as collateral for DeFi composability. A proof-of-concept smart contract and a web application for perpetual contract NFT are provided to demonstrate its functionality. To validate the profitability of the perpetual contract NFT using a real-world scenario, we experiment with the position NFT of Uniswap v3 decentralized exchange. The position NFT is a form of perpetual contract NFT. Specifically, we present validation with three types of pools: stablecoins, stablecoin/wrapped tokens pair, and wrapped tokens.

Mr.Vimu Ram Kale Kale, Chandrani Singh, Dr.Sunil Khilari

Non-Fungible Tokens (NFT’s) indicate the creation of a blockchain-based digital certificate of authenticity that is comparable to other virtual crypto assets and currencies. The use of blockchain technology and the exchange of digital currency have become increasingly widespread in recent years. Having said that, as has been shown in recent years, the NFT market is also booming. The very idea of NFT is derived from an Ethereum token standard that aims to separate and recognise each token with its distinct signature being tied with digital attributes. India has also seen increased interest in this digital sector, particularly from the future new-age investors and digital innovators, as a result of the spectacular return on its quickly expanding global market. However, due to the early stage of the NFT ecosystem's growth, India lacks a regulatory legislative framework to oversee such immature digital crypto assets. There are several legal complexities surrounding them, which has made it difficult to determine their legal legitimacy and sanctity. New artists could have a tendency to become lost in this chaotic growth in the absence of comprehensive descriptions. This paper aims to examine the idea of NFT in comparison to bitcoin and copyright, as well as its operational and technological elements. It attempts to examine the legal hazards that affect its operation as well as the potential and difficulties the Indian legal system has with regard to crypto-assets.

Mantas Jurgelaitis, Lina Čeponienė, Rita Butkienė

For the development of blockchain smart contracts, a structured approach based on the principles of the Model Driven Architecture can be beneficial and facilitate the implementation of smart contracts. This paper presents such an approach, which, in combination with Unified Modeling Language (UML) Class and State machine diagrams, allows the smart contract structure and behavior logic to be modeled in several abstraction layers. This paper delves into details on how the model-to-model transformations from the specified Blockchain Platform Independent Model (PIM) with specified state-like behavior can be used to produce a Solidity Platform Specific Model (PSM). Subsequently, we elaborate on how the Solidity PSM is used for Solidity smart contract code generation by employing model-to-text transformations. The paper also demonstrates the process of our proposed transformations and code generation using smart contract code examples from Solidity documentation. Based on the examples, a Blockchain PIM is specified and transformed to Solidity PSM, which is then used for Solidity smart contract code generation. The generated smart contract code is then compiled, deployed on the Ethereum blockchain JavaScript virtual machine, and compared to the original smart contract code in terms of Solidity code metrics, similarity scores, and execution costs. The evaluation results indicate that our approach could be successfully used to model and later generate smart contract code.

Alhonita Yatie

This paper studies the impact of fear, uncertainty and market volatility caused by the Ukraine-Russia war on crypto-assets returns (Bitcoin and Ethereum) and Gold returns. We use the searches on Wikipedia trends as proxies of uncertainty and fear and two volatility indices: S&P500 VIX and the Russian VIX (RVIX).
\nThe results show that Bitcoin, Ethereum and Gold failed as safe havens during this war.