In this study, we empirically examine the existence and dynamics of herding in the burgeoning market of non-fungible tokens (NFT). We find supportive evidence of the existence of herding in this market, the dynamics of which appears to be event-driven. A large inflow of newcomers or inexperienced investors can serve as a trigger of herding. Meanwhile, unlike in traditional asset markets, herding in NFT markets does not appear to happen across submarkets.
Proof of Stake powered blockchains account for general trends in existing consensus mechanisms. However, existing PoS protocols are vulnerable to the nothing at stake and long range attacks, which allow attackers to gain unfair shares based on costless simulations and malicious sale information. In a decentralized setting, these securities are limited as each node is unregulated. To address these problems, we introduce a proof-of-hardware-stake (PohS) consensus mechanism and a regulatory mechanism based on a consortium blockchain. Our approach is implemented in a sharding blockchain to scale the consensus. Since any node on the network cannot fake information, the blockchain trustless won not be decreased by the reliance on a consortium blockchain. Under the competing rule of PohS consensus mechanism, adversaries can issue the long range attack with at most$10^{-3}$probability. The regulatory mechanism implements the regulation of costless simulations at the nothing stake attack. We prove that our design is secure (e.g.,51% and selfish mining) against adversarial stakes less than 51% by adopting the square root of stakes for competition. Our proof also highlights the security of double-spending and long range attacks. Simulations are conducted to compare the efficiency of our approach with Ethereum and Ouroboros.
Jan 1, 2022·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Tom Barbereau, Reilly Smethurst, Orestis Papageorgiou, Alexander Rieger · 5 authors
Bitcoin and Ethereum are frequently promoted as decentralized, but developers and academics question their actual decentralization. This motivates further experiments with public permissionless blockchains to achieve decentralization along technical, economic, and political lines. The distribution of tokenized voting rights aims for political decentralization. Tokenized voting rights achieved notoriety within the nascent field of decentralized finance (DeFi) in 2020. As an alternative to centralized crypto-asset exchanges and lending platforms (owned by companies like Coinbase and Celsius), DeFi developers typically create non-custodial projects that are not majority-owned or managed by legal entities. Holders of tokenized voting rights can instead govern DeFi projects. To scrutinize DeFi’s distributed governance strategies, we conducted a multiple-case study of non-custodial, Ethereum-based DeFi projects: Uniswap, Maker, SushiSwap, Yearn Finance, and UMA. Our findings are novel and surprising: quantitative evaluations of DeFi’s distributed governance strategies reveal a failure to achieve political decentralization.
A blockchain is a list of data blocks as a publicly distributed ledger, which are linked together using cryptography. By allowing Turing-complete programming languages to implement smart contracts, recent blockchains such as Ethereum can reduce needs in trusted intermediators, arbitrations and enforcement costs. However, subtle errors in smart contracts have induced an enormous financial loss—for examples, the DAO attack, Parity multisignature wallet attacks, and integer underflow/overflow attacks. To identify such errors in smart contracts, various researches are performed, which are based on static analysis and theorem proving. However, they only support inspection for pre-defined error patterns, or they cannot explore the whole searching space exhaustively or be fully automatic. Hence, in this paper, we propose a novel formal verification technique to analyze blockchain smart contracts by using ATL model checking. In our methodology, we represent the interaction between users and smart contracts into a two-player game and verify properties we want to check using MCMAS that is an efficient ATL model checker for multi-agent systems. Moreover, we present three case studies to show that our proposal can successfully identify subtle flaws in real world smart contracts.
Increasingly frequent illegal transactions hinder the security of Ethereum transactions, and the anonymity of electronic money makes it difficult to track and analyze problems. In this paper, the transaction data of the Ethereum trading platform is used as the data source, and the marked illegal account and the unmarked normal account data set are used as the training set. Based on the CatBoost algorithm, the overall prediction of the various types of illegal accounts is made. The process adopts multiple cross-validation, the accuracy of the established algorithm model prediction reached 94.07%, and the evaluation metric of the area under the curve of the receiver reached 0.9846. The proposed scheme accurately predicts illegal behaviors on the Ethereum trading platform and effectively improves the blockchain-based trading environment.
G. Ravikumar, K. Venkatachalam, Mehedi Masud, Mohamed Abouhawwash
Recently internet of medical things (IoMT) act as a smart doctor using sensor wearable’s device in human body. This smart doctor device senses necessary medical data from human and transfer via network immediately to physician. It is important to transfer sensitive data very securely. Blockchain becomes trending technology to provide high security to both end users in the network. Traditionally security structure is relying on cryptographic techniques which is very expensive and takes more time in securely transmitting data. To overcome this issue, this paper builds a cost effective, blockchain with IoMT using fog-cloud computing. The aim of research is to provide cost effective healthcare services in the present system. This study develops an IoMT systems using fusion of scheduling techniques in blockchain. We propose a Smart Contract with Function Based Cost Efficient Task Scheduling (FTS-SCON) algorithm in blockchain framework. The proposed algorithm uses functions to schedule the task in the blockchain which is cost effective. With the help of cryptography based Blockchain schemes with smart contracts enables consistency and validation of data with symmetric cryptography. Simulation results shows the proposed outperform all existing elements regarding data security, validation by 10%, and cost of application execution by 30% in IoMT.
Standardized Ethereum tokens, e.g., ERC-20 tokens, have become the norm in fundraising (through ICOs) and kicking off blockchain-based DeFi applications. However, they require the user's wallet to hold both tokens and ether to pay the gas fee for making a transaction. This makes for a cumbersome user experience, and complicates, from the user perspective, the process of transitioning to a different smart-contract enabled blockchain, or to a newly launched blockchain. We formalize, instantiate, and analyze in a composable manner a system that we call Etherless Ethereum Tokens (in short, EETs), which allows the token users to transact in a closed-economy manner, i.e., having only tokens on their wallet and paying any transaction fees in tokens rather than Ether/Gas. In the process, we devise a methodology for capturing Ethereum token-contracts in the Universal Composability (UC) framework, which can be of independent interest.
Pedro Antonino, Juliandson Ferreira, Augusto Sampaio, A. W. Roscoe
Smart contract evolution is crucial for the success of decentralized applications, and current methods and processes are not well suited to handle these drivers of change, as the knowledge about the software is predominantly stored in informal documents. In addition, they are the building blocks of the ”code is law” paradigm: the smart contract’s code indisputably describes how its assets are to be managed - once it is created, its code is typically immutable. Faulty smart contracts present the most significant evidence against the practicality of this paradigm; they are well-documented and resulted in assets worth vast sums of money being compromised. To address this issue, the Ethereum community proposed (i) tools and processes to audit/analyse smart contracts, and (ii) design patterns implementing a mechanism to make contract code mutable. Individually, (i) and (ii) only partially address the challenges raised by the ”code is law” paradigm. In this work, we combine elements from (i) and (ii) to create a systematic framework that moves away from ”code is law” and gives rise to a new ”specifica- tion is law” paradigm. It allows contracts to be created and upgraded but only if they meet a corresponding formal specification. We explain how formal verification techniques can be used to ensure safety properties of smart contracts during their evolution. Although formal verification methods have the potential of being used in several application fields, we focus on ensuring compliance with its specifications. The process consists of three phases: Formal requirements specification, verification, and deployment. All steps are planned and executed in an integrated way and together they form a framework capable of fostering safe evolution and make it more reliable and secure. The framework is centered around a trusted deployer: an off-chain service that formally verifies and enforces specification conformance. We have proto- typed this framework, and investigated its applicability to contracts implementing three widely used Ethereum standards: the ERC20 Token Standard, ERC3156 Flash Loans and ERC1155 Multi Token Standard, with promising results.
Rateb Jabbar, Eya Dhib, Ahmed Ben Said, Moez Krichen · 7 authors
The use of Blockchain technology has recently become widespread. It has emerged as an essential tool in various academic and industrial fields, such as healthcare, transportation, finance, cybersecurity, and supply chain management. It is regarded as a decentralized, trustworthy, secure, transparent, and immutable solution that innovates data sharing and management. This survey aims to provide a systematic review of Blockchain application to intelligent transportation systems in general and the Internet of Vehicles (IoV) in particular. The survey is divided into four main parts. First, the Blockchain technology including its opportunities, relative taxonomies, and applications is introduced; basic cryptography is also discussed. Next, the evolution of Blockchain is presented, starting from the primary phase of pre-Bitcoin (fundamentally characterized by classic cryptography systems), followed by the Blockchain 1.0 phase, (characterized by Bitcoin implementation and common consensus protocols), and finally, the Blockchain 2.0 phase (characterized by the implementation of smart contracts, Ethereum, and Hyperledger). We compared and identified the strengths and limitations of each of these implementations. Then, the state of the art of Blockchain-based IoV solutions (BIoV) is explored by referring to a large and trusted source database from the Scopus data bank. For a well-structured and clear discussion, the reviewed literature is classified according to the research direction and implemented IoV layer. Useful tables, statistics, and analysis are also presented. Finally, the open problems and future directions in BIoV research are summarized.
Dynamic Searchable Symmetric Encryption (DSSE) is a practical cryptographic primitive that assists servers to provide search and update functionalities in the ciphertext domain. Recent work on DSSE schemes has focused on the direction of forward-privacy, requiring that newly added files cannot be linked to previously query results. However, due to the complexity of forward-privacy updates, existing schemes can only address an honest-but-curious server. It is difficult to verify updated results while preserving forward-privacy. In this paper, we explore how blockchain techniques can help us achieve a verifiable and forward-privacy DSSE scheme. Our scheme resorts to the emerging smart contract as a trusted platform to store digests for public result verification, and carefully crafts dynamic query protocols to enable encrypted search with forward-privacy. In our design, indexes are collocated with encrypted files and stored at storage-servers, which makes the blockchain light-weighted and search operations more efficient. Moreover, we propose a hybrid index design to support efficient files deletion. By using our blockchain-assisted primitive, the property collision between dynamic result verification and forward-privacy can be solved. We formally analyze the security strengths and provide the prototype implementation on Ethereum. Experiment results demonstrate the feasibility and usability of our blockchain-assisted DSSE scheme.
This paper investigates the market reaction to large positive or negative liquidity shocks on the value of tokens traded on decentralized exchanges (DEXes) on the Ethereum blockchain. Automated market makers (AMMs) and constant product markets provide transparent and decentralized ways to directly swap two blockchain tokens for each other via the use of liquidity pools. Using trade-by-trade data of 2.77 million swaps of 14 different tokens traded on Uniswap v2, v3 and SushiSwap, we find that the size of sell orders significantly correlates with negative future token returns, while buy size positively correlates with future token returns. Using an event study approach, we quantify the market reaction of unusually large sell and buy orders (top 1% percentile) and identify that the market reaction outweighs the economic value of the event by a factor of -7.4 for sell orders and +4.4 for buy orders over a short-span trading window. In the case of sell orders, a high proportion of the abnormal return is already realized before the event, which indicates informed trading in the form of arbitrage or frontrunning via Miner Extractable Value (MEV). Looking at individual crypto assets, we find a mean reassessment of token value following short sales of up to 0.79% within just one follow-up trade (buy orders up to 0.50%). The findings indicate that price shocks may have a signaling effect but also that market capitalization may be an insufficient metric for assessing the liquidity and valuation of (inefficient) crypto assets. The results suggest multiple challenges for investor protection in decentralized finance (DeFi) markets.
A smart contract is a computer program which is automatically executed with some conditional statements such as “if/then”. Since smart contracts can include some vulnerable program codes, smart contract exploit was recently highlighted as one of the severe threats to Ethereum blockchain. As one of the efficient and effective smart contract vulnerability detection methods, deep learning methods have been studied due to the fast detection speed and the high detection accuracy. Recently, the deep learning methods using convolutional neural network(CNN) have actively studied to classify images transformed from smart contracts into vulnerable or invulnerable. However, while simply transforming a smart contract into an image and analyzing, semantics and context of the smart contract are ignored to cause false detection alarms. To detect vulnerable smart contracts while maintaining their semantics and context, we propose a new code-targeted CNN architecture, called CodeNet. To improve the performance of CodeNet, we also design a data pre-processing procedure, where a smart contract is transformed into an image while maintaining locality. From the experimental results under various types of vulnerabilities, the proposed CodeNet-based vulnerability detection method shows the good-enough detection performance and detection time compared to well-known state-of-the-art vulnerability detection tools.
Leonardo H.S. Fernandes, Elie Bouri, JOSÉ W. L. SILVA, Lucian Bejan · 5 authors
We examine the price disorder and market efficiency of five cryptocurrencies (Bitcoin, BNB, Cardano, Ethereum, and XRP) before and during COVID-19 pandemic period. Using permutation entropy and Fisher information measure (FIM), we construct the Shannon-Fisher causality plane (SFCP) to map these cryptocurrencies and their respective locations in a two-dimensional plane and then apply sliding time window approach to study the temporal evolution of efficiency. All cryptocurrencies exhibit high but slightly varying informational efficiency during both periods. Cardano is the most efficient. These results might point to the increasing maturity and lower potential for price predictability, which matter to cryp-tocurrencies usage for liquidity risk diversification strategy.
Francisco Javier García-Corral, José Antonio Cordero-García, Jaime de Pablo Valenciano, Juan Uribe-Toril
With the development of new technologies, some concepts become relevant in the economic area, as is the case with cryptocurrencies, in general, or Bitcoin and Ethereum, in particular. Due to the impact of these tools, a detailed bibliometric study that allows us to obtain all information about cryptocurrencies must be conducted. This study will help scientific production by specifying the development and lines of related research that have been followed and are currently being followed. We have used Tableau, R (Bibliometrix R Package), and VOSviewer software to analyze the information. These have been combined to create and review unified metadata from the Web of Science (WoS) and Scopus databases. The bibliometric analysis shows 771 articles on the WoS database and 648 articles on Scopus published between 2010 and early 2019. They present the most relevant articles, research areas, countries, institutions, authors, journals, and trends during the last few years. In conclusion, the number of publications has grown in the last 3 years. The analysis shows the evolution of blockchain technology used in this type of cryptocurrency. The review of this period marks a possible end to the historical part of cryptocurrencies, thereby opening the current topic to its multiple applications.
Cryptocurrencies and decentralized finance (DeFi) are reshaping how value is created, exchanged, and governed, and this chapter positions them as more than speculative instruments by reading them as an emerging financial infrastructure. In an ideal digital economy, programmable money supports low-friction transactions, broad participation, and transparent rules, while users retain control without surrendering trust to dominant intermediaries. Yet that ideal remains unevenly realized: markets still absorb extreme volatility, smart contracts still fail under adversarial conditions, and regulatory responses still oscillate between accommodation and restriction, leaving innovation and consumer protection in tension. Prior scholarship has mapped the monetary properties of Bitcoin as a scarcity-driven “digital store of value,” and it has framed Ethereum as the computational base layer that makes smart contracts—and therefore DeFi—possible. Studies on decentralized exchanges, lending protocols, automated market makers, and liquidity incentives have shown how 328 intermediated functions can be replicated through code, but they have also documented exploit patterns, oracle manipulation, governance capture, and composability risks that propagate across protocols. What remains underdeveloped is an integrated account that connects asset design, protocol architecture, and institutional constraints into a single explanatory model. To address this gap, the study advances a sociotechnical framework that links blockchain trust primitives with financial intermediation theory. By tracing how cryptocurrencies supply liquidity and collateral to DeFi, while DeFi amplifies token utility and systemic exposure, the chapter clarifies the conditions under which decentralized finance can mature into a resilient, inclusive financial ecosystem.
Yujia Tang, Chang Xu, Can Zhang, Yan Wu · 5 authors
Abstract Tornado Cash, the most popular non-custodial coin mixer on Ethereum, is widely used to protect the privacy of addresses. However, some inappropriate transaction behaviors in Tornado Cash mixing mechanism lead to the risk of privacy leakage. More specifically, the malicious attackers can link multiple addresses of the same users according to the transaction data. Motivated by the above problem, this paper systematically analyzes the privacy issues of Tornado Cash for the first time. In this paper, we give the macroscopic analysis of Tornado Cash based on the on-chain data and formalize two types of transaction patterns. Focus on the presented transaction patterns, we propose three heuristic clustering rules to link the users’ addresses, which reduce the size of users’ anonymity set. Finally, we perform the experiment on real Tornado Cash transaction data to describe the effectiveness of the proposed clustering rules.
Web3 and DeFi are widely advocated as innovations for greater financial inclusion and democratization. We assemble the most comprehensive dataset to date on the largest Web3 ecosystem and use large-scale computing to investigate the claim. We discuss Ethereum's network structure, time trends, and distributions of transactions, mining, and ownership. Mining income and Ether ownership are concentrated in a few nodes, even after excluding exchange and mining pool wallets, with inequalities more exacerbated than observed in the real economy. Network activities are dominated by large transactions, shifting from peer-to-peer to user-DApps/DeFi interactions, and from Ether-based to ERC-20-token-based. High percentage transaction fees, congestion-induced gas-price fluctuation, suboptimal reserve setting, and large return volatility of tokens disproportionally harm small, unsophisticated, and new nodes, with high failure rates hurting all users. Finally, we present causal evidence that base-fee burning mechanisms (e.g., EIP-1559) and airdrop programs (e.g., OmiseGo Airdrop) promote inclusion and equality through monetary redistribution.