Blockchain Papers

Carlos Bellón Núñez-Mera, Isabel Figuerola–Ferretti

No abstract is available for this record.

Jinhuan Wang, Pengtao Chen, Shanqing Yu, Qi Xuan

Blockchain technology and, in particular, blockchain-based transaction offers us information that has never been seen before in the financial world. In contrast to fiat currencies, transactions through virtual currencies like Bitcoin are completely public. And these transactions of cryptocurrencies are permanently recorded on Blockchain and are available at any time. Therefore, this allows us to build transaction networks (TN) to analyze illegal phenomenons such as phishing scams in blockchain from a network perspective. In this paper, we propose a Transaction SubGraph Network (TSGN) based classification model to identify phishing accounts in Ethereum. Firstly we extract transaction subgraphs for each address and then expand these subgraphs into corresponding TSGNs based on the different mapping mechanisms. We find that TSGNs can provide more potential information to benefit the identification of phishing accounts. Moreover, Directed-TSGNs, by introducing direction attributes, can retain the transaction flow information that captures the significant topological pattern of phishing scams. By comparing with the TSGN, Directed-TSGN indeed has much lower time complexity, benefiting the graph representation learning. Experimental results demonstrate that, combined with network representation algorithms, the TSGN model can capture more features to enhance the classification algorithm and improve phishing nodes' identification accuracy in the Ethereum networks.

Christof Ferreira Torres, Antonio Ken Iannillo, Arthur Gervais, Radu State

In recent years, Ethereum gained tremendously in popularity, growing from a daily transaction average of 10K in January 2016 to an average of 500K in January 2020. Similarly, smart contracts began to carry more value, making them appealing targets for attackers. As a result, they started to become victims of attacks, costing millions of dollars. In response to these attacks, both academia and industry proposed a plethora of tools to scan smart contracts for vulnerabilities before deploying them on the blockchain. However, most of these tools solely focus on detecting vulnerabilities and not attacks, let alone quantifying or tracing the number of stolen assets. In this paper, we present Horus, a framework that empowers the automated detection and investigation of smart contract attacks based on logic-driven and graph-driven analysis of transactions. Horus provides quick means to quantify and trace the flow of stolen assets across the Ethereum blockchain. We perform a large-scale analysis of all the smart contracts deployed on Ethereum until May 2020. We identified 1,888 attacked smart contracts and 8,095 adversarial transactions in the wild. Our investigation shows that the number of attacks did not necessarily decrease over the past few years, but for some vulnerabilities remained constant. Finally, we also demonstrate the practicality of our framework via an in-depth analysis on the recent Uniswap and Lendf.me attacks.

Yuxin Huang, Ben Wang, Yinggui Wang

Abstract With the rapid development of blockchain technology and the increasing demand for partial decentralization of the Internet, the application of underlying technology based on blockchain has been widely concerned. Along with decentralized objects, the programmable financial system represented by Ethereum has been gotten more and more attention. However, smart contract sacrifices its security to improve decentralization. So Ethereum has the fatal problem with a large number of users, and negligence of users in coding contract threatens the entire Ethereum network. Therefore, this paper aims to research and expand applications of smart contract usage in Ethereum blockchain. We start from basic concepts to define structure of Ethereum, and then discuss security issues on smart contract. In the end, an optimized smart contract application of auction is implemented, which is useful for further consolidating and understanding of smart contract in practice.

Mudabbir Kaleem, Weidong Shi

Smart contracts are dependent on oracle systems for their adoption and usability. We perform an empirical study of oracle systems' usage trends and adoption metrics to provide better insight into the health of the smart contract ecosystem. We collect ChainLink usage data on the Ethereum network using a modified Ethereum client and running a full node. We analyze the collected data and present our findings and insights surrounding the usage trends, adoption metrics, oracle pricing and service quality associated with ChainLink on the Ethereum network.

Christof Ferreira Torres, Ramiro Daniel Camino, Radu State

Ethereum prospered the inception of a plethora of smart contract applications, ranging from gambling games to decentralized finance. However, Ethereum is also considered a highly adversarial environment, where vulnerable smart contracts will eventually be exploited. Recently, Ethereum's pool of pending transaction has become a far more aggressive environment. In the hope of making some profit, attackers continuously monitor the transaction pool and try to frontrun their victims' transactions by either displacing or suppressing them, or strategically inserting their transactions. This paper aims to shed some light into what is known as a dark forest and uncover these predators' actions. We present a methodology to efficiently measure the three types of frontrunning: displacement, insertion, and suppression. We perform a large-scale analysis on more than 11M blocks and identify almost 200K attacks with an accumulated profit of 18.41M USD for the attackers, providing evidence that frontrunning is both, lucrative and a prevalent issue.

Shanqing Yu, Jie Jin, Yunyi Xie, Jie Shen · 5 authors

With the rapid growth of blockchain, an increasing number of users have been attracted and many implementations have been refreshed in different fields. Especially in the cryptocurrency investment field, blockchain technology has shown vigorous vitality. However, along with the rise of online business, numerous fraudulent activities, e.g., money laundering, bribery, phishing, and others, emerge as the main threat to trading security. Due to the openness of Ethereum, researchers can easily access Ethereum transaction records and smart contracts, which brings unprecedented opportunities for Ethereum scams detection and analysis. This paper mainly focuses on the Ponzi scheme, a typical fraud, which has caused large property damage to the users in Ethereum. By verifying Ponzi contracts to maintain Ethereum's sustainable development, we model Ponzi scheme identification and detection as a node classification task. In this paper, we first collect target contracts' transactions to establish transaction networks and propose a detecting model based on graph convolutional network (GCN) to precisely distinguishPonzi contracts. Experiments on different real-world Ethereum datasets demonstrate that our proposed model has promising results compared with general machine learning methods to detect Ponzi schemes.

Ch. Rupa, Divya Midhunchakkaravarthy, Mohammad Kamrul Hasan, Hesham Alhumyani · 5 authors

The use of advanced technologies has increased drastically to maintain any sensitive records related to education, health, or finance. It helps to protect the data from unauthorized access by attackers. However, all the existing advanced technologies face some issues because of their uncertainties. These technologies have some lapses to provide privacy, attack-free, transparency, reliability, and flexibility. These characteristics are essential while managing any sensitive data like educational certificates or medical certificates. Hence, we designed an Industry 5.0 based blockchain application to manage medical certificates using Remix Ethereum blockchain in this paper. This application also employs a distributed application (DApp) that uses a test RPC-based Ethereum blockchain and user expert system as a knowledge agent. The main strength of this work is the maintenance of existing certificates over a blockchain with the creation of new certificates that use logistic Map encryption cipher on existing medical certificates while uploading into the blockchain. This application helps to quickly analyze the birth, death, and sick rate as per certain features like location and year.

Lennart Ante

The market for non-fungible tokens (NFTs), transferrable and unique digital assets on public blockchains, has received widespread attention and experienced strong growth since early 2021. This study provides an introduction to NFTs and explores the 14 largest submarkets using data from the Ethereum blockchain between June 2017 and May 2021. The analyses rely on (a) the number of NFT sales, (b) the dollar volume of NFT trades and (c) the number of unique blockchain wallets that traded NFTs. Based on the number of transactions and wallets, the Ethereum-based NFT market peaked at the end of 2017 due to the success of the CryptoKitties project. As of 2021, fewer transactions occur but the traded value is much higher. We find that NFT submarkets are cointegrated and feature various causal short-run connections between them. The success or adoption of younger NFT projects is influenced by that of more established markets. At the same time, the success of newer markets has an impact on the more established projects. The results contribute to the overall understanding of the NFT phenomenon as an emerging asset class and suggest that NFT markets are immature or even inefficient.

Lennart Ante

Non-fungible tokens (NFTs) are transferrable rights to digital assets, such as art, in-game items, collectables, or music. The phenomenon and its markets have grown significantly since early 2021. We investigate the interrelationships between NFT sales, NFT users (unique active blockchain wallets), and the pricing of Bitcoin (BTC) and Ether (ETH). Using daily data between January 2018 and April 2021, we show that a Bitcoin price shock triggers an increase in NFT sales. Also, Ether price shocks reduce the number of active NFT wallets. The results suggest that (larger) cryptocurrency markets affect the growth and development of the (smaller) NFT market, but there is no reverse effect.

Naipeng Dong, Babu Pillai, Guangdong Bai, Mark Utting

Abstract Distributed ledger technology (DLT) emerged as a disruptive force towards decentralization and has expanded beyond its origins in cryptocurrencies like Bitcoin. At the heart of DLT is an infrastructure that replicates data across multiple network nodes, enabling new opportunities for data integrity, transparency, and trust in distributed business environments. In recent years, technological advances have improved the performance, energy efficiency, and functionality of DLT, expanding its application to various sectors such as finance, healthcare, trade and media, logistics, and the public sector. Despite these advances, adoption remained limited, with notable successes primarily in areas such as decentralized finance and non-fungible tokens. By placing DLT within the historical development of ledgers and distributed databases, this Fundamental provides a business-oriented foundation for structuring and assessing DLT-based solutions. It presents, a unified definition covering blockchain technologies, describes the key characteristics of DLT, and offers a structured analysis of its potential and challenges using a multi-dimensional interaction framework. Ultimately, it serves to carve out where and under which conditions DLT infrastructures add value for interorganizational relationships.

Ahmad Musamih, Khaled Salah, Raja Jayaraman, Junaid Arshad · 7 authors

Healthcare supply chains are complex structures spanning across multiple organizational and geographical boundaries, providing critical backbone to services vital for everyday life. The inherent complexity of such systems can introduce impurities including inaccurate information, lack of transparency and limited data provenance. Counterfeit drugs is one consequence of such limitations within existing supply chains which not only has serious adverse impact on human health but also causes severe economic loss to the healthcare industry. Consequently, existing studies have emphasized the need for a robust, end-to-end track and trace system for pharmaceutical supply chains. Therein, an end-to-end product tracking system across the pharmaceutical supply chain is paramount to ensuring product safety and eliminating counterfeits. Most existing track and trace systems are centralized leading to data privacy, transparency and authenticity issues in healthcare supply chains. In this article, we present an Ethereum blockchain-based approach leveraging smart contracts and decentralized off-chain storage for efficient product traceability in the healthcare supply chain. The smart contract guarantees data provenance, eliminates the need for intermediaries and provides a secure, immutable history of transactions to all stakeholders. We present the system architecture and detailed algorithms that govern the working principles of our proposed solution. We perform testing and validation, and present cost and security analysis of the system to evaluate its effectiveness to enhance traceability within pharmaceutical supply chains.

Khaldoun Besoul, Ayman Nayef Al Halaybeh, Safwan Al Salaimeh

There are many changes related to the development of the Internet and e-business, which significantly impact the logistics sector's service sectors. Electronic logistics is not a new segment or a new standard in the classification process for logistics companies. It leads to the development and improvement of a wide range of logistics services. Blockchain technologies can be used to improve and develop services, which are an integral part of this evolution. This research sheds light on the mechanism and application of these technologies in logistics services and the extent of their impact on logistical activities where some technical aspects of Blockchain are studied in detail, including smart contracts that use the Ethereum platform as an example.

Sandi Rahmadika, Muhammad Firdaus, Seolah Jang, Kyung-Hyune Rhee

No abstract is available for this record.

Branimir Cvitko Cicvarić

Many models have been developed to model, estimate and forecast financial time series volatility, amongst which are the most popular autoregressive conditional heteroscedasticity (ARCH) model introduced by Engle (1982) and generalized autoregressive conditional heteroscedasticity (GARCH) model introduced by Bollerslev (1986). The aim of this paper is to determine which type of ARCH/GARCH models can fit the best following cryptocurrencies: Ethereum, Neo, Ripple, Litecoin, Dash, Zcash and Dogecoin. It is found that the EGARCH model is the best fitted model for Ethereum, Zcash and Neo, PARCH model is the best fitted model for Ripple, while for Litecoin, Dash and Dogecoin it depends on the selected distribution and information criterion.

Mikel Cortes-Goicoechea, Luca Franceschini, Leonardo Bautista-Gomez

Scalability is a common issue among the most used permissionless blockchains, and several approaches have been proposed accordingly. As Ethereum is set to be a solid foundation for a decentralized Internet web, the need for tackling scalability issues while preserving the security of the network is an important challenge. In order to successfully deliver effective scaling solutions, Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), which implements sharding. As the change of consensus mechanism is an extremely delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. For this, a specification has been developed and multiple groups have implemented clients to run the new protocol. In this work, we analyse the resource usage behaviour of different clients running as Eth2 nodes, comparing their performance and analysing differences. Our results show multiple network perturbations and how different clients react to it.

Novak Kaluđerović, Thorsten Kleinjung, Dušan Kostić

Linear Legendre pseudorandom functions were introduced in 1988 by Damgrd, and higher degree generalisations were introduced by Russell and Shparlinski in 2004. We present new key recovery methods that improve the state of the art for both cases. For degree r 3 we give an attack that runs in time O( p r -3 ) after O( p 3 ) precomputation for the most relevant high degree case; it is based on the action of the group of Mbius transformations on degree r polynomials. For r < 3 we give an O( p r/2 ) attack with O( p r/4 ) oracle queries. In the linear case we recovered the keys for the 64, 74 and 84-bit prime Ethereum challenges, being the first to solve the 84-bit case.

Klender Aimer Cortéz Alejandro, Martha del Pilar Rodríguez-García, Samuel Mongrut

In this paper, we compare the predictions on the market liquidity in crypto and fiat currencies between two traditional time series methods, the autoregressive moving average (ARMA) and the generalized autoregressive conditional heteroskedasticity (GARCH), and the machine learning algorithm called the k-nearest neighbor (KNN) approach. We measure market liquidity as the log rates of bid-ask spreads in a sample of three cryptocurrencies (Bitcoin, Ethereum, and Ripple) and 16 major fiat currencies from 9 February 2018 to 8 February 2019. We find that the KNN approach is better suited for capturing the market liquidity in a cryptocurrency in the short-term than the ARMA and GARCH models maybe due to the complexity of the microstructure of the market. Considering traditional time series models, we find that ARMA models perform well when estimating the liquidity of fiat currencies in developed markets, whereas GARCH models do the same for fiat currencies in emerging markets. Nevertheless, our results show that the KNN approach can better predict the log rates of the bid-ask spreads of crypto and fiat currencies than ARMA and GARCH models.

Mikel Cortes-Goicoechea, Leonardo Bautista-Gomez

Achieving the equilibrium between scalability, sustainability and security has prevailed as the ideal solution for decentralized blockchain applications over the last years. Several approaches have been proposed being Ethereum a solid proposal among them. Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), implementing Sharding and introducing the Proof-of-Stake (PoS). As the change of consensus mechanism is a delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. The implementation of the latest has been stated with the recent launch of the Eth2 main net. In this work, we introduce an Eth2 network monitor tool, called Armiarma, used to generate a complete analysis of the p2p network of the Eth2 main net. In this paper, we present some of the results of what this Eth2 network monitor can achieve.

Mikel Cortes-Goicoechea, Leonardo Bautista-Gomez

Achieving the equilibrium between scalability, sustainability, and security while keeping decentralization has prevailed as the target solution for decentralized blockchain applications over the last years. Several approaches have been proposed by multiple blockchain teams to achieve it, Ethereum being among them. Ethereum is on the path of a major protocol improvement called Ethereum 2.0 (Eth2), implementing Sharding and introducing the Proof-of-Stake (PoS). As the change of consensus mechanism is a delicate matter, this improvement will be achieved through different phases, the first of which is the implementation of the Beacon Chain. As Ethereum1, Eth2 relies on a decentralized peer-to-peer (p2p) network for the message distribution. Up to date, we estimate that there are around 5.000 nodes in the Eth2 main net geographically distributed. However, the topology of this one still prevails unknown. In this paper, we present the results obtained from the analysis we performed on the Eth2 p2p network. Describing the topology of the network, as possible hazards that this one implies.

Vandana Dangi

Calendar anomalies as the seasonal tendencies in stock returns are the signal of irregular behaviour of stock markets. These anomalies have been comprehensively studied in many matured as well as emerging stock markets. But there is lack of exploration of calendar anomalies in the cryptocurrency market. So, the present treatise is an attempt to fill this lacuna by studying day of the week effect on cryptocurrencies' returns and volatility. This study is based on the prices of eight cryptocurrencies (viz. Bitcoin, EOS, Ethereum, Bitcoin Cash, Litecoin, Tether, XRP and Stellar) for a period starting from July 2017 and up to March 2020. The series of daily and day-wise returns were initially studied for stationarity using Ng-Perron tests and augmented Dickey–Fuller test. The results from these tests confirmed that the cryptocurrencies' return series are stationary. The day of the week effect on cryptocurrencies returns was studied by introducing the dummies for each day of the week in the ordinary least square regression equation. The residuals from the ordinary least square regression equation were tested for ARCH effect using Engle's ARCH test. The results from the test confirmed the presence of ARCH effect in all series. The GARCH (1,1) model and PARCH model were further applied to account for ARCH effect and these models confirmed the presence of the day of the week effect in all the cryptocurrencies' returns and volatility except for day of week effect in Bitcoin and Tether returns. So, the significant day of the week effect was present in all cryptocurrencies' returns and volatility but the significant day of the week effect was absent in Bitcoin's returns and Tether's returns. These findings of significant day effect may help the existing and potential investors in taking investment decision in contemporary scenario of no ban in cryptocurrency market in India.

Zulfiqar Ali Khan, Akbar Siami Namin

Smart contract (SC) is an extension of BlockChain technology. Ethereum BlockChain was the first to incorporate SC and thus started a new era of crypto-currencies and electronic transactions. Solidity helps to program the SCs. Still, soon after Solidity's emergence in 2014, Solidity-based SCs suffered many attacks that deprived the SC account holders of their precious funds. The main reason for these attacks was the presence of vulnerabilities in SC. This paper discusses SC vulnerabilities and classifies them according to the domain knowledge of the faulty operations. This classification is a source of reminding developers and software engineers that for SC's safety, each SC requires proper testing with effective tools to catch those classes' vulnerabilities.

Junhoo Park, Hyekjin Kim, Geunyoung Kim, Jae‐Cheol Ryou

As blockchain-based applications and research such as cryptocurrency increase, an oracle problem to bring external data in the blockchain is emerging. Among the methods to solve the oracle problem, a method of configuring oracle based on TLS, an existing internet infrastructure, has been proposed. However, these methods currently have the disadvantage of not supporting privacy protection for external data, and there are limitations in configuring the process of a smart contract based on external data verification for automation. To solve this problem, we propose a framework consisting of middleware of external source server, data prover, and verification contract. The framework converts the data signed in the web server into a proof that the owner can prove with zk-SNARKs and provides a smart contract that can verify this. Through these procedures, data owners not only protect their privacy by proving themselves, but they can also automate on-chain processing through smart contract verification. For the proposed framework, we create a proof using libsnark for server data and show the performance and cost to verify with Solidity the smart contract language of the Ethereum platform.

Ayşe Meti̇n Karakaş, Aslıhan DEMİR, Sinan Çalık

In recent years, there has been a growing interest on the combination of copulas with mixture model. The combination of vine copulas incorporated into a finite mixture model is also helpful to capture secret structures in a data. This paper aims to examine the relationship between bitcoin and other crypto money indicators with the CD Vine Copula Approach method. In the study, we use closing prices of Bitcoin, Bitcoin Cash, Ethereum, Litecoin, and IOT. The results show that there is a strong dependence between bitcoin and prominent financial indicators.