With the onset of the COVID-19 pandemic and the succession of its waves, the transmission of this disease and the number of deaths caused by it have been increasing. Despite the various vaccines, the COVID-19 virus is still contagious and dangerous for affected people. One of the remedies to this is precaution, and particularly social distancing. In the same vein, this paper proposes a remote voting system, which has to be secure, anonymous, irreversible, accessible, and simple to use. It therefore allows voters to have the possibility to vote for their candidate without having to perform the operation on site. This system will be used for university elections and particularly for student elections. We propose a platform based on a decentralized system. This system will use two blockchains communicating with each other: the public Ethereum blockchain and the private Quorum blockchain. The private blockchain will be institution-specific. All these blockchains send the necessary data to the public blockchain which manages different data related to the universities and the ministry. This system enables using encrypted data with the SHA-256 algorithm to have both security and information security. Motivated by the high energy consumption of blockchain and by the performance improvements in low-power, a test is performed on a low-power embedded platform Raspberry PI4 showing the possibility to use the Blockchain with limited resources.
Flash Loan, a popular lending service in the decentralized finance (DeFi) ecosystem, allows users to borrow a large number of virtual assets without any collateral. It can be leveraged to support many financial activities (such as arbitrage, collateral swap, self-liquidation, etc.), but unfortunately, it is often abused for malicious intent. One example of abusing flash loan servicing is to simultaneously sell and buy the same crypto currency on the same exchange to mislead the market, aka wash trading. It can manipulate the crypto currency market at a very low cost (anecdotally average around 0.033 ETH gas fee for each transaction on Ethereum mainnet), thereby dramatically damaging the stability and fairness of the market. More seriously, attackers can amplify the market impact by borrowing more assets from Flash Loan platforms. Until now, there has been little attention paid to Flash-Loan-based wash trading, but meanwhile, we have started to witness significant wash trading activities using Flash Loan. In this research, we analyze the properties of Flash-Loan-based wash trading in detail and propose a heuristic-based detection method. The real-world Flash Loan transaction data from Ethereum is used to verify our proposed detection method and more than 6,000 wash transactions were found. Moreover, we analyze the relationship between wash transactions and fluctuations in the price and volume of targeted assets. Finally, we evaluate the cost difference between traditional wash trading and Flash-Loan-based wash trading to reveal the attackers' motivation.
Yunming Xiao, Sarit Markovich, Aleksandar Kuzmanovic
Having enabled numerous applications, blockchains have attracted not only much attention, in the past decade, but also huge amount of resources: talent, capital, energy, etc. Focusing on the mining side of the market, in this paper, we aim at understanding how to efficiently use the resources mining and staking pools attract. We start with developing predictions about factors that increase the efficient allocation of pools' resources. We then test our predictions based on a general model for optimal resource allocation that we develop, as well as data we collected on pools' actual resource allocations. We find that pools can increase resource efficiency by mining for more blockchains as well as by increasing the frequency of resource re-allocation. Further, we enroll to mining pools as a miner to understand and comment on how pools can encourage their miners to increase the efficiency of their allocation. While our empirical investigation mostly focuses on the BTC family, we show that our theory and results are general and applicable to the Ethereum family as well as other proof-of-work (PoW) and proof-of-stake (PoS) chains.
Shresth Agrawal, Joachim Neu, Ertem Nusret Tas, Dionysis Zindros
Popular Ethereum wallets (like MetaMask) entrust centralized infrastructure providers (e.g., Infura) to run the consensus client logic on their behalf. As a result, these wallets are light-weight and high-performant, but come with security risks. A malicious provider can mislead the wallet by faking payments and balances, or censoring transactions. On the other hand, light clients, which are not in popular use today, allow decentralization, but are concretely inefficient, often with asymptotically linear bootstrapping complexity. This poses a dilemma between decentralization and performance. We design, implement, and evaluate a new proof-of-stake (PoS) superlight client with concretely efficient and asymptotically logarithmic bootstrapping complexity. Our proofs of proof-of-stake (PoPoS) take the form of a Merkle tree of PoS epochs. The verifier enrolls the provers in a bisection game, in which honest provers are destined to win once an adversarial Merkle tree is challenged at sufficient depth. We provide an implementation for mainnet Ethereum: compared to the state-of-the-art light client construction of Ethereum, our client improves time-to-completion by 9x, communication by 180x, and energy usage by 30x (when bootstrapping after 10 years of consensus execution). As an important additional application, our construction can be used to realize trustless cross-chain bridges, in which the superlight client runs within a smart contract and takes the role of an on-chain verifier. We prove our construction is secure and show how to employ it for other PoS systems such as Cardano (with fully adaptive adversary), Algorand, and Snow White.
In this work, we explore the class of Ethereum smart contracts called the administrated ERC20 tokens. We demonstrate that these contracts are more owner-controlled and less safe than the services they try to disrupt, such as banks and centralized online payment systems. We develop a binary classifier for identification of administrated ERC20 tokens, and conduct extensive data analysis, which reveals that nearly 9 out of 10 ERC20 tokens on Ethereum are administrated, and thereby unsafe to engage with even under the assumption of trust towards their owners. We design and implement SafelyAdministrated - a Solidity abstract class that safeguards users of administrated ERC20 tokens from adversarial attacks or frivolous behavior of the tokens' owners.
We reveal six zero-day social engineering attacks in Ethereum, and subdivide them into two classes: Address Manipulation and Homograph. We demonstrate the attacks by embedding them in source codes of five popular smart contracts with combined market capitalization of over \$29 billion, and show that the attacks have the ability to remain dormant during the testing phase and activate only after production deployment. We analyze 85,656 open source smart contracts and find 1,027 contracts that can be directly used for performing social engineering attacks. For responsible disclosure, we contact seven smart contract security firms. In the spirit of open research, we make the source codes of the attack benchmark, tools, and datasets available to the public.
Kranthi Kiran Reddy, Gutha Vijay Kumar, Sai Siddu Sirimulla, Chanan Singh · 6 authors
This article explores the use and impact of voting using blockchain technology. As a result of mounting worries about the honesty and security of conventional voting methods, especially in the digital era, the study tackles the requirement for an open, impenetrable, and robust method of conducting elections. A decentralized application on a blockchain platform is designed and implemented using the technique, which makes use of smart contracts for voter registration, ballot generation, and vote counting. The viability of blockchain technology in guaranteeing voter anonymity, data integrity, and cryptographic security are important discoveries. Online voting can be done securely and digitally using blockchain technology. It has great potential to reduce costs and increase voter turnout. Using Blockchain we can secure any application and work securely for that application. Therefore, cryptocurrency, healthcare, real estate, etc. Many applications use blockchain technology. *Blockchain technology encrypts votes, preventing any votes from being tampered with. It allows voters to vote for a candidate only once. The system reduces labor costs and counting errors by providing quick access to election results. This article explains solutions to solve the above problems. Our solution is to use an online voting system based on the Ethereum blockchain. That's why we connect surveys to blockchain technology
Open access
2 source records
Internet Traffic Analysis and Secure E-voting
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Ali Aljofey, Abdur Rasool, Qingshan Jiang, Qiang Qu
Blockchain technology has allowed many abnormal schemes to hide behind smart contracts. This causes serious financial losses, which adversely affects the blockchain. Machine learning technology has mainly been utilized to enable automatic detection of abnormal contract accounts in recent years. In spite of this, previous machine learning methods have suffered from a number of disadvantages: first, it is extremely difficult to identify features that enable accurate detection of abnormal contracts, and based on these features, statistical analysis is also ineffective. Second, they ignore the imbalances and repeatability of smart contract accounts, which often results in overfitting of the model. In this paper, we propose a data-driven robust method for detecting abnormal contract accounts over the Ethereum Blockchain. This method comprises hybrid features set by integrating opcode n-grams, transaction features, and term frequency-inverse document frequency source code features to train an ensemble classifier. The extra-trees and gradient boosting algorithms based on weighted soft voting are used to create an ensemble classifier that balances the weaknesses of individual classifiers in a given dataset. The abnormal and normal contract data are collected by analyzing the open source etherscan.io, and the problem of the imbalanced dataset is solved by performing the adaptive synthetic sampling. The empirical results demonstrate that the proposed individual feature sets are useful for detecting abnormal contract accounts. Meanwhile, combining all the features enhances the detection of abnormal contracts with significant accuracy. The experimental and comparative results show that the proposed method can distinguish abnormal contract accounts for the data-driven security of blockchain Ethereum with satisfactory performance metrics.
Rubens Moura de Carvalho, Helena Inácio, Rui Pedro Marques
To assess the financial statements of companies that invest in stablecoin, a digital representation of a fiat currency managed and backed by a blockchain, the auditor must collect evidence of transactions from the blockchain (on-chain) or from an off-chain ledger managed by an intermediary. This study aims to expand the understanding of such transactions, outline possible configurations for the recognition of stablecoin balances and transactions in financial statements, and audit procedures for collecting evidence of these transactions. Based on actual transactions of stablecoin registered on the Ethereum blockchain, we present a hypothetical case of the accounting history of an audited company to demonstrate the challenges in establishing accounting and audit procedures for these novel transactions. We observe an abundance, diversity, and unprecedentedness in the stablecoin transactions studied. We further identify the need to adapt current audit procedures and create new ones, and rethink the very process of doing so. The findings could help auditors obtain more significant knowledge of the information required to assess a company’s financial statements when such statements include stablecoin transactions. In addition, the study addresses the evolving relationship between auditing, accounting, and information technology, and the problems in integrating accounting and information technology.
Rukhsana Rasheed, Mazhir Nadeem, Mahnaz Muhammad Ali
This study is conducted to investigate the potential volatilities and interdependencies among cryptocurrencies during global health crises, i.e., during COVID-19. The top five cryptocurrencies have been selected to assess their interdependencies. These currencies have been ranked as the top five due to their highest market capitalization. These top five currencies are Bitcoin, Ethereum, Tether, USD coin, and BNB. Monthly data for these currencies from the first month of 2019 to eighth month of 2022 is taken from online sources by investing.com. Squared deviations from mean values have been taken as measures of volatilities. These measures are simple but more precise to capture the possibility of potential interrelations in the volatilities of cryptocurrencies through regression analysis. The results of this study showed that the volatility of each cryptocurrencies involved is interlinked with the volatility of at least one other cryptocurrencies.
<sec> <title>BACKGROUND</title> Wearable devices have limited ability to store and process such data. Currently, individual users or data aggregators are unable to monetize or contribute such data to wider analytics use cases. When combined with clinical health data, such data can improve the predictive power of data-driven analytics and can proffer many benefits to improve the quality of care. We propose and provide a marketplace mechanism to make these data available while benefiting data providers. </sec> <sec> <title>OBJECTIVE</title> We aimed to propose the concept of a decentralized marketplace for patient-generated health data that can improve provenance, data accuracy, security, and privacy. Using a proof-of-concept prototype with an interplanetary file system (IPFS) and Ethereum smart contracts, we aimed to demonstrate decentralized marketplace functionality with the blockchain. We also aimed to illustrate and demonstrate the benefits of such a marketplace. </sec> <sec> <title>METHODS</title> We used a design science research methodology to define and prototype our decentralized marketplace and used the Ethereum blockchain, solidity smart-contract programming language, the web3.js library, and node.js with the MetaMask application to prototype our system. </sec> <sec> <title>RESULTS</title> We designed and implemented a prototype of a decentralized health care marketplace catering to health data. We used an IPFS to store data, provide an encryption scheme for the data, and provide smart contracts to communicate with users on the Ethereum blockchain. We met the design goals we set out to accomplish in this study. </sec> <sec> <title>CONCLUSIONS</title> A decentralized marketplace for trading patient-generated health data can be created using smart-contract technology and IPFS-based data storage. Such a marketplace can improve quality, availability, and provenance and satisfy data privacy, access, auditability, and security needs for such data when compared with centralized systems. </sec>
Remote laboratories have been developed at many universities worldwide to provide students with access to apparatus and experiments via the Internet around the clock, thus giving partner institutions the opportunity to share resources, expensive equipment and specialized laboratories, whether within a single country or at regional and international levels. Universities usually implement learning management systems (LMS) such as Moodle and Blackboard to enable students to interact, carry out learning activities and access remote labs. However, remote labs generate enormous amounts of data, which is stored, processed, analyzed, and accessed using centralized systems that lack transparency, traceability, security features, trustworthiness, and reliability. In addition, they are vulnerable to the single point of failure problem due to centralization. The application of blockchain technology in remote labs is proposed as a promising solution for future online learning as it combines a new pedagogical approach with various state-of-the-art technologies in an era that embraces Education 4.0 as the education norm. Furthermore, a novel blockchain-based framework for remote labs allows data streaming and transfer in a decentralized, transparent, traceable, reliable, secure, and trustful manner, where only authorized peers can join or access the network, thereby providing privacy of students’ data files and reports. An initial pilot of an Ethereum-based remote lab show promising result for effective management of online experiments, originally hosted in a Moodle LMS.
The purpose of the article/hypothesis: The purpose of this article is to present the impact of capital gains tax on the returns of the two most popular cryptocurrencies: BITCOIN and Ethereum Classic (ETC). Methodology: In this study, the rates of return on selected cryptocurrencies were proposed as a variable that may be affected by taxes on capital gains. The article presents a new approach to the analysis of issues related to cryptocurrencies. Results of the research: The results show that for selected countries (Hungary, Italy, Poland, the USA) there is a correlation between the tax rate on capital gains and the return on ETC. In the case of BITCON, however, there is no such a relationship.
Yongjing Wang, Zubair Ahmad, Faridoon Khan, Dalia Kamal Alnagar · 7 authors
This paper offers the introduction of a new updated form of the Dagum distribution. The new updated form of the Dagum model is called a novel generalized-Dagum distribution. The proposed novel generalized-Dagum distribution is a prominent updated form of the Dagum model with a single additional/extra parameter. The novel generalized-Dagum model is produced by mixing the Dagum distribution with the novel generalized-M distributions approach. The heavy-tailed properties of the novel generalized-Dagum model are obtained. The derivation of the estimators and a simulation study of the novel generalized-Dagum distribution are also provided. Finally, the novel generalized-Dagum model is illustrated by analyzing two real-life data sets related to the financial sector. The first data set represents the Bitcoin exchange rates vs the United States dollars. Whereas, the second data set represents the Ethereum exchange rates vs the United States dollars. Using the Bitcoin and Ethereum exchange rates data sets, the fitting power of the novel generalized-Dagum model is compared with the transmuted Dagum distribution and a new modified Dagum distribution.
Open access
Statistical Distribution Estimation and Applications
The reality is that there are constantly lots of critiques and testimonials approximately any industrial product or situation at the community. Several crypto buying and selling groups offer a wealth of critiques approximately<strong> Ethereum Trader</strong> or different structures along with Quantum AI buying and selling platform or Bitcoin Edge, that's considerable there.For this reason, the usage of the buying and selling platform may be taken into consideration cost-unfastened. However, it ought to be maintained that they'll be capable of take a small percent of earnings to cowl their prices and pay the debts supervisor fee. https://www.theethereumtrader.com
Smart contract, one of the most successful applications of blockchain, is taking the world by storm, playing an essential role in the blockchain ecosystem. However, frequent smart contract security incidents not only result in tremendous economic losses but also destroy the blockchain-based credit system. The security and reliability of smart contracts thus gain extensive attention from researchers worldwide. In this survey, we first summarize the common types and typical cases of smart contract vulnerabilities from three levels, i.e., Solidity code layer, EVM execution layer, and Block dependency layer. Further, we review the research progress of smart contract vulnerability detection and classify existing counterparts into five categories, i.e., formal verification, symbolic execution, fuzzing detection, intermediate representation, and deep learning. Empirically, we take 300 real-world smart contracts deployed on Ethereum as the test samples and compare the representative methods in terms of accuracy, F1-Score, and average detection time. Finally, we discuss the challenges in the field of smart contract vulnerability detection and combine with the deep learning technology to look forward to future research directions.
Atualmente, existem diversos dispositivos que coletam dados e prestam serviços na Internet. Alguns desses dispositivos colaboram para trocar informacões e usá-las para tomar decisões mais inteligentes em um ambiente chamado Internet das Coisas (IoT). Recentemente, a tecnologia blockchain surgiu como uma possível solução para superar problemas de segurança em IoT. Apesar disso, blockchains tradicionais (como Bitcoin ou Ethereum) nao são adequados para a natureza de capacidade/recursos limitados dos dispositivos IoT. Alem disso, as propostas atuais carecem de uma discussão sobre o comportamento do usuario em diferentes contextos e como ele pode ser adaptado para diferentes algoritmos de consenso. Para superar esses problemas, apresentamos na tese um conjunto de etapas para criar um mecanismo de consenso multinível para diferentes contextos usando uma estrutura blockchain leve chamada appendable-block blockchain. Essa abordagem fornece uma solução que permite usar diferentes configurações ou consensos, de acordo com os requisitos de cada contexto no ambiente IoT. Por fim, a tese mostra que um consenso multinível pode produzir uma alta taxa de transferencia e baixa latência para inserir novas transações em appendable-block blockchains.
Luciano Baresi, Giovanni Quattrocchi, Damian A. Tamburri, Luca Terracciano
The deployment and management of Blockchain applications require non-trivial efforts given the unique characteristics of their infrastructure (i.e., immutability) and the complexity of the software systems being executed. The operation of Blockchain applications is still based on ad-hoc solutions that are error-prone, difficult to maintain and evolve, and do not manage their interactions with other infrastructures (e.g., a Cloud backend). This paper proposes KATENA, a framework for the deployment and management of Blockchain applications. In particular, it focuses on applications that are compatible with Ethereum, a popular general-purpose Blockchain technology. KATENA provides i) a metamodel for defining Blockchain applications, ii) a set of processes to automate the deployment and management of defined models, and iii) an implementation of the approach based on TOSCA, a standard language for Infrastructure-as-Code, and xOpera, a TOSCA-compatible orchestrator. To evaluate the approach, we applied KATENA to model and deploy three real-world Blockchain applications, and showed that our solution reduces the amount of code required for their operations up to $82.7\%$.
The field of digital pathology produces a large number of images associated with patient metadata that are the raw material of computational pathology. The process of making images available with adequate privacy and data protection considerations takes a long time. Given that the Ethereum network associated with InterPlanetary File System (IPFS) promotes the exchange of information in a secure, private and decentralized manner, this association could be an important partner between digital and computational pathology. Therefore, here we propose and discuss a prototype with the aforementioned parts and the addition of neural compression, as an essential information preservation step. This prototype could constitute a link for the exchange of information in a secure way, providing transparency and reliability to the chain and empowering the field of manufacturing artificial vision solutions for the medical field
May Altulyan, Lina Yao, Salil S. Kanhere, Chaoran Huang
Abstract Recommender system for the IoT (RSIoT) has attracted considerable attention. By leveraging emerging technologies such as the Internet of Things (IoT), artificial intelligence, and blockchain, RSIoT improves various indicators of residents' life. However, data integrity threats may affect the accuracy and consistency of the data particularly in the IoT environment where most devices are inherently dynamic and have limited resources that could fail in ensuring the quality of data transmission. Prior work has focused on processing big data and ensuring their integrity by considering cloud storage service as the popular way. In this article, we address integrity of data leveraging blockchain capabilities to ensure the integrity of the critical data. We adapted the Ethereum blockchain to our RCS for ensuring integrity of data during sharing them between doctor and patient without handling their data by third party. We build four smart contracts that enable our system of gaining more advantage of blockchain. We evaluated the performance of our smart contracts in Kovan and Rinkeby test networks. The preliminary results show the feasibility and effectiveness of the proposed solution.
Recent advanced Zero-Knowledge protocols, along with other high-level constructions such as Multi-Party Computations (MPC), have highlighted the need for a new type of symmetric primitives that are not optimized for speed on the usual platforms (desktop computers, servers, microcontrollers, RFID tags...), but for their ability to be implemented using arithmetic circuits.Several primitives have already been proposed to satisfy this need. In order to enable an efficient arithmetization, they operate over large finite fields, and use round functions that can be modelled using low degree equations. The impact of these properties on their security remains to be completely assessed. In particular, algebraic attacks relying on polynomial root-finding become extremely relevant. Such attacks work by writing the cryptanalysis as systems of polynomial equations over the large field, and solving them with off-the-shelf tools (SageMath, NTL, Magma, . . . ).The need for further analysis of these new designs has been recently highlighted by the Ethereum Foundation, as it issued bounties for successful attacks against round-reduced versions of several of them.In this paper, we show that the security analysis performed by the designers (or challenge authors) of four such primitives is too optimistic, and that it is possible to improve algebraic attacks using insights gathered from a careful study of the round function.First, we show that univariate polynomial root-finding can be of great relevance n practice, as it allows us to solve many of the Ethereum Foundation’s challenges on Feistel–MiMC. Second, we introduce a trick to essentially shave off two full rounds at little to no cost for Substitution-Permutation Networks (SPN). This can be combined with univariate (resp. multivariate) root-finding, which allowed to solve some challenges for Poseidon (resp. Rescue–Prime). Finally, we also find an alternative way to set up a system of equations to attack Ciminion, leading to much faster attacks than expected by the designers.
Soroush Goodarzi, Vahid Kayvanfar, Alireza Haji, Alireza Shirzad
Vaccinating the global population against Covid-19 is one of the biggest supply chain management challenges humanity has ever faced. Rapid supply of Covid-19 vaccines is essential for successful global immunization, but its effectiveness depends on a transparent supply chain that can be monitored. In this research, we have proposed an approach based on blockchain technology, which is used to ensure seamless distribution of the Covid-19 vaccine with transparency, data integrity, and full traceability of the supply chain to reduce risk, ensure safety, and immutability. A vaccine supply chain needs to update the status of the vaccine at every stage, and any problem in the supply and distribution path can lead to irreparable damage. Currently, the research conducted on the use of blockchain in supply chains is still in the early stages. In this paper, the use of blockchain technology to monitor the vaccine supply and distribution system will be investigated. A model close to reality of today's vaccine supply chains in developing countries is considered and then a new intelligent system for vaccine monitoring in the vaccine supply chain is designed based on the considered model. Also, smart contracts based on a blockchain network is designed to check consumer vaccination records as well as vaccine circulation from beginning to end. The implementation and design of the vaccine supply chain is done using smart contracts on the Ethereum blockchain network. Additionally, the system has been tested on both local networks, the HardHat suite and Rinkbey's test network. The system has also been developed to work seamlessly when it is using an integrated IoT chip that can automatically update a batch's location, temperature, and other physical conditions periodically.
In this paper, the authors have amplified the concept that EHRs need to be patient-centric and patient-driven, that is the patient should be the real owner as well as the manager of his medical records. The authors propose patient-centric multichain healthcare record (PCMHR) that implements health records using smart contracts on ethereum blockchain and also utilizes the multichain framework - Polygon. PCMHR can concurrently implement blockchain functionality while addressing the concerns of interoperability among authorized hospitals and patient health information confidentiality that damages our healthcare system. The authors propose a solution to fully decentralize the current medical healthcare system by storing PCMHR on IPFS (InterPlanetary File System) to resolve the limitation of blockchain-based applications in scalability and high cost. The authors have depicted the cost and time analysis of transactions on the polygon framework to give a clear view of this multichain framework and its advantages over the ethereum blockchain.
A. A. Talha Talukder, Md. Anisul Islam Mahmud, Arbiya Sultana, Tahmid Hasan Pranto · 6 authors
Food delivery systems are gaining popularity recently due to the expansion of internet connectivity and for the increasing availability of devices. The growing popularity of such systems has raised concerns regarding (i) Information security, (ii) Business to business (B2B) deep discounting race, and (iii) Strict policy enforcement. Sensitive personal data and financial information of the users must be safeguarded. Additionally, in pursuit of gaining profit, the restaurants tend to offer deep discounts resulting in a higher volume of orders than usual. Therefore, the restaurants and the delivery persons fail to maintain the delivery time and often impair the food quality. In this paper, we have proposed a blockchain and smart contract-based food delivery system to address these issues. The main goal is to remove commission schemes and decrease service delays caused by a high volume of orders. The protocols have been deployed and tested on the Ethereum test network. The simulation manifests a successful implementation of our desired system; with the payment being controlled by our system. The actors (restaurant, delivery-person or consumer) are bound to be compliant with the policies or penalized otherwise.