Leyi Shi, Yang Li, Tianxu Liu, Jia Liu · 6 authors
Honeypot technology can be applied to efficiently attract attackers and exhaust their resources. However, the traditional static honeypot is easy to be recognized by anti-honeypot technology. By contrast, most of the dynamic honeypots can simulate the real system in time, thus interacting with an intruder in disguise. In this paper, we employ the dynamic property of honeypot in four kinds of services of our system. However, this dynamic property shows up in a location and identification, indicating that genuine or fake services (honeypots) are changeable in different hosts. Thus, the dynamic property of our system differs from the dynamic honeypot aforementioned. Besides, we adopt the blockchain platform (Ethereum) to decentralize our system and store the port access data by delivering a private chain. To illustrate the effectiveness of our scheme in theory and practice, security analysis, eavesdropping attack, scanning attack, and DoS attack experiments are conducted. The results show that our scheme is valid in safeguarding against network attack.
Proof-of-burn has been used as a mechanism to destroy cryptocurrency in a verifiable manner. Despite its well known use, the mechanism has not been previously formally studied as a primitive. In this paper, we put forth the first cryptographic definition of what a proof-of-burn protocol is. It consists of two functions: First, a function which generates a cryptocurrency address. When a user sends money to this address, the money is irrevocably destroyed. Second, a verification function which checks that an address is really unspendable. We propose the following properties for burn protocols. Unspendability, which mandates that an address which verifies correctly as a burn address cannot be used for spending; binding, which allows associating metadata with a particular burn; and uncensorability, which mandates that a burn address is indistinguishable from a regular cryptocurrency address. Our definition captures all previously known proof-of-burn protocols. Next, we design a novel construction for burning which is simple and flexible, making it compatible with all existing popular cryptocurrencies. We prove our scheme is secure in the Random Oracle model. We explore the application of destroying value in a legacy cryptocurrency to bootstrap a new one. The user burns coins in the source blockchain and subsequently creates a proof-of-burn, a short string proving that the burn took place, which she then submits to the destination blockchain to be rewarded with a corresponding amount. The user can use a standard wallet to conduct the burn without requiring specialized software, making our scheme user friendly. We propose burn verification mechanisms with different security guarantees, noting that the target blockchain miners do not necessarily need to monitor the source blockchain. Finally, we implement the verification of Bitcoin burns as an Ethereum smart contract and experimentally measure that the gas costs needed for verification are as low as standard Bitcoin transaction fees, illustrating that our scheme is practical.
We conduct a detailed analysis of investors in successful initial coin offerings (ICOs). The average ICO has 4700 contributors. The median participant contributes small amounts and many investors sell their tokens before the underlying product is developed. Large presale investors obtain tokens at a discount and flip part of their allocation shortly after the ICO. ICO contributors lack the protections traditionally afforded to investors in early-stage financing. Nevertheless, returns 9 months after the ICO are positive on average, driven mostly by an increase in the value of the Ethereum cryptocurrency.
Santiago Bragagnolo, Matteo Marra, Guillermo Polito, Elisa Gonzalez Boix
Analysing the blockchain is becoming more and more relevant for detecting attacks and frauds on cryptocurrency exchanges and smart contract activations. However, this is a challenging task due to the continuous growth of the blockchain. For example, in early 2017 Ethereum was estimated to contain approximately 300GB of data [1], a number that keeps growing day after day. In order to analyse such ever-growing amount of data, this paper argues that blockchain analysis should be treated as a novel type of application for Big Data platforms. In this paper we explore the application of parallelization techniques from the Big Data domain, in particular Map/Reduce, to extract and analyse information from the blockchain. We show that our approach significantly improves the index generation by 7.77 times, with a setup of 20 worker nodes, 1 Ethereum node and 1 Database node. We also share our findings of our massively parallel setup for querying Ethereum in terms of architecture and the bottlenecks. This should help researchers setup similar infrastructures for analysing the blockchain in the future.
Rui Song, Yubo Song, Ziming Liu, Min Tan · 5 authors
The birth of blockchain has promoted the development of electronic currencies such as Bitcoin and Ethereum. Blockchain builds a financial system based on cryptology instead of credit, which allows parties to complete the tran... | Find, read and cite all the research you need on Tech Science Press
We take this question to be isomorphic to, "What Keeps Fixed Exchange Rates Fixed?" and address it with analysis familiar in exchange-rate economics. Stablecoins solve the volatility problem by pegging to a national currency, typically the US dollar, and are used as vehicles for exchanging national currencies into non-stable cryptocurrencies, with some stablecoins having a ratio of trading volume to outstanding supply exceeding one daily. Using a rich dataset of signed trades and order books on multiple exchanges, we examine how peg-sustaining arbitrage stabilizes the price of the largest stablecoin, Tether. We find that stablecoin issuance, the closest analogue to central-bank intervention, plays only a limited role in stabilization, pointing instead to stabilizing forces on the demand side. Following Tether's introduction to the Ethereum blockchain in 2019, we find increased investor access to arbitrage trades, and a decline in arbitrage spreads from 70 to 30 basis points. We also pin down which fundamentals drive the two-sided distribution of peg-price deviations: Premiums are due to stablecoins' role as a safe haven, exhibiting, for example, premiums greater than 100 basis points during the COVID-19 crisis of March 2020; discounts derive from liquidity effects and collateral concerns.
This work presents ContractChecker, a Blockchain-based security protocol for verifying the storage consistency between the mutually distrusting cloud provider and clients. Unlike existing protocols, the ContractChecker uniquely delegates log auditing to the Blockchain, and has the advantages in reducing client cost and lowering requirements on client availability, lending itself to modern scenarios with mobile and web clients. The ContractChecker collects the logs from both clients and the cloud server, and verifies the consistency by cross-checking the logs. By this means, it does not only detects the attacks from malicious clients and server forging their logs, but also is able to mitigate those attacks and recover the system from them. In addition, we design new attacks against ContractChecker exploiting various limits in real Blockchain systems (e.g., write unavailability, Blockchain forks, contract race conditions). We analyze and harden the security of ContractChecker protocols against the proposed new attacks. For evaluating the cost, we build a functional prototype of the ContractChecker on Ethereum/Solidity. By experiments on private and public Ethereum testnets, we extensively evaluate the cost of the ContractChecker in comparison with that of existing client-based log auditing works. The result shows the ContractChecker can scale to hundreds of clients and save client costs by more than one order of magnitude.
Cryptocurrencies have emerged about ten years ago as a new form of currency and have attracted much attention since they depend on a fully decentralized system, and so their transactions are very fast and have zero transaction cost. Therefore, character of cryptocurrencies and their volatility have been discussed widely by investors, policymakers and economists in recent years. From this point of view, this study aims to explain the price volatility of cryptocurrencies with macro-financial indicators, and thereby, the effects of S&P 500 stock market index, gold price, oil price, 2-year benchmark US Bond interest rate and US Dollar index on the prices of four major cryptocurrencies, Bitcoin, Litecoin, Ethereum, and Ripple, are investigated. The study comprises a panel data analysis applied to daily data over the period of August 2016 – April 2019, and analysis results show that increases in gold price, oil price and S&P 500 index raise the prices of cryptocurrencies, while increases in 2-year benchmark US Bond interest rate and US Dollar index cause to a fall. This adverse effects of the US Dollar index and US Bond interest rate on the prices of cryptocurrencies indicates that when the value of US Dollar and US Bond yield decrease investors prefer to invest in cryptocurrencies as alternative investment instruments. On the other hand, cryptocurrencies move with a similar trend of stock market index, gold price and oil price which are overall market indicators. Thereby, findings of this study show that cryptocurrencies behave more like an investment instrument than a currency, and prices of these financial assets interact with significant macro-financial indicators.
Anja Meironke, Tobias Seyffarth, Johannes Damarowsky
Second generation blockchain technologies such as Ethereum can be used not only for financial transactions but also for cross-organizational processes, for applications in the pharmaceutical industry and even in the field of Business Process Compliance (BPC). However, there are many challenges in the field of BPC. Thus, we raised the following research question: How does the Ethereum blockchain address challenges of BPC? To answer this question, we conducted a structured literature review to identify challenges in BPC as well as features of the Ethereum blockchain that may solve the selected BPC challenges. As a result, we identified 21 BPC challenges and categorized these into legal, organizational, human-centered, technical and economic challenges. We found that the technical and organizational BPC challenges were those that Ethereum could best solve, while human-centered challenges could be less well addressed. Furthermore, the implementation of the Ethereum blockchain leads to additional challenges, such as the immutability of illegal content within the Ethereum blockchain or the error-proneness and zero-defect tolerance of smart contracts.
This study examines and compares the volatility in sample fit and out of sample forecast of four different heteroscedasticity models, namely ARCH, GARCH, EGARCH and GJR-GARCH applied to Bitcoin, Ethereum and Ripple. The models are fitted over the period from 2016-01-01 to 2019-01-01 and then used to obtain one day rolling forecasts during the period from 2018-01-01 to 2019-01-01. The study investigates three different themes consisting of the modelling framework structure, complexity of models and the relation between a good in sample fit and good out of sample forecast. AIC and BIC are used to evaluate the in sample fit while MSE, MAE and R2LOG are used as loss functions when evaluating the out of sample forecast against the chosen Parkinson volatility proxy. The results show that a heavier tailed reference distribution than the normal distribution generally improves the in sample fit, while this generality is not found for the out of sample forecast. Furthermore, it is shown that GARCH type models clearly outperform ARCH models in both in sample fit and out of sample forecast. For Ethereum, it is shown that the best fitted models also result in the best out of sample forecast for all loss functions, while for Bitcoin non of the best fitted models result in the best out of sample forecast. Finally, for Ripple, no generality between in sample fit and out of sample forecast is found.
An inclusive project is classified and alienated into several tasks where as task management is one of the foremost components of project management, since the roles and tasks assigned by the manager of this component to each employee working on a project. In scrupulous there are several ways to track the status of work and this monitoring is also required to find the efficiency of an individual and at the time of the annual and mid- term appraisal and all these monitoring records can be used to give qualifications to associates and employees. In this work, the authors have proposed a system along with the solution based on the ERC20 token which is identified as blockchain platform based on Ethereum in which they can implement Project Task Management which is tamper proof and as well as can track the assigned task of an employee on real time basis.
Функциональное моделирование на основе стандарта IDEF0 – создание графических моделей любой предметной деятельности, включающих иерархическое описание процессов, операций, ресурсов (информации), инструментария, исполнителей, управления и связей между ними. В статье предложена функциональная модель создания и управления смарт-контрактами на платформе Ethereum.
The 2008 debut of Bitcoin marked the first large-scale implementation of blockchain technology, and its decentralized approach to monetary systems has since been abstracted to more generalized purposes like distributed computing. Platforms like Ethereum, which function as a global, decentralized computing and data storage system, promise to bring the cost of decentralized knowledge production in line with the efficiencies afforded by the centralized, integrated computing systems that currently dominate the knowledge economy. Blockchain technologies have been investigated for a wide range of information management purposes, but their exploration within the realm of library and information studies has largely been nascent. Though many applications within the field have been envisioned, few have been explored in depth. Among the many functions performed in the field of librarianship, the work of cataloguers—which has always been performed in a decentralized manner—represents an intriguing use case. A review of current shared-cataloguing practices reveals that catalogues have become largely-centralized, divorced from public participation, dominated by an ethos of efficiency at the cost of quality, and essentially unaltered since the shift from physical to electronic catalogue storage more than 40 years ago. The evolution of blockchain technologies, paired with an intentional approach to shared catalogues that is open for use, transparency, and public participation, is explored in a conceptual framework and design based on the Ethereum platform. A theoretical design scheme grounded in the affordances of Ethereum, shaped by the principles of open source software development, and guided by the best practices of existing social information production systems results in a proposal for Catagora: an open source, open-for-use, transparent and participatory shared-cataloguing platform that reverses the trend towards architectural and political centralization and promises novel catalogue features such as complete revision history and distributed collaboration on the content and quality of catalogue entries. Blockchain technology, alone, cannot disrupt shared cataloguing practices; such a shift involves the voluntary and eager participation of cataloguers and members of the public in order to sustain and grow the system. The Catagora design concept presented in this thesis incorporates accessibility, collaboration and reputational systems that are intended to foster open participation, but these alone cannot guarantee a thriving, shared-cataloguing alternative to existing systems. Further exploration, in the form of a live implementation, is warranted; and lessons from existing large-scale library technology projects suggest that a centrally-coordinated implementation, targeting key cataloguing partners and driven by a passionate project champion, may provide a more complete picture of the blockchain’s potential to support open, shared cataloguing for the benefit of information seekers.
In early 2018 prices peaked at USD 20,000 and, almost two years later, we still continue debating if cryptocurrencies can actually become a currency for the everyday life or not. From the economic point of view, and playing in the field of behavioral finance, this paper analyses the relation between prices and the search interest on Bitcoin since 2014. We questioned the forecasting ability of Google Trends for the behavior of price by performing linear and nonlinear dependency tests, and exploring performance of ARIMA and Neural Network models enhanced with this social sentiment indicator. Our analyses and models are founded upon a set of statistical properties common to financial returns that we establish for Bitcoin, Ethereum, Ripple and Litecoin.
Rewriting-history attacks can erase all valid records of blockchain-based systems, which is extremely devastating. To deter such attacks, we design a new smart contract-based secure model to make such attacks ineffective. Each node who creates a new block is required to register with the smart contract to get a voucher required for the subsequent block validation. We introduce the design idea and the structure of the proposed model in detail. We also present the algorithms of the smart contract and analyze the security performance of the proposed model in different cases. To prove the feasibility of the proposed model, we use the Solidity language to implement the smart contract in this model and simulate it on the Ethereum test network. We also show simulation results in terms of runtime and resource consumption.
Karl Wüst, Loris Diana, Kari Kostiainen, Ghassan Karame · 6 authors
In this paper, our main goal is to design a solution that adds expressive smart contract execution support as a subsystem to existing legacy blockchain systems. The primary usage of our solution is to enhance systems like Bitcoin that have no built-in smart contract capabilities. The secondary usage is to extend the contract execution capabilities of platforms like Ethereum that support contracts but have severe limitations on the complexity of allowed computations.
Block-chain world is very dynamic and there is need for strong governance and underlying technology architecture to be robust to face challenges. This paper considers Ethereum, a leading block chain. We deep dive into the nature of this block chain, wherein for software upgrades forks are performed. They types of forks and impact is discussed. A specific Ethereum hack led to a hard fork and focus is provided on understanding the hack and overcoming it from a novel approach. The current model has been unable to handle multiple Ethereum attacks. Thus the current approach is compared against a novel approach providing a security and scaling solution. Here the architecture draws upon combining block-chain layers into operating system level. The approach can have tremendous benefits to block chain world and improve the way decentralized application teams perform. The benefits of the novel architecture is discussed. The approach helps safe guard block chain projects, making them safer and chain agnostic.
Current research has led to a rejection of the hypothesis of a normal distribution of financial assets returns. Under these conditions, portfolio variance cannot serve as a good risk measure. In this paper analyzed the daily returns of the most common cryptocurrencies: Bitcoin, Bitcoin Cash, Litecoin, XRP, Ethereum, NEM. It is shown that the asset returns are not normally distributed, but with good precision follow the Cauchy distribution. The analytical expressions for risk measure were obtained using the Cauchy distribution function and the VaR technique. The efficient frontiers of cryptocurrencies portfolios were constructed using modified Markowitz model. The purpose of the article is to assess the risks of major cryptocurrencies and to diversify the risk of cryptocurrency investing by applying a portfolio model
Abstract This paper examines whether there exists a momentum effect after one-day abnormal returns in the cryptocurrency market. For this purpose, a number of hypotheses of interest are tested for the Bitcoin, Ethereum and Litecoin exchange rates vis-à-vis the US dollar over the period 01.01.2015–01.09.2019, specifically whether or not: (H1) the intraday behavior of hourly returns is different on abnormal days compared to normal days; (H2) there is a momentum effect on days with abnormal returns, and (H3) after one-day abnormal returns. The methods used for the analysis include various statistical methods as well as a trading simulation approach. The results suggest that hourly returns during the day of positive/negative abnormal returns are significantly higher/lower than those during the average positive/negative day. The presence of abnormal returns can usually be detected before the day ends by estimating specific timing parameters. Prices tend to move in the direction of the abnormal returns till the end of the day when it occurs, which implies the existence of a momentum effect on that day giving rise to exploitable profit opportunities. This effect (together with profit opportunities) is also observed on the following day. In two cases (BTCUSD positive abnormal returns and ETHUSD negative abnormal returns), a contrarian effect is detected instead.
The purpose of this paper is to examine if there is cointegration between the daily closing price of the cryptocurrency Bitcoin and five other cryptocurrencies; Ethereum, Ripple, Bitcoin Cash, EOS and Litecoin in five different time periods, all ending April 9, 2019. To test if there is a long-run relationship between Bitcoin and these mentioned cryptocurrencies, two different tests for cointegration are applied; the Engle-Granger two step approach and Johansen’s cointegration test as well as a Vector Error Correction Model (VECM). The results from both cointegration tests suggest that Bitcoin is cointegrated with Bitcoin Cash, Ethereum, Litecoin and Ripple. The Johansen test and the Engle-Granger method for cointegration demonstrate that Bitcoin and EOS do not have any cointegrating relationship. Another finding is that, based on the results from the VECM estimation, the price of Bitcoin has a statistically significant long-run impact on the prices of Bitcoin Cash, Ethereum, Litecoin and Ripple.