The article compares the concepts of virtual currency (cryptocurrency) and electronic money. It is established that such assets, although different from each other, have certain similar features. Electronic money, unlike cryptocurrency, has a legal status, a legally defined issuer, a fixed offer and is regulated and supervised. It is established that there are four qualitative characteristics that increase the usefulness of financial information that is relevant and accurately presented - it is comparability, reliability, timeliness and clarity. Thus, the issue of reflecting in the financial statements of digital assets that affect the assets of the enterprise, determining the liquidity of the balance sheet, understanding of the transactions in connection with which the company has acquired digital assets. Based on this, cryptocurrency assets have every chance to become an integral part of the world economy, as some countries are already inclined to introduce such currency in the process of use and exchange for goods or other funds. If an enterprise is able to control certain assets, such as cryptocurrency, and to carry out storage and accumulation operations with it, this affects the reflection of such assets in the financial statements of the enterprise and the assessment of the solvency of such enterprise. It is established that the liquidity of digital assets depends on their recognition in the accounting policy as a certain asset. If they are recognized as cash, they are the most liquid assets of the first group, but if they are recognized as digital goods, then this is the third group of liquidity. It is determined that the risk of using cryptocurrency has an economic and legal nature. Its essence is that the value of cryptocurrency is set by the ratio of supply and demand for it. When investing real money in cryptocurrency, the demand for it may not increase or decrease due to its unpopularity. But it should also be noted that such economic risk must be associated with legal, as the state can legalize transactions with cryptocurrency, but not with all, but only with a specific one, such as bitcoin and its "forks". Thus, based on the peculiarities of the use of cryptocurrency, the following risks can be identified, such as legal, economic, technical and others.
Blockchain and cryptocurrencies have risen to popularity in the recent years to a great extent due to its increasing trading volumes and huge capitalization in the market. These cryptocurrencies are being used not only for trading but are being accepted for monetary transactions as well these days. As the prices fluctuate and return on investment increases investors, traders and general public are showing increased interest towards bitcoin and altcoins. This research focuses on implementing forecasting models that will return accurate price predictions for cryptocurrencies. Prices for Bitcoin, Ethereum and Litecoin are predicted using the traditional forecasting model for timeseries ARIMA, the Prophet Model and deep learning algorithm LSTM. The results of the three models were evaluated and the LSTM Model was found to outperform the Prophet as well as the ARIMA model.
Jan 1, 2020·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Vikram Kanth, Ashley McaAbee, Murali Tummala, John McEachen
As the threat of cyber attack grows ever larger, new approaches to security are required. While there are several different types of intrusion detection systems (IDS), collaborative IDS (CIDS) offers particular promise in identifying distributed, coordinated attacks that might otherwise elude detection. Even for CIDS, there are unresolved issues associated with trusting participants and aggregating data. Blockchain technology appears capable of addressing those issues if practical implementation strategies can be developed. To that end, we implement an Ethereum blockchain-based CIDS leveraging pluggable authentication modules. Our system is specifically crafted to detect doorknob rattling attacks by immutably recording login activity in a blockchain-protected ledger.
This paper analyzes the stability of stablecoins and proposes a framework to test for absolute and relative stability of stablecoins. Based on high-frequency data, we find strong evidence of excess price variations. While Bitcoin is a likely source of this excess volatility because stablecoin returns, volatility and volumes are highly correlated with corresponding Bitcoin time-series, we also demonstrate through a quasi-natural experiment that stablecoins increase the trading volume of Bitcoin. The findings suggest stablecoins play a key role in cryptocurrency markets.
The aim of this study is to determine whether successful predictions for cryptocurrencies such as Bitcoin can be obtained with different methods. The reason why Bitcoin prices (Bitcoin / $) are used in the study is that this cryptocurrency is still the most widely used cryptocurrency in the market, and the idea that it will successfully represent the overall state of the cryptocurrencies market. Financial market series may contain fluctuations for some reason, such as speculations. It also usually includes nonlinear changes. Such features lead to failures in obtaining forecasts for financial time series. In this study, with the GARCH model, one of the classicial time series models and LS -SVM method, a machine learning method, predictions of the Bitcoin price series were obtained, and model performances were compared. In the study, between January 01, 2017 and February 29, 2020, 1155 daily Bitcoin price series ( ) was used. In both models, the Bitcoin price series and the volatilities of this series were used, and external variables were not included in the models. For both models, forecasts were obtained for periods of 1 month, 2 months and 3 months. For GARCH and LS -SVM models, out of sample successful forecasting rates according to MAPE ratios were 98,0347% -95,3423% for 1 month; 97,9544% -96,1307% for 2 months and 98,1272% -91,4874% for 3 months, respectively. The GARCH model has provided more successful results for all three periods. The finding of the study is that the GARCH model can be used to obtain forecasts for the crypto price series.
Merkle trees are ubiquitous in blockchains and other distributed ledger technologies (DLTs). They guarantee that the involved systems are referring to the same binary tree, even if each of them knows only the cryptographic hash of the root. Inclusion proofs allow knowledgeable systems to share subtrees with other systems and the latter can verify the subtrees' authenticity. Often, blockchains and DLTs use data structures more complicated than binary trees; authenticated data structures generalize Merkle trees to such structures. We show how to formally define and reason about authenticated data structures, their inclusion proofs, and operations thereon as datatypes in Isabelle/HOL. The construction lives in the symbolic model, i.e., we assume that no hash collisions occur. Our approach is modular and allows us to construct complicated trees from reusable building blocks, which we call Merkle functors. Merkle functors include sums, products, and function spaces and are closed under composition and least fixpoints. As a practical application, we model the hierarchical transactions of Canton, a practical interoperability protocol for distributed ledgers, as authenticated data structures. This is a first step towards formalizing the Canton protocol and verifying its integrity and security guarantees.
Toqeer Ali Syed, Muhammad Shoaib Siddique, Adnan Nadeem, Ali Alzahrani · 6 authors
Transactions related to vehicles include manufacturing, buying, selling, paying insurance(takaful), obtaining regular inspection, leasing a vehicle from banks, getting in an accident, engaging in a traffic violation, calculating price predictions and renting a vehicle. Many people perform transactions related to vehicles in their daily life; transportation authorities also perform vehicle transactions as part of managing vehicle fleets. But tracking these transactions is a challenging task. There are countrywide solutions that uses centralized systems. However, these solutions have problems with trust management, transparency, and access control. Therefore, we believe there is still room for integrated automation of various vehicle-related transactions. In this paper, we present a blockchain-based framework for vehicle tracking that incorporates the mentioned features. Moreover, blockchain is customized to enable usage control for additional transactions, such as inspection, renting and islamic insurance. The usage control model is integrated with IoT devices to continuously monitor the vehicles for certain conditions and remotely revoke access if needed. The complete transaction set is recorded over an immutable ledger that provides trust, transparency and a complete history of record. In this paper, we also presents a prototype implementation of a permissioned blockchain, which will be made available under the GNUv3 General Public License. Performance analysis is performed on the newly proposed framework implementation over the permissioned blockchain to measure its adoption and suitability.
Previous contract protocols in blockchains ensure their fairness and traceability by utilizing centralized credible nodes. If credible nodes are dishonest or conspire with the signatory, then other nodes are compromised. Meanwhile, the leakage of sensitive information of participant nodes poses a serious threat to the privacy security of data access in blockchains. To address this issue, this study proposes a secure control method of digital certificate-based data access in blockchains. The proposed method combines blockchain and digital certificate technologies and designs a secure authentication protocol for privacy data in blockchains without verifying the encrypted identity signature of the third-party participant. The high-efficiency network forwarding protocol proposed in this work can support the fair contract signing of multiple signers via blockchain. This protocol can protect the privacy of contracts and identities of participants. Experimental results show that the proposed scheme is superior in terms of communication overhead, storage overhead, and detection rate.
Open access
Blockchain Technology Applications and Security
Privacy-Preserving Technologies in Data
Advanced Steganography and Watermarking Techniques
Water has always been considered as a physically scarce resource, particularly in North Africa, Central Asia, West Asia, among others. On the other hand, the current water management system is facing substantial difficulties due to the depletion of resources, the complexity of regulation, as well as the increasing demand of water in society. This article attempts to show the possibility of using blockchain technologies in managing scarce resources, such as water, to address environmental sustainability. Those applications could consolidate the seamless integration of the existing water management system through keen agreements which dwell on the blockchain and take into account automated work processes. It is expected that the implementation of blockchain technology will ensure trust, transparency, and accountability among individuals and other economic actors.
Abstract The Internet of Things (IoT) has recently emerged as an innovative technology capable of empowering various areas such as healthcare, agriculture, smart cities, smart homes and supply chain with real-time and state-of-the-art sensing capabilities. Due to the underlying potential of this technology, it already saw exponential growth in a wide variety of use-cases in multiple application domains. As researchers around the globe continue to investigate its aptitudes, a collective agreement is that to get the best out of this technology and to harness its full potential, IoT needs to sit upon a flexible network architecture with strong support for security, privacy and trust. On the other hand, blockchain (BC) technology has recently come into prominence as a breakthrough technology with the potential to deliver some valuable properties such as resiliency, support for integrity, anonymity, decentralization and autonomous control. Several BC platforms are proposed that may be suitable for different use-cases, including IoT applications. In such, the possibility to integrate the IoT and BC technology is seen as a potential solution to address some crucial issues. However, to achieve this, there must be a clear understanding of the requirements of different IoT applications and the suitability of a BC platform for a particular application satisfying its underlying requirements. This paper aims to achieve this goal by describing an evaluation framework which can be utilized to select a suitable BC platform for a given IoT application.
IoT-enable monitoring can provide valuable information for the shellfish quality evaluation during cold storage condition. However, IoT based information storage relies on the centralized platform, it is possible to tamper. In this paper, we establish blockchain based multi-sensors (WSN) monitoring system to collect quality parameters and verify captured information for improving transparency and trust during cold storage. The implementation of the K-means and SVM algorithms were used in quality evaluation applications to classify and predict the quality loss of frozen shellfish. The results show blockchain based WSN monitoring can achieve the dynamic indicators continuous monitoring and ensures the data security and reliability. The proportion of the training set and the test set in the allowable deviation range is 88.89% and 87.17%. The root mean square error (RMSE) of training set and test set are 0.1502 and 0.1793 by SVM model. The performance of the K-means and SVM model has higher accuracy than BP model. This paper could help to reduce the risk of food losses and improve quality and safety management of frozen shellfish during cold storage.
Iryna Tsymbalіuk, Mohammed Younus Hasan Alghadhywi
The main ideas and principles of inclusive development are revealed in this paper It is proved that the main condition for the transition of the Ukrainian regions to the principles of inclusive growth is the provision of developed inclusive infrastructure. The purpose of the paper is to substantiate the system of quantitative indicators that reflect the prospects for achieving the goals and objectives of infrastructure development in the region as an important component and prerequisite for inclusive growth. Based on the methodology proposed in the paper, the analysis of infrastructural development of the Ukrainian regions as a basis for inclusive growth is carried out. It is proved that in order to involve the maximum number of the population in the development processes, it is necessary to create appropriate conditions, which are provided by the developed infrastructure. Due to indicators of construction development, transport infrastructure, passenger and cargo turnover, the level of the population coverage with Internet services, preschool educational institutions for children; development of higher education, accessibility of medical services and health care, an index of infrastructural development of the region has been formed, which reflects the possibility of including all segments of the population in productive activities and creating conditions for growth. Significant asymmetry of infrastructural development between the regions of Ukraine has been revealed, which puts them in unequal conditions for achieving inclusive growth. It is stated that the solution of this problem is possible only with the active state support and improvement of mechanisms for financing regional development projects from the State budget. The main results presented in the paper are obtained during the research «Fiscal space of inclusive development of the region» and «Security of sustainable development of regions and territorial communities of Ukraine in the context of decentralization on the basis of inclusive growth», within which the author systematizes goals, objectives and indicators of quantitative assessment of the achievement of prospects for regions inclusive development.
Cryptocurrencies are more than a decade old and several issues have been discovered since their then. One of these issues is a partial negation of the intent to “democratize” money by decentralizing control of the infrastructure that creates, transmits, and stores monetary data. The Programmatic Proof of Work (ProgPoW) algorithm is intended as a possible solution to this problem for the Ethereum cryptocurrency. This paper examines ProgPow’s claim to be Application Specific Integrated Circuit (ASIC) resistant. This is achieved by isolating the proof-of-work code from the Ethereum blockchain, inserting the ProgPoW algorithm, and measuring the performance of the new implementation as a multithread CPU program, as well as a GPU implementation. The most remarkable difference between the ProgPoW algorithm and the currently implemented Ethereum Proof-of Work is the addition of a random sequence of math operations in the main loop that require increased memory bandwidth. Analyzing and comparing the performance of the CPU and GPU implementations should provide an insight into how the ProgPoW algorithm might perform on an ASIC.
Industry 4.0 around the world. From year to year, many important cross-border and global blockchain consortia and councils are created in the world. They are aimed at developing, supporting experiences, as well as practical application, and implementation of blockchain technology. These institutions are based mainly in the USA, Great Britain, Japan, Canada, China, Luxembourg, and Dubai (eg Blockchain Embassy Asia or Global Blockchain Council -Dubai).
Saiful Izzuan Hussain, Nadiah Ruza, Nurulkamal Masseran, Muhammad Aslam Mohd Safari
Dependence structure between financial assets plays an important role in risk management. This research investigates the dependence pattern between the stock market and the potential of cryptocurrency. We employed time- varying copula and Extreme Value Theory (EVT) to model the extreme dependence between the United States (US) index stock market (S&P500) and Bitcoin. Empirical results show risk diversification for holdings of the S&P500 and Bitcoin during extreme events seem to be effective. This paper contributes to a better understanding of the dependence structure of the financial market during extreme events. This information is useful for investors who are seeking for the cross-market diversification.
We examine the long- and short-run relationships between USD/EUR official rates and implicit exchange rates, through Bitcoin as a currency vehicle, over the period from March 07, 2016 to November 22, 2019. The results show that the two exchange rates are cointegrated and that the cointegrating vector is not statistically different from the theoretical one that results from the law of one price. In the short-run, the implied rate Granger-causes the official reference rate. Our main conclusion is that Bitcoin USD and EUR prices incorporate fundamental information from the USD/EUR official exchange rate