Blockchain Papers

동아대학교 금융학과 부교수, Sang Won Lee, Dong Yoon Oh

No abstract is available for this record.

Furkan Atlan, İhsan Pençe

No abstract is available for this record.

N. Kamalakshi, Naganna

No abstract is available for this record.

Aatif Jamshed, Asmita Dixit

Bitcoin has gained a tremendous amount of attention lately because of the innate nature of entering cryptographic technologies and money-related units in the fields of banking, cybersecurity, and software engineering. This chapter investigates the effect of Bayesian neural structures or networks (BNNs) with the aid of manipulating the Bitcoin process's timetable. The authors also choose the maximum extensive highlights from Blockchain records that are carefully applied to Bitcoin's marketplace hobby and use it to create templates to enhance the influential display of the new Bitcoin evaluation process. They endorse actual inspection to check and expect the Bitcoin technique, which compares the Bayesian neural network and other clean and non-direct comparison models. The exact tests show that BNN works well for undertaking the Bitcoin price schedule and explain the intense unpredictability of Bitcoin's actual rate.

Jay Mehta, Darsh Mehta, Jainam Jain, Surekha Dholay

Abstract— The technique of following a product or a batch of things throughout the supply chain to ensure that the products that reach clients are authentic and tamper-proof is known as asset tracking. The ultimate goal of an asset monitoring system is to track products along the supply chain, verifying that they haven't been tampered with and, if they have, pinpointing where the tampering took place. Traditional tracking technologies, such as BLE (Bluetooth Low Energy Beacon), which works within a limited range, RFID, and above-mentioned systems, are expensive and centralised. So, for this project, we'll use Blockchain Technology, which is an immutable, tamper-proof, decentralised distributed ledger with security features that allows us to establish an asset tracker that can follow our product along the supply chain. Ethereum is used to implement the system. Unlike other methods, there are no hardware components or large gadgets that may be removed from the original object and attached to the copy. Keywords— Blockchain, Supply Chain, Smart Contract, Keccak-256, Ethereum,GUI

Ikhlaas Gurrib, Firuz Kamalov, Linda Smail

Cryptocurrencies such as bitcoin have garnered a lot of attention in recent months due to their meteoric rise. In this paper, we propose a new method for predicting the direction of bitcoin price using linear discriminant analysis (LDA) together with sentiment analysis. Concretely, we train an LDA-based classifier that uses the current bitcoin price information and Twitter headline news in order to forecast the next-day direction of bitcoin price. The proposed model achieves highly accurate results beating several benchmark targets. In particular, the proposed approach produces forecast accuracy of 0.828 and AUC of 0.840 on the test data.

Rasa Bruzgė, Alfreda Šapkauskienė

A bibliometric analysis of Bitcoin remains of high importance as it helps to cope with emerging trends. Compared to the existing literature, this paper additionally covers the keywords and analysis of the main topics, provides status-quo information and an insight on the future direction of Bitcoin research. We used VOSviewer to perform a network analysis of the most commonly used keywords in the literature. The results of the network analysis have shown that there are four main cluster groups of keywords in different topics. Also, we used R studio to form a matrix that presented the associations and correlation coefficients between the words most frequently used in combination in abstracts of scientific articles. Bibliography analysis has shown that the main topics dealt with in Bitcoin-related literature in 2020-2021 are volatility, gold, inefficiency, safe-haven, and hedge with a potential future increase of analysis as a safe-haven. By using these results, other researchers could optimize their research by concentrating on a specific topic they are interested in and they can use the relevant keywords we have highlighted for each topic. Furthermore, we have distinguished the most active authors in each field, so that researchers could find potential collaborators in each topic, and we also established the most suitable journals for publishing. Our paper not only optimizes all research processes but also reveals the most relevant topics and identifies future direction.

Subhasish Goswami, Rabijit Singh, Nayanjeet Saikia, Kaushik Kumar Bora · 5 authors

The use of Ethereum based tokens in blockchain applications have been on the rise in recent times and accordingly, the need for proper analysis of token source codes for security vulnerabilities has become paramount. Existing symbolic analysis tools have demonstrated to be efficient in detecting many of the security vulnerabilities, but by virtue of the complex nature of the analysis they perform to detect vulnerable paths, there is a considerable increase in search time with an increase in depth. Cryptocurrencies have recently achieved the milestone of a USD 2 trillion market cap and with such a high volume of assets involved, the need for an efficient and scalable security vulnerability detection tool in an ever-increasing list of tokens becomes of utmost priority. This paper proposes a deep learning based approach for the prediction of security vulnerabilities in ERC-20 token smart contracts. The proposal proposed by this paper is based on the use of Long Short-Term Memory neural network architecture on smart contract opcodes which are in form of sequential data. The proposed solution achieves an accuracy of 93.26% when tested on ERC-20 smart contracts collected from Ethereum mainnet and thus proves to be an efficient alternative for existing symbolic tools.

Sandeep Saxena, Umesh Kumar Gupta, Renu -, Vimal Dwivedi

No abstract is available for this record.

Olli‐Pekka Hilmola

Since the inauguration of cryptocurrencies, Bitcoin has been under pressure from competing tokens. As Bitcoin is a public open ledger blockchain coin, it has its weaknesses in privacy and anonymity. In the recent decade numerous coins have been initiated as privacy coins, which try to tackle these weaknesses. This research compares mostly mature privacy coins to Bitcoin, and comparison is made from a price perspective. It seems that Bitcoin is leading privacy coins in price terms, and correlation is typically high and positive. From the earlier crypto market peak of 2017–18, only a very small number of coins are showing positive returns in 2021. It is typical that many privacy coins have lost substantial amounts of their value (ranging 80–90%) or that they do not exist anymore at all. Only Horizen and Monero have shown long-term sustainability in their value; however, their price changes follow that of Bitcoin very closely. The role of privacy coins in the future remains as an open issue.

Majia Luolun

Early power stations in China have been in operation for a long time. Due to the limitations of design, construction materials and technological level at that time, many hydroelectric generators have some defects. The computer monitoring and control system of a hydropower station refers to the measurement, control, protection and monitoring of the entire equipment of a hydropower station completed and realized by the computer system. The computer monitoring and control system of hydropower station replaces the traditional control equipment, fault recording equipment, monitoring and measuring equipment and relay protection equipment. This paper studies the full homomorphic encryption algorithm, introduces the zero-knowledge proof technology into the block chain trading protocol based on the full homomorphic encryption, and constructs the block chain that protects data privacy.

Anmol Kaushik, Anju S. Pillai

Blockchain Technology has certain inherent characteristics that can prove particularly useful to the field of IoT. It has the potential to add a layer of trust and transparency to the data reported by IoT based applications due to its decentralized and immutable nature. An application that utilizes these aspects of Blockchain has been explored in this paper. A smart inventory monitoring system that focuses on shipped goods was developed. The proposed system monitors the temperature and humidity of the goods' container. It also keeps track of whether the lid of the container was opened at a certain point or not and the duration for which it was left opened. These details are periodically uploaded to Ethereum Blockchain's Rinkeby Test Network along with a timestamp and location history. These details can then be retrieved from the Ethereum Blockchain and monitored for signs of tampering or undesirable conditions. The system was implemented on a Raspberry Pi 4. Details such as transaction construction and upload times have also been reported in the paper. The proposed system was able to provide an immutable and decentralized historical log of the shipped inventory as it passed through different stages of the delivery process.

Ferhat Şirin Sökmen, Samet Gürsoy

The gold mine has been a commodity used for thousands of years, today it is also an investment tool with the highest reliability. However; cryptocurrencies that are recently used are affecting our portfolio. Bitcoin is the most traded cryptocurrency. Since there are alternative investment instruments involved in portfolios, the relationship between these two independent values inspired the emergence of this study. The aim of this study was to investigate whether there is a causality-cointegration relationship between daily Bitcoin prices and gold prices for the periods between 10,01,2014 and 11,12,2020. In the application section, Toda Yamamoto causality and the Maki Cointegration test were applied. According to the results of the Toda Yamamoto causality test, there is a two-way causality relationship. According to the results of the Maki cointegration test, there was no long-term relationship between the series. As a result, it is expected that in the long term, investors will have a risk-reducing effect by including both investment instruments in the same portfolio.

Yılmaz Dikilitaş, Kazım Onur TOKA, Ahmet Sayar

A blockchain is a digital record of transactions. The name comes from its structure, in which individual records, called blocks, are linked together in single list, called a chain. It stands out with the rise of Bitcoin. Its popularity is increasing day by day. It provides anonymity, privacy and data integrity without any control organization. In this report, we will reveal the areas of research that have emerged. We will touch on what these research areas can bring forward. Articles are generally related to Bitcoin. But lately, this technology has entered many areas of our lives. Recommendations on future research directions are provided in this paper.

Namrata Thakur, Vinayak D. Shinde

Data security is the key to the development of modern Internet technology. The distributed, decentralized, and secured hashed mechanism of the blockchain gives a complete new point of view for the evolution of data security technology. Block chain technology is one of the major technological innovations of this century. In the last couple of years, the interest around blockchain technologies is increasing. Many implementation of blockchain technology are widely available today. Blockchain,the foundation of Bitcoin, has gain much attention in this era. Blockchain is an encrypted, immutable, distributed ledger, which allows transactions take place in a decentralized manner. Blockchain based applications expected to alter numerous fields including financial services, health care, entertainment media, Internet of Things (IoT), and many more. The Blockchain technology plays important role in the process of data security. In this paper, we will discuss about the research being done on this new domain of Computer Science. It is not only the most popular topic to discuss about, but is the most technological innovation, that is all set to reform the entire world.

Oiza Salau, Steve A. Adeshina

Document verification is a complex domain that involves processes to authenticate original documents. Some original documents like birth certificate, university diploma, contract, certificate of occupancy, Will etc. may involve serious verification and authentication practices, because fake documents can easily be created. A skillfully generated fake document is always difficult to detect and can be treated as original. With the increase of forged documents, the integrity of both the document holder and the issuing authority is jeopardized. This research is intended to address the issue of electronic document forgery and provide an alternative secure means for storing documents. The aim of this research is to design and implement a secure document verification system using blockchain. The result of this study shows how the user documents are stored securely in the blockchain, and if any change or adjustment are made to the documents the chain becomes invalid and the user will be notified

K. Kumutha, S. Jayalakshmi

No abstract is available for this record.

Alvin Ho, Ramesh Vatambeti, Sathish Kumar Ravichandran

Objective: This paper explains the working of the linear regression and Long Short-Term Memory model in predicting the value of a Bitcoin. Due to its raising popularity, Bitcoin has become like an investment and works on the Block chain technology which also gave raise to other crypto currency. This makes it very difficult to predict its value and hence with the help of Machine Learning Algorithm and Artificial Neural Network Model this predictor is tested. Methodology: In this study, we have used data sets for Bitcoin for testing and training the ML and AI model. With the help of python libraries, the data filtration process was done. Python has provided with a best feature for data analysis and visualization. After the understanding of the data, we trim the data and use the features or attributes best suited for the model. Implementation of the model is done and the result is recorded. Finding: It was discovered that the linear regression model’s accuracy rate is very high when compared to other Machine Learning models from related works; it was found to be 99.87 percent accurate. The LSTM model, on the other hand, shows a mini error rate of 0.08 percent. This, in turn, demonstrates that the neural network model is more optimized than the machine learning model. Novelty: In this work, a small GUI has been created using the tkinter library that will allow the user to input the High, Low, and Open features values and then predict the next value for the coin. This paper compares the prediction outcomes of a machine learning model and an artificial neural network model. Because linear regression provided the highest accuracy compared to the other machine learning models, we used it to compare it to the LSTM model. Keywords: Bitcoin; Block chain; Crypto currency; Machine Learning; Artificial Neural Network

Sara El-Switi, Mohammad Qatawneh

The used vehicle market is one of the most important economic sectors, which suffers from severe frauds and the absence of integrity measures since multi-variant stakeholders are involved in the vehicle trade. For example, odometer frauds have become a serious concern that cost European consumers approximately 5.6 to 9.6 billion euros per year. Therefore, a solution to track and log vehicle data is necessary to satisfy a high level of trust, data integrity, and traceability. Blockchain technology has great potential to change the way specific industries operate by eliminating middleware layers between seller and buyer. Blockchain (BC) provides a secure ledger of transactions that can be reliable even in monetary applications. The characteristics of Blockchain technology make it an excellent solution to address many issues, such as counterfeiting and trustless between parties in various applications like supply chain, healthcare, and used vehicles market. This paper surveys the status of research until 2020 related to the used vehicles market. Based on the previous literature review and analysis, there is a need for using Blockchain technology in the used vehicles market to reduce fraud by logging vehicle life-cycle events in a secure ledger. The study also shows that most of the previous work focused on collecting data from sensors and did not take into consideration the stakeholders of the application, such as insurance companies, governments, and repair shops.

Rahmeh Ibrahim, Aseel Mohammad Elian, Mohammed M. Ababneh

Blockchain is a platform technology for the cryptocurrency's applications like Bitcoin and Ethereum. The purpose of the blockchain is to eliminate the need for third trusted parties such as banks. In recent years and because of the properties of this technology like immutability and transparency, the technology was extended beyond cryptocurrencies and was exploited by various sectors like education, healthcare, finance, energy, government, and IoT providing more privacy, faster transactions and more security. In this research, we investigated Illicit accounts on Ethereum blockchain and proposed a Fraud detection model using three different machine learning algorithms: decision tree (j48), Random Forest and K-nearest neighbors (KNN). These algorithms were applied on a data set obtained from Kaggle.com containing 42 features. We have used the correlation coefficient to select the most effective features and built a new data set using 6 features only. Our research results show a significant improvement in time measurements using the three algorithms and an improvement in the F measure using the Random Forest algorithm.

Onur Gözbaşı, Buket Altınöz, Eyup Ensar Sahin

Bitcoin and other digital currencies are financial assets with high volatility, which calls for an investigation of the factors that influence their prices and thus has led to a debate on whether they are reliable investment instruments or diversification tools. The present study aims to explore the impact upon Bitcoin prices of commodities such as gold and oil, the S&P 500 index, and the volatility index and financial stress index, which represent the financial risk environment. To this purpose, we analyze this relationship using the Autoregressive Distributed Lag (ARDL) approach based on the monthly data from the 2010-2021 period. The results suggest that both in the long and short run, gold price per ounce does not have a statistically significant effect on Bitcoin price. On the other hand, an increase in crude oil prices has a negative impact on Bitcoin price in the short run, with no significant effect in the long run. The S&P 500 stock market index positively affects the Bitcoin price both in the short and long run. In addition, our analysis results also demonstrate that developments indicating increased risk in the long run tend to reduce Bitcoin returns.Keywords: Bitcoin, gold, oil, volatility, ARDL.JEL Classifications: G11; B23DOI: https://doi.org/10.32479/ijefi.11602

Helen Mary Varghese, Dhwani Apurva Nagoree, Anshu, N. Jayapandian

Cryptocurrency has developed as a new mode of money exchange since it has become easier, faster and safer. The first cryptocurrency was introduced in 2009 and since then, the growth rate of cryptocurrency has been increasing drastically. As of 2020, the cryptocurrency exchange all over the world has exceeded 300%. The researchers face many challenges during their research on the various cryptocurrencies. For example, most of the high-tech companies still do not support bitcoin on mobile platforms. High-tech companies like Google and Apple are also thinking into banning the bitcoin wallet from their app stores. The work provides a review of cryptocurrency and its types, scope on the investment plans and its advantages also discussed. The growth and comparison between bitcoins and gold is also discussed. The challenges researchers face and the security issues concerning it. This review provides an overview of how the different forms of cryptocurrency are increasing from over a decade. It explains the different types and the year in which they were invented. It also gives a brief comparison with respect to bitcoin, which is one of the most used cryptocurrency. Furthermore, it gives a brief explanation on investments, and schemes for those who are new in the cryptomarket. Later emphasizes on the security issues faced by this technology. It talks about proof of work and the different data attacks the software faced and how the issues were overcome. In the end, it talks about the challenges researchers face while researching cryptocurrency.

Wenhan Hou, Bo Cui, Ru Li

With the development of blockchain technology, the data on the blockchain represented by Bitcoin and Ethereum is exploding. Data represents people's activities, indicating that blockchain has been paid more and more attention. However, many problems are hidden behind so much data, such as security and privacy. Analyzing the data can help to find out the problems and propose methods to improve blockchain. Therefore, in order to make the blockchain well applied to various walks of life, data analysis is quite essential. In this paper, we collected the relevant literature in the field of blockchain data analysis, summarized the current analysis methods, and analyzed the research status from four aspects: security, privacy, performance and prediction of price. Finally, we discussed those research work and forecasted the future trend and challenges in this field, providing some reference for related researchers. We thought that applying machine learning technology to blockchain data analysis will become mainstream in the future.

Nensya Yuhanitha, Robiyanto Robiyanto

This study examines the potential of cryptocurrencies such as Bitcoin, Ethereum, ripple, tether, and Bitcoin cash as hedging instruments and a safe haven for the Indonesian capital market, especially during the Covid-19 pandemic era. Now, Indonesia's capital market condition is in turbulence. The benefit of this research is to help the investors make decisions on which cryptocurrencies can be an instrument hedge and safe haven in this Covid-19 pandemic era for Indonesia Stock Exchange (IDX). The data used in this study are data on the closing price of the Composite Stock Price Index (CSPI), bitcoin (BTC), Ethereum (ETH), ripple (XRP), tether (USDT), and bitcoin cash (BCH) from January 3 to June 16, 2020. Data analysis used Generalized AutoregressiveConditional Heteroscedasticity (GARCH) and Quantile Regression (QREG). This study found that Bitcoin, Ethereum, tether, and Bitcoin cash can act as a hedge, but only the ripple cannot act as a hedge. Bitcoin, Ethereum, ripple, tether, and bitcoin cash cannot act as a safe haven when the Indonesian capital market was getting extreme, like during the Covid-19 pandemic era. The roles of Bitcoin, Ethereum, ripple, tether, and bitcoin cash as safe havens will fade when conditions in the Indonesian capital market become more extreme. This research can be used as a reference for investors for their investments by looking top four cryptocurrencies as a hedging instrument. However, in severe conditions such as during the Covid-19 Pandemic, the top five cryptocurrencies cannot be used as a safe haven, as revealed in this study.