Blockchain Papers

Ting-Hsuan Chen, Mu‐Yen Chen, Guan-Ting Du

No abstract is available for this record.

Yiming Guo, Zhen-Ling Huang, Ji Guo, Xingrong Guo · 8 authors

No abstract is available for this record.

Chenxue Yang, Zhiguo Sun

In order to better realize agricultural informatization, a data management system for agricultural supply chain, which has the characteristics of safe, credible, stable, traceable, information-sharing, and large-throughput, is needed to construct. To date, the information management method for China's agricultural supply chain is usually stored in a centralized database and file system, with weak information management capabilities, leading to problems such as theft, tampering, deletion, and inconsistencies. In light of these problems, we introduce blockchain technology which is a cutting-edge technology in digital finance and has developed rapidly. This paper proposes a data management system based on blockchain technology and affords efficient data extraction, management and access control for heterogeneous forms of data across the agricultural supply chain. The data management system includes four credible data management platforms: agricultural production information, recording transportation information, farmer-consumer transaction information, and consumer credit information. It also can add more platforms according to later needs and combine an interstellar distributed file system and smart contract technology, making it possible to conduct information security research throughout the agricultural supply chain. The proposed system effectively protects information about supply chain activities including agricultural product production, warehousing, transportation, distribution, and sales. It implements seamless connection between agricultural product production and marketing, enabling the transforming and upgrading of agriculture, thereby helping farmers increase their income and eliminate poverty.

Marco I. Bonelli

In recent years, bitcoin has been at the center of a debate: is it a financial asset or not? If it is an asset, what kind of asset is it? Is it a tradable, speculative asset, or is it a long-term investment? The debate has largely unfolded around the real nature of Bitcoin and its correlation with other asset classes. Some scholars have discussed the correlation coefficient of bitcoin using the S& P 500 Index, the Volatility Index, and gold. However, the debate is now sufficiently mature to discuss the reasons determining its correlation with other assets. We study the correlations of Bitcoin and one benchmark, a stock market index-specifically, the Nasdaq 100 Index. Our focus is on the correlation between Bitcoin and the Nasdaq 100 as a proxy for the most representative technology stocks. We show that the correlation between the two has grown substantially since 2018, and has increased more since the beginning of the COVID-19 pandemic.

Yincheng Lou, Yanmei Zhang, Shiping Chen

As one of the leading blockchain systems in operation, Ethereum has numerous smart contracts deployed to implement a variety of functions. Unfortunately, speculators introduce scams such as Ponzi scheme in the traditional financial sector into some of these smart contracts, causing millions of dollars of losses to investors. At present, there are a few of quantitative identification methods for new fraud modes under the background of Internet finance, and detection methods for the Ponzi scheme contracts on Ethereum are even less. In this paper, we propose an improved convolutional neural network as a detection model for Ponzi schemes in smart contracts. We use real smart contracts to evaluate the feasibility and usefulness of our mode. Results show that our improved convolutional neural network can overcome difficulties in training caused by different length of smart contracts' bytecodes. Compared with the state-of-the-art methods, the precision and recall rate of our model for Ponzi scheme detection are improved by 3.2% and 24.8% respectively.

Vasily Derbentsev, Andriy Matviychuk, Наталія Даценко, Vitalii Bezkorovainyi · 5 authors

This paper is discusses the problems of the short-term forecasting of financial time series using supervised machine learning (ML) approach. For this goal, we applied several the most powerful methods including Support Vector Machine (SVM), Multilayer Perceptron (MLP), Random Forests (RF) and Stochastic Gradient Boosting Machine (SGBM). As dataset were selected the daily close prices of two stock index: SP 500 and NASDAQ, two the most capitalized cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), and exchange rate of EUR-USD. As features we used only the past price information. To check the efficiency of these models we made out-of-sample forecast for selected time series by using one step ahead technique. The accuracy rates of the forecasted prices by using ML models were calculated. The results verify the applicability of the ML approach for the forecasting of financial time series. The best out of sample accuracy of short-term prediction daily close prices for selected time series obtained by SGBM and MLP in terms of Mean Absolute Percentage Error (MAPE) was within 0.46-3.71 %. Our results are comparable with accuracy obtained by Deep learning approaches.

Rizky Parlika, Pratama Wirya Atmaja

Various ways have been done by researchers from all over the world to predict the price of Bitcoin which is the first digital commodity based on blockchain. Various forecasting and computational techniques have been widely applied and continue to be refined to find a prediction package that has the closest accuracy. The purpose of this research is to test hundreds of API data shared by hundreds of Cryptocurrency Markets and as a result we have succeeded in extracting the latest bitcoin price data from 20 Crypto Markets via shared APIs. This data will then be stored in a MySQL database on hosting automatically when a condition is reached. This data can then be mined continuously using Cronjob, and to facilitate the reading of data that has been collected, we use a telegram bot as well as using a web-based application. This step is expected to help in efforts to monitor bitcoin price movements and predict future price movements.

B Vivekanadam

Blockchain is a digital ledger in which each record known as blocks and that are combined in a single list known as a chain. It is regarded as Bitcoin's backbone technology. It is also regarded as cohesive collections of digital wallets. Blockchains are primarily used by cryptocurrencies such as Bitcoin and other applications to record these transactions. A blockchain is commonly referred to as a collection of distributed databases that consists of all public transactions, records and digital events then that information is shared among the participants. Every transaction is verified and it cannot be removed. The main features of this technology are reliable, efficient operation, fault tolerance and scalability. Some of the applications are manufacturing, government and finance when the three properties met together (i.e., Efficiency, Scalability and Security). By using several computers, each transaction that is applied to a blockchain is validated. A peer-to-peer network is developed by these systems that are used to validate these forms of blockchain transactions. They work together to ensure that any transaction is legitimate until it is added to the blockchain, and invalid blocks cannot be added to the chain by these systems. When a new block is added, it can be connected to a previous block using a cryptographic hash and the chain cannot be broken and each block is recorded permanently. Blockchain can be used for an exchanging the transaction securely without an intermediate. It enables customer relationship and agile chain values and thereby integrating with IoT and Cloud technology. The functionality of distributed ledger is combined with blockchain security to solve the financial and non-financial industry problems. This paper proposes the blockchain technology with devices and creates a common platform and secure data communication.

Ricardo Carreño Aguilera, Miguel Patiño-Ortiz, Julián Patiño-Ortiz, ADAN ACOSTA BANDA

Blockchain technology apparently is a trivial innovation, but this technology has attracted huge investors in a very short period compared to other technologies, and it is still having a lot of potential applications. Smart contracts are making possible execution in an automated and safe way by using blockchain technology. Therefore, smart contracts are applied in this research for the expert system. This paper is about an expert system working with smart contracts and neural networks as the inference machine to decide on the sensors optimal distribution and taking actions when sensor readings are out of range: control lights, activating fire alarms, temperature alarms, etc. for all spaces (parks, schools, hospitals, etc.) in a smart city based on the needs, and likes of the expert system user. This expert system works using a blockchain structure on the EOSIO ecosystem with all data gathered by the sensors being saved in cloud online making internet of things environment and essential data saved in a blockchain node.

Mengyi Xie, Zuobin Liao, Liting Huang

Blockchain is a distributed shared ledger and database. Because of its unforgeable, traceable, open, and transparent, and collective maintenance features, it has laid a solid foundation of “trust”. At the same time, the blockchain also brings hidden dangers of data security. How to protect the data security of digital currency in blockchain transactions is the direction of this article. This article first analyzes the basic structure of the blockchain, and then takes Bitcoin in the digital currency as an example to introduce its technical principles and implementation process. Finally, the PBFT algorithm is proposed, which can search for the application of encryption in the blockchain consensus mechanism. The experimental data verification proves the future application prospects of blockchain-based digital currency using PBFT algorithm to protect data security.

Mobeen Ur Rehman, Sang Hoon Kang

No abstract is available for this record.

Saurabh Suratkar, Mahesh Shirole, Sunil Bhirud

A blockchain is a growing list of records, called blocks, that are linked using cryptography. Blockchain private and public keys are stored in a cryptocurrency wallet, but not the actual currency values. Wallets provide customers with the ability to send and receive virtual currency / tokens and tune their balance through interaction with blockchains. Multi-currency wallets may be broken down into 3 categories: software, hardware, and paper. Software wallets are web, mobile and desktop. Growing penetration of blockchain in many industries makes one to understand wallets in detail. There are a variety of wallet kinds to pick out from. This paper focuses on multi-currency wallets review exploring on features like supported currencies, anonymity, cost, platform support, key management, wallet recovery methods and fiat currencies supported.

N. M. Dhanya

No abstract is available for this record.

Mohd Azeem Faizi Noor, Saba Khanum, Taushif Anwar, Manzoor Ansari

Blockchain, the technology behind most popular cryptocurrency Bitcoin and Ethereum, has attracted wide attention recently. It is the most emerging technology that has changed the financial and non-financial transaction system. It is omnipresent. Currently, this technology is enforcing banks, industries, and countries to adopt it in their financial, industrial, and government section. Earlier, it solved the centralize and double-spending problems successfully. In this chapter, the authors present a study of blockchain security issues and its challenges as well. They divided the whole chapter into two parts. The primer part covers a holistic overview of blockchain followed by the later section that argues about basic operations, 51% attack, scalability issue, Fork, Sharding, Lightening, etc. Finally, they mention an intro about its adaptation (financial or non-financial) in our 24/7 life and collaboration with fields like IoT.

Dharmendra Singh Rajput, Pankaj Shukla, Thippa Reddy Gadekallu, Rajesh Kaluri · 7 authors

In today's world, security has become a major issue in our lives, and in this era, one cannot trust the government for handling their lifetime savings. That's where the bitcoin comes to our lives. In this chapter, the authors try to understand one of the famous innovative payment methods (Bitcoin), how it is used and the data structure (Merkle tree) that is used in it. Also, they discuss one of the most recent attacks that involved the use of bitcoin (Wanacry). Further, they try to understand how this hack succeeded in stealing 10,800 euros that is 8,74,290 rs from the hospital with the help of bitcoin. They also discuss the various bitcoin companies now emerging with their own security measures against such hacks.

Kyungchan Ko, Changhoon Kang, Young-Bok Park, Jongsoo Woo · 5 authors

Supply chain is an entire network of producing and delivering a specific product to a final consumer. Stainless steel is a specific product being delivered on a supply chain. It is not easy to manage and monitor the entire supply chain because a supply chain has high complexity, including various organizations and activities. Due to this difficulty, several issues occur in the process of supplying stainless steel, such as forgery and alteration. Blockchain is a decentralized and distributed ledger technology that specializes in transparency and immutability. Many companies try to introduce this blockchain technology into supply chain management to conveniently monitor their supply chain. Accordingly, the blockchain technology can make steel companies be able to investigate and protect high-quality products from counterfeited low quality products. This paper proposes a design of a blockchain-based stainless steel tracking system to thoroughly track the entire process involved in supplies from stainless steel mills to the final customers. This proposed design is based on the hyperledger fabric which is one of the most popular private blockchain platforms.

Ahmed Ibrahim, Liam Corrigan, Rasha Kashef

Traditional time series modeling techniques emphasize on predicting cryptocurrencies using classically structured data representation as numerical features to present the time-series datasets. In this paper, a novel approach to analyze time-series data charts using a modified Convolutional Neural Networks (CNNs) is proposed. The CNNs have been adopted to recognize subtle and undetectable patterns within images of time-series data charts. Our approach has been proven to achieve significant results, suggesting a need for further research into this new method for time series modeling, especially for Bitcoin.

Lokesh Vaddi

In the past eight years of Bitcoin's history, the economy has seen the price of Bitcoin rapidly grow due to its promising outlook on the future for crypto currencies. Investors have taken note of several advantages Bitcoin provides over the traditional banking system. One such trait is that Bitcoin allows for decentralized banking, meaning that Bitcoin cannot be regulated by powerful banks. There is also a market cap of 21 million Bitcoins that can be in circulation, therefore a surplus of Bitcoins cannot be "printed" which would result in inflation. Bitcoin resolves the issue with transaction security by using a block chain, or a ledger, which records the history of every transaction ever made into one long hexadecimal "chain" of anonymous transactions, which keeps transaction history transparent, but also confidential. Bitcoin as a result has become a very bullish investing opportunity, and due to the huge volatility of the Bitcoin market price, this paper attempts to aid in investment decision making by providing Bitcoin market price prediction. Our team explored several Machine Learning algorithms by using Supervised Learning to train a prediction model and provide informative analysis of future market prices. We start with Linear Regression models, and train on several important features, then We proceed with the implementation of Recurrent Neural Networks (RNN) with Long Short Term Memory (LSTM) cells. All code is written in Python using Google's Tensor Flow software library. We show that the price of Bitcoin can be predicted with Machine Learning with high degree of accuracy.

Alberto Femenias-Hermida, Cristian R. Munteanu, José M. Vázquez-Naya

One of the major factors hindering the adoption of crypto assets in general, and Bitcoin in particular, is the high level of complexity they present to the common user. Although physical coins are a possible solution, the need to place trust in the manufacturers (so that they throw away the private key) is a big drawback that has hampered their widespread use. The recent boom of the maker movement has brought in a significant number of users with access to 3D printing devices, as well as the supporting electronic and computing resources. We have taken advantage of these capabilities to develop an open source project that interested parties can use to easily print a physical model of a Bitcoin coin, along with the necessary software that allows the creation and validation of keys and addresses.

Subhasish Mohapatra, Smita Parija

The blockchain is significantly adopted widely in all domains due to its open , decentralized , distributed form of public digital ledger where all transactions are put down between people across many nodes, so that the record cannot be made diverse retrospectively without the adaptation of all successive blocks and the consensus of the network infrastructure. Here we emphasize the beauty of blockchain which is regarded as a growing chain of records fastened by the robust cryptography technique. Cryptography rooted upon a written code that needs authorized decoding and standard format of encryption. Blockchain is governed by a network that sticks fast to protocols. It would bring off nodal communication and validation of new blocks. Miners can validate transactions, and a transaction log is to be inscribed into the blockchain. Mining step clings to the application of an algorithm to validate and retrieve data. Cryptocurrency is an innovation in digi-currency that is digital by nature in which encryption is involved for the regulation and generation of units of currency. Cryptocurrency uses cryptography for data security and blockchain technology for making transactions. This mechanism of adding valid transactions to a chain of records in its entirety is remarked as a blockchain algorithm. In blockchain, every node in the network culminates in the same conclusion; each one is capable of updating the record independently, with the most promising record conceptualized as the de-facto official record in lieu of a master copy. Specific transactions broadcast this message, and every node build’s its own updated version of events. This tremendous application makes enigmatic blockchain technology totally unique. It is regarded as a revolution in recording and distributing information, because it eliminates the need of a third party to accelerate digital relationships. Blockchain technology is extensively designed to meet in various emerging aspects. It is built using emerging protocols that provide right framing for a peer-to-peer network, which is a pile of records, based on private key cryptography to verify agents’ identification. Algorithms play a vital role in the blockchain technology. A blockchain is a series of transactional interactions that do not need a trusted third-party verification for authenticity. The marshaling of digital relationships is secured by an inherent mechanism. Subsequently, it makes the application robust, simple, and sophisticated. Considering its most popular and successful application, Bitcoin is a cryptocurrency that constructs upon a consensus network algorithm called proof of work . Bitcoin was the front release of an electronic money system that assembles a peer-to-peer network to prevent double spending and validate transactions. It is completely decentralized without any central authority. In this chapter, we focus upon blockchain algorithm and its impact upon cloud-connected ecosystem.

Olivia Angela, Yen Sun

Cryptocurrency market has a potential growth since Bitcoin emerged as one of the commodity investment in Indonesia. Besides Bitcoin, there is another altcoin which rapidly developing and dominating the cryptocurrency market, Ethereum. Therefore, this study aims to analyze the factors that affect Ethereum prices through macroeconomic aspects, such as EUR/USD exchange rate and the price of gold, as well as Bitcoin and other altcoins prices in the cryptocurrency market. The time series data consists of weekly data of all variables will be utilized during the 2016-2018 period. This study will conduct an empirical analysis by using the Autoregressive Distributed Lag (ARDL) test model. The result found that only in the short term, EUR/USD affects the Ethereum prices, while the price of gold do not show any effect on Ethereum prices. Moreover, Bitcoin and 2 alt-coins (Litecoin, and Monero) affect significantly the Ethereum prices. Nevertheless, Ripple and Stellar do not show significant effect on Ethereum prices.

Weili Chen, Xiongfeng Guo, Zhiguang Chen, Zibin Zheng · 6 authors

As Ethereum's smart contracts have boomed, it has become an integral part of the blockchain ecosystem. Unfortunately, some malicious users also find the opportunity to use fraudulent means to profit. A new reported approach is to lure new users or other attackers into the contract in an attempt to make a profit by exposing seemingly obvious flaws in the contract. But in fact, the contract contains a hidden trap that ultimately benefits the creator of the contract. Such contracts are known as honeypot contracts in the blockchain ecosystem. Previous studies proposed two methods to identify such smart contracts by using symbolic execution and contract behaviors. However, these methods either make it difficult to discover new categories or fail to warn users before they lose money. To solve this problem, we propose a machine learning model to detect honeypot contracts based on N-gram features and LightGBM. Extensive experiments show that our proposed model performs well in different conditions.

Nikita Singh, Tarun Kumar, Manu Vardhan

No abstract is available for this record.

Uğur Kaya, Fırat Akba, İ̇hsan Tolga Medeni, Tunç D. Medeni

Son zamanlarda kullanımı oldukça yaygınlaşan blokzinciri teknolojisinin, İnternet teknolojisi ile beraber adı sıkça anılır olmaya başlamıştır. Blokzinciri teknolojisiyle geliştirilen Bitcoin, sanal para birimleri arasında en çok piyasa hacmini elinde bulunduran sanal para birimidir. Sanal para piyasalarının kontrolünü elinde bulunduran bir merkezi otoritenin olmaması sebebiyle fiyat manipülasyonlarına ve dışarıdan müdahalelere açık olan bu pazarda, en uçtaki yatırımcının yatırım yapabilmesi açısından yol gösterimine ihtiyaç duyulmaktadır. Son zamanlarda bu ihtiyacı karşılamak amacıyla birtakım yöntemler kullanılmaya başlanmıştır. Bu çalışmada makine öğrenmesi, zaman serileri analizi ve derin öğrenme yöntemleri kullanılarak Bitcoin fiyatlarındaki dalgalanma hakkında çeşitli tahminleme ve sınıflama yöntemleri beraber olarak değerlendirilmiştir. Bu bağlamda, koronavirüs pandemisi öncesi ve sonrasındaki Bitcoin kapanış fiyatları ve düşüş-yükseliş eğilimleri baz alınarak iki ayrı veri kümesi oluşturulmuştur. Bu veri kümeleri üzerinde tahmin ve sınıflama yöntemleri değerlendirilerek, başarıları karşılaştırılmıştır. Karşılaştırmalar sonucunda, pandemi öncesi verilerle yapılan çalışmada Destek Vektör Makineleri, pandemi sonrası verilerle yapılan çalışmada ise ARIMA en başarılı sonuçları vermiştir.