Bitcoin is considered the most valuable currency in the world. Besides being highly valuable, its value has also experienced a steep increase, from around 1 dollar in 2010 to around 18000 in 2017. Then, in recent years, it has attracted considerable attention in a diverse set of fields, including economics and computer science. The former mainly focuses on studying how it affects the market, determining reasons behinds its price fluctuations, and predicting its future prices. The latter mainly focuses on its vulnerabilities, scalability, and other techno-crypto-economic issues. Here, we aim at revealing the usefulness of traditional autoregressive integrative moving average (ARIMA) model in predicting the future value of bitcoin by analyzing the price time series in a 3-years-long time period. On the one hand, our empirical studies reveal that this simple scheme is efficient in sub-periods in which the behavior of the time-series is almost unchanged, especially when it is used for short-term prediction, e.g. 1-day. On the other hand, when we try to train the ARIMA model to a 3-years-long period, during which the bitcoin price has experienced different behaviors, or when we try to use it for a long-term prediction, we observe that it introduces large prediction errors. Especially, the ARIMA model is unable to capture the sharp fluctuations in the price, e.g. the volatility at the end of 2017. Then, it calls for more features to be extracted and used along with the price for a more accurate prediction of the price. We have further investigated the bitcoin price prediction using an ARIMA model, trained over a large dataset, and a limited test window of the bitcoin price, with length $w$, as inputs. Our study sheds lights on the interaction of the prediction accuracy, choice of ($p,q,d$), and window size $w$.
Kalpanasonika R, Sayasri S M, Vinothini A, Suga Priya H
The accusative of this paper is to predict the bitcoin price accurately by taking various parameters into consideration which affects the bitcoin value. Here multi-layer perceptron algorithms under deep learning are used to predict the price of crypto-currency. Many researchers have analysed the crypto-currency features in many ways such as, market price prediction, the impact of cryptocurrency in real life. It has the ability to make long-term prediction of the exchange price in crypto-currencies particularly in US dollar, based on historical trends. The bitcoin cost prediction is done based on the data set which consists of 13 features relating to the crypto-currency price recorded daily over the period of particular range.
Supply chain traceability is one of the most promising use cases to benefit from characteristics of blockchain, such as decentralization, immutability and transparency, not required to build prior trust relationships among entities. A plethora of supply chain traceability solutions based on blockchain has been proposed recently. However, current systems are limited to tracing simple goods that have not been part of the manufacturing process. We recommend a method that allows for the traceability of manufactured goods, including their components. Products are represented using non-fungible digital tokens that are created on a blockchain for each batch of manufactured products. To create a link between a product and the components that are needed to produce it, we propose “token recipes” that define the amount of tokenized goods required for minting a new token. As input tokens are automatically and transparently consumed when creating a product token, the physical process of producing a new item out of existing components is projected onto the ledger. This ultimately leads to the complete traceability of goods, including the origin of inputs. Evaluating the performance of the system, we show that a prototypical implementation for the Ethereum Virtual Machine (EVM) scales linearly with the amount of the input and goods tracked.
The promise of immutable documents to make it easier and less expensive for consumers and producers to collaborate in a verifiable way would represent an enormous progress, especially as companies strive for establish service contracts which are based on the flow of many small transactions using machine-to-machine communication. The blockchain technology logs these data, verifies the authenticity and make them available for service offers. This work deal with an architecture enabling to setup order processing between consumers and producers using blockchain. In this way, the technical feasibility is shown and the special characteristics of blockchain production networks will be discussed.
Blockchain technology had become evident since 2008 when Santoshi Nakamoto aimed to serve blockchain as a bond ledger of the cryptocurrency bitcoin. It should never be compared to any existing technologies like the internet. Blockchain is pleased with the fact that it provides high satisfaction and a trust bond to its users. There are significant implementations of blockchain technology across various sectors of a country which includes the agricultural venture, education venture, and supply chain management systems. Blockchain technology can be useful in countries like India, where the agricultural sector perturb about one-sixth of the total GDP of the country and also about half of the employees working in that country. So we will discuss several implementations of blockchain, which are spoonful in transforming a nation.
2008 yılında yayınlanan "Bitcoin: A Peer-to-Peer Electronic Cash System" adlı makale sayesinde bilgi sahibi olduğumuz Bitcoin, bilimsel litaratüre yeni terimler kazandırarak popülerliğini arttırmaktadır. Alternatif sanal para olarak geliştirilen Ethereum, merkezi bir sunucu veya bir kontrol noktaya ihtiyaç duymadan, karşılıklı uçlar arası anonim ve ucuz şekilde varlık transferine olanak sağlayan bir sistemdir. Blokzincir yapısının en yaygın kullanımı olan Bitcoin ve altcoinlerdir. Kripto paralar madencilik olarak adlandırılan ve zorlu bir algoritmanın çözümü ile gerçekleşmektedir. Sistemde yer alan herhangi bir madenci bu çözümü elde etmek için elinde bulunan ekran kartı ve işlemci gücünü kullanmaktadır. Bu çalışmada GPU'ların barındırdığı işlemcilerin, kayan noktalı işlem hesaplamalarında daha verimli olmaları sebebiyle Ethereum madenciliğinde kullanılan çeşitli ekran kartlarının performansları 4 kademeli bir iyileştirme paketi ile artırılarak karşılaştırılmıştır. Önerilen iyileştirme metotları için kullanılan ekran kartlarının model ve bellek miktarları şu şekildedir: 4 GB AMD R9 290, 4 GB AMD R9 380, 8 GB AMD R9 390, 4 GB AMD RX 560, 4 GB AMD RX 470, 4 GB AMD RX 480, 4 GB AMD RX 570, 4 GB AMD RX 580, 6 GB NVIDIA GTX1060, 8 GB NVIDIA GTX1070, 8 GB NVIDIA GTX1080. Bu çalışmanın en önemli amacı, Ethereum madenciliğine özgü Ethash özet algoritmasında iyileştirme yöntemleri uygulamaktır. Bu amaçla, AMD ve NVIDIA yonga seti grafik kartlarının daha düşük güç tüketimi ile daha hızlı algoritmalar çözmelerini sağlamak için iyileştirmeler yapılmıştır. Grafik kartları fabrika ayarlarıyla çalıştırıldığında, hiçbiri geçerli döviz kurlarından dolayı fayda getiremeyecek durumdadır. Algoritmanın hızını arttırmanın yanı sıra güç tüketimini azaltmak kar bölgesine geçiş için önemli bir faktör olmuştur. Yapılan çalışmalar sonucunda elde edilen değerlere bakıldığında yaklaşık % 30 performans artışı görülmüştür. Ayrıca iyileştirme paketi ile ekran kartlarının tükettiği elektrik enerjisi yüzde 20 ile yüzde 30 arası azaltılmıştır. Anahtar Kelimeler: Ethereum, Blokzincir, Kripto para madenciliği, GPU madenciliği
Open access
Blockchain Technology Applications and Security
Currency Recognition and Detection
Advanced Steganography and Watermarking Techniques
Bushra Hameed, Muhammad Murad, Abdul Noman, Muhammad Umar Javed · 8 authors
Blockchain is a decentralized and shared dis-tributed ledger that records the transaction history done by totally different nodes within the whole network. The technology is practically used in the field of education for record-keeping, digital certification, etc. There have already been several papers published on this, but no one can’t find a single paper covering the blockchain-based educational projects. So, There is a gap of latest trends to education. Blockchain-based educational projects resolve the issues of today’s educators. On that basis, we conclude that there is a need for conducting a systematic literature review. This study, therefore, reviews the artistic gap between these two based on educational projects. For this purpose, the paper focuses on exploring some block-chain based projects and protocols that are used in these projects. It also analyses the block-chain features that are being used and the services are offered by the existing educational projects using block-chain features to improve the execution of this technology in education.
The electronic transition has been gaining a large groundin recent decades due to the use of crypto currencies. One of the most popular is Bitcoin. It is open source, the transactions and the issuance of bitcoins occur collectively through the network.The analysis of the behavior of Bitcoin becomes a relevance to the prediction Price and achieve successful investments in it.This review is conducted for the analysis and comparison of the of the different prediction methods focused on the bitcoin price. Anemphasis is placed on those who have a structure as the basis of the ARIMA model, then adding to the hybrid methods, which use neural networks to complete the method.
Anders Stensås, Magnus Frostholm Nygaard, Khine Kyaw, Sirimon Treepongkaruna
This paper investigates whether Bitcoin acts as a diversifier, hedge or safe haven tool for investors in major developed and developing markets, as well as for commodities. This paper employs the GARCH Dynamic Conditional Correlation (DCC) model. The sample covers seven developed and six developing countries, five regional indices and 10 commodity series. The results show that Bitcoin acts as a hedge for investors in most of the developing countries such as Brazil, Russia, India and South Korea, but only as a diversifier for investors in developed countries and for commodities. Moreover, Bitcoin acts as a diversifier for all the 10 commodities studied here. During the US election in 2016, Brexit referendum in 2016, and the burst of Chinese market bubble in 2015, Bitcoin acted as a safe haven asset for both the US and non-US investors. Understanding the role of Bitcoin is important for financial market participants who seek protection against market turmoil and downward movements. Furthermore, our findings would be of interests to regulators and governments to engage in more discussion of the role of Bitcoin in financial markets. This paper contributes to the ongoing debate on the usefulness of Bitcoin for investments. Furthermore, it distinguishes the benefits of Bitcoin as a diversifier, hedge and safe haven to investors in the developed versus developing markets.
In the last century, the automotive industry has arguably transformed society, being one of the most complex, sophisticated, and technologically advanced industries, with innovations ranging from the hybrid, electric, and self-driving smart cars to the development of IoT-connected cars. Due to its complexity, it requires the involvement of many Industry 4.0 technologies, like robotics, advanced manufacturing systems, cyber-physical systems, or augmented reality. One of the latest technologies that can benefit the automotive industry is blockchain, which can enhance its data security, privacy, anonymity, traceability, accountability, integrity, robustness, transparency, trustworthiness, and authentication, as well as provide long-term sustainability and a higher operational efficiency to the whole industry. This review analyzes the great potential of applying blockchain technologies to the automotive industry emphasizing its cybersecurity features. Thus, the applicability of blockchain is evaluated after examining the state-of-the-art and devising the main stakeholders' current challenges. Furthermore, the article describes the most relevant use cases, since the broad adoption of blockchain unlocks a wide area of short- and medium-term promising automotive applications that can create new business models and even disrupt the car-sharing economy as we know it. Finally, after strengths, weaknesses, opportunities, and threats analysis, some recommendations are enumerated with the aim of guiding researchers and companies in future cyber-resilient automotive industry developments.
Tejasvi Alladi, Vinay Chamola, Reza M. Parizi, Kim‐Kwang Raymond Choo
The potential of blockchain has been extensively discussed in the literature and media mainly in finance and payment industry. One relatively recent trend is at the enterprise-level, where blockchain serves as the infrastructure for internet security and immutability. Emerging application domains include Industry 4.0 and Industrial Internet of Things (IIoT). Therefore, in this paper, we comprehensively review existing blockchain applications in Industry 4.0 and IIoT settings. Specifically, we present the current research trends in each of the related industrial sectors, as well as successful commercial implementations of blockchain in these relevant sectors. We also discuss industry-specific challenges for the implementation of blockchain in each sector. Further, we present currently open issues in the adoption of the blockchain technology in Industry 4.0 and discuss newer application areas. We hope that our findings pave the way for empowering and facilitating research in this domain, and assist decision-makers in their blockchain adoption and investment in Industry 4.0 and IIoT space.
Blockchain Technology is an emerging technology nowadays. The Blockchain was first used as a Peer-to-Peer ledger for registering Bitcoin transactions. The blockchain is a singly linked list which consists of a number of transactions. The blockchain is a decentralized distributed ledger which consists of a number of blocks organized in the form of a chain. A block in blockchain consists of two parts data and hash pointer. The first block in the blockchain is known as genesis block. The transactions and data in the block are secured by cryptography. The data inside a block in blockchain can be anything like bank transactions, backup data etc., which are recorded chronologically and publicly. The Hash pointer of a block is a unique code generated by a hash function like SHA256, SHA-3 etc., the hash function used in bitcoin blockchain. A block consists of a public key and a private key, using hash function digital signature is generated to the block. This is how the data inside the blockchain is so secured. The blocks are added into the blockchain by verifying the transaction in the block, the transactions are verified by miners. The miners use consensus algorithm to solve the blocks.
Yury Yanovich, Igor Shiyanov, Timur Myaldzin, Ivan Prokhorov · 6 authors
Counterfeit and unaccounted postage stamps used on mailings cost postal administrations a significant amount of money each year. Corporate and individual clients become victim to stamp fraud and incur losses when security teams investigate such mailings. The blockchain technology is supposed to be a solution to make postage stamps market transparent and to guarantee invariability of stamps volume produced and used. The blockchain-based supply chain for postage stamps is introduced in the article.
We study the probabilistic distribution of the confirmation time of Bitcoin transactions, conditional on the current memory pool (i.e., the queue of transactions awaiting confirmation). The results of this paper are particularly interesting for users that want to make a Bitcoin transaction during `heavy-traffic situations', when the transaction demand exceeds the block capacity. In such situations, Bitcoin users tend to bid up the transaction fees, in order to gain priority over other users that pay a lower fee. We argue that the time until a Bitcoin transaction is confirmed can be modelled as a particular stochastic fluid queueing process (to be precise: a Cramér-Lundberg process). We approximate the queueing process in two different ways. The first approach leads to a lower bound on the confirmation probability, which becomes increasingly tight as traffic decreases. The second approach relies on a diffusion approximation with a continuity correction, which becomes increasingly accurate as traffic intensifies. The accuracy of the approximations under different traffic loads are evaluated in a simulation study.
Agri-food trade has a profound impact on social stability and sustainable economic development. However, there are several technological problems in current agricultural product transactions. For example, it is almost impossible to improve the efficiency of transactions and maintain market stability. This paper designs a novel Food Trading System with COnsortium blockchaiN (FTSCON) to eliminate information asymmetry in the food trade, in order to establish a sustainable and credible trading environment, the system uses consortium blockchain technology to meet the challenge of different authentications and permissions for different roles in food trade. Meanwhile, we have used the online double auction mechanism to eliminate competition. We also have designed a improved Practical Byzantine Fault Tolerance (iPBFT) algorithm to improve efficiency. In addition, a case study based on a series of data from Shandong Province, China indicate that the FTSCON can achieve profit improvement of merchants. Therefore, the proposed system proved to have high commercial value.
Bitcoin it is digital currency used for any Electronic Financial Transactions, created in 2008 by Satoshi Nakamoto as Peer-to-Peer Electronic System cash. The precise prediction of bitcoin exchange rate with respect to the US dollar is an essential matter because it effected on the world economic constancy. Meanwhile the technology that used in Bitcoin has flickered a revolution in world. This paper aim to a survy on the use artificial neural networks to predict the exchange rate of a Bitcoin(BTC ) currency. https://doi.org/10.24897/acn.64.68.172
Bitcoin, merkezi otoriteye ihtiyaç duymayan, dağıtık ve dijital bir para birimi olarak, son yıllarda finans dünyasındaki popüler konuların başında gelmektedir. İlk dönemde Bitcoin’in finansal özelliklerine duyulan ilgi, zaman içerisinde Bitcoin’e hayat veren blok zinciri teknolojisine doğru kaymaya başlamıştır. Hemen her gün yeni bir uygulama alanını duymaya başladığımız blok zinciri teknolojisi alanındaki akademik araştırmalar sınırlı sayıdadır. Ülkemizde de gerek uygulama gerekse akademik anlamda yeterli sayıda çalışma olmadığını söyleyebiliriz. Bu inceleme, blok zinciri teknolojisini sistematik olarak gözden geçirerek, kullanım alanlarını, açık noktalarını ve gelecek beklentilerini tartışmaktadır.
The food supply chain is a complex system that involves a multitude of "stakeholders" such as farmers, production factories, distributors, retailers and consumers. "Information asymmetry" between stakeholders is one of the major factors that lead to food fraud. Some current researches have shown that applying blockchain can help ensure food safety. However, they tend to study the traceability of food but not its supervision. This paper provides a blockchain-based credit evaluation system to strengthen the effectiveness of supervision and management in the food supply chain. The system gathers credit evaluation text from traders by smart contracts on the blockchain. Then the gathered text is analyzed directly by a deep learning network named Long Short Term Memory (LSTM). Finally traders' credit results are used as a reference for the supervision and management of regulators. By applying blockchain, traders can be held accountable for their actions in the process of transaction and credit evaluation. Regulators can gather more reliable, authentic and sufficient information about traders. The results of experiments show that adopting LSTM results in better performance than traditional machine learning methods such as Support Vector Machine (SVM) and Navie Bayes (NB) to analyze the credit evaluation text. The system provides a friendly interface for the convenience of users.
Blockchain and Cryptocurrencies are gaining unprecedented popularity and understanding. Meanwhile, Ethereum is gaining a significant popularity in the blockchain community, mainly due to the fact that it is designed in a way that enables developers to write smart contract and decentralized applications (Dapps). This new paradigm of applications opens the door to many possibilities and opportunities. However, the security of Ethereum smart contracts has not received much attention; several Ethereum smart contracts malfunctioning have recently been reported. Unlike many previous works that have applied static and dynamic analyses to find bugs in smart contracts, we do not attempt to define and extract any features; instead we focus on reducing the expert's labor costs. We first present a new in-depth analysis of potential attacks methodology and then translate the bytecode of solidity into RGB color code. After that, we transform them to a fixed-sized encoded image. Finally, the encoded image is fed to convolutional neural network (CNN) for automatic feature extraction and learning, detecting compiler bugs of Ethereum smart contract.
Amaç: Kripto parabirimleri teknolojinin gelişmesiyle birlikte son yıllarda önem kazanmış ve dahaçok kullanılır hale gelmiştir. Merkezi bir otoriteye bağlı olmayan vekriptografik sistemler ile güvenliği sağlanan bu para birimlerinden en bilineniBitcoin’dir. Bu çalışmada, başlıca kripto para birimleri ve işleyiş süreçleriincelenmiştir. Buna ek olarak Bitcoin’in döviz, hisse senedi emtia piyasalarıve faiz ile olan ilişkisi ele alınmıştır. Yöntem: Çalışmadakullanılan veri setinin frekansı aylık olup Mart-2012 ile Mayıs-2018 döneminikapsamaktadır. Zaman serisi yöntemlerinden Johansen Eşbütünleşme ve GrangerNedensellik analizleri uygulanmıştır.Bulgular: Çalışmanınsonuçlarına göre, Bitcoin fiyatlarının artan bir trende ve yüksek birvolatiliteye sahip olduğu görülmektedir. Faiz değişkeni ile Bitcoin fiyatları arasında diğer analizler ve Grangernedensellik testi sonuçlarına göre istatistiksel olarak anlamlı bir ilişkivardır.