M. Sivaram, E. Laxmi Lydia, Irina V. Pustokhina, Denis A. Pustokhin · 7 authors
The booming applications of bitcoin Blockchain technologies made investors concerned about the return and risk of financial products. So, the return rate of bitcoin must be foreseen in prior. This research article devises an effective return rate prediction technique for Blockchain financial products based on Optimal Least Square Support Vector Machine (OLS-SVM) model. The parameter optimization of the LS-SVM model was performed using hybridization of Grey Wolf Optimization (GWO) with Differential Evolution (DE), called optimal GWO (OGWO) algorithm. The hybridization process is performed to eliminate the local optima problem of GWO and enhance the diversity of the population. To verify the goodness of the proposed model, the Ethereum (ETH) return rate was chosen as the target and experimental analysis was performed on it to verify the predictive results on the time series. The experimental outcome was analyzed in terms of two performance measures namely Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The obtained simulation outcome infers that the OLS-SVM model yielded better predictive outcome of the return rate of financial products.
Bitcoin is one of the most valuable cryptocurrency in the world with the prices as high as 19,783 United States Dollar(USD) in December of 2017. It made Bitcoin a very profitable market for investment but Bitcoin saw many ups and down as well. Today’s Bitcoin price is 3913 USD but that doesn’t mean that the prices always keep falling. The price of Bitcoin vary over time and is governed by various factors, like the market it is being traded in, scarcity, supply and demand. What has made Bitcoin valuable is that it can be used as a currency, we can pay a part or a fraction of Bitcoin to a person in exchange for something and the part is easily verifiable by blockchain. The small number of Bitcoin, roughly 16 million Bitcoins for the entire world has made it scare and above that its high utility makes it more prestigious.Trading of Bitcoin has proved to be very profitable to many people but the risk in trading is huge as the market of Bitcoin is very volatile. To decrease the risks, this project has been carried out to predict the price of Bitcoin using Recurrent Neural Network(RNN), Long Short Term Memory (LSTM) and Linear Regression(LR) to predict the price of Bitcoin. Evaluation of these algorithms is carried out to determine which among the two is better for the prediction of Bitcoin prices. The dataset used contains minute by minute prices of Bitcoin of over 5 years and contains almost 30,00,000 entries. Since, the dataset used is a big data, evaluating the performance of algorithms over a large dataset will give accurate results.
The current land registration process involves a lot of vulnerabilities and people uses it to cheat the common people and the government. This paper discusses about a secure land registry implemented using blockchain which works on the basis of majority consensus. By implementing the land registry in blockchain, the security issue is resolved to a great extent. The hash value calculated for each block will be unique as it is linked to the hash of the previous block. The algorithm that is used for hashing is SHA256. Along with SHA256, Proof Of Work(PoW) algorithm is also used which makes the information related to each transaction more secure. Message digest that is generated for each block is of fixed size and each hash represents a complete set of transaction within a given block. The proposed land registry blockchain network consists of 12 nodes which calculates the proof of work. Nodes are responsible for verifying a transaction, mining a new block and adding the new block to the blockchain. A total of 200 land transactions are recorded using the blockchain methodology which offers a tamper proof and updated version of land registry. Elliptic curve cryptographic algorithm is used for signature generation which is used for verifying whether the transaction is signed by the owner or not. Merkle tree is used for linking the transactions using hash and in turn reduces the disk usage. The proposed implementation of land registry using blockchain thus offers a 99% reduction in manual effort spent in record keeping.
Bitcoin is a current popular cryptocurrency with a promising future. It’s like a stock market with time series, the series of indexed data points. We looked at different deep learning networks and methods of improving the accuracy, including min-max normalization, Adam optimizer and windows min-max normalization. We gathered data on the Bitcoin price per minute, and we rearranged them to reflect Bitcoin price in hours, a total of 56,832 points. We took 24 hours of data as input and output the Bitcoin price of the next hour. We compared the different models and found that the lack of memory means that Multi-Layer Perceptron (MLP) is ill-suited for the case of predicting price based on current trend. Long Short-Term Memory (LSTM) provides relatively the best prediction when past memory and Gated Recurrent Network (GRU) is included in the model.
Bin Yu, Ping Zhan, Ming Lei, Fang Zhou · 5 authors
Currently, food quality has become a major concern for the food industry. To efficiently detect food quality problems during the production process, food enterprises must build quality monitoring systems. However, in a traditional quality monitoring system, data tampering and centralized storage have become barriers to reliability. In addition, due to lack of sufficient automation, traditional quality monitoring approaches are usually inefficient. Fortunately, blockchain is a promising technology that is tamper-proof and decentralized. Moreover, smart contracts, which are executable codes on the blockchain platform, are able to conduct transactions between mutually untrusted parties and are self-executing and self-verifying. By combining smart contracts and quality evaluation models, this paper presents an intelligent quality monitoring system for fruit juice production. This system has the characteristics of high automation and high reliability. In this system, response surface models are established based on preproduction data, and the optimal production condition for each stage is identified. During the actual production process, smart contracts are executed to record production data on a blockchain. These data serve as the inputs for evaluation models. Based on the evaluation outcome, smart contracts will decide whether the production process can be resumed or not. To evaluate the feasibility of the presented system, a prototype version of the quality monitoring system for flat peach juice production is implemented based on the Ethereum platform and executed in the Remix IDE.
Bitcoin is considered to be most valuable and expensive currency in the world. Besides being first decentralized digital currency, its value has also experienced a steep increase, from around 1 dollar in 2010 to around 18000 in 2017. In recent years, it has attracted considerable attention in a diverse set of fields, including economics, finance and computer science. In economics, the primary focus has always been on studying how it affects the market, determining reasons behinds its price fluctuations, and predicting its future prices. In computer science, the focus is on its vulnerabilities, scalability, and other techno-cryptoeconomic issues. Firstly, we are going to collect the historical data of Bitcoin prices over the years 2013 to 2019 and do prediction for the year 2020. We have aimed to justify the usefulness of traditional Autoregressive Integrative Moving Average (ARIMA) model for predicting bitcoin prices. We have predicted the closing price of bitcoin for first seven days of January 2020. Further, we have created web services using ASP.NET to make the predictions on bitcoin price online and lastly, we have plotted the results in a responsive chart using Highcharts.
Günümüzde kripto para birimlerinin önemi gittikçe artmaktadır. Kripto para birimleri sanal oyun platformlarında kullanılırken, şu an pek çok kurum ve kuruluş tarafından ödeme aracı olarak kullanılmaktadır. Güvenlik risklerine karşı blockchain (Blok Zinciri) adı verilen algoritması ile üretimi sağlanmaktadır. Kripto para fiyatlarının doğru olarak tahmin edilmesi yatırımcı ve karar vericiler açısından büyük önem taşımaktadır. Bu çalışma kapsamında en çok kullanılan dört kripto para birimine (Bitcoin, Ethereum, Ripple, Litecoin) ait fiyat değerleri tahmin edilmiştir. Çoklu kırılma testinden yararlanılarak her seriye ait kırılmalar belirlenerek analiz genişletilmiştir. Ele alınan sanal para değerlerini doğru bir şekilde tahmin etmek amacıyla hem klasik zaman serisi modellerinden hem de üç farklı tür yapay sinir ağı modelinden faydalanılmıştır. Ayrıca elde edilen tahminler üzerinde basit birleştirilme teknikleri uygulanmıştır. Rassal yürüyüşün egemen olduğu bu seriler arasından, özellikle işlem hacmi ve bilinilirliği en fazla olan Bitcoin sanal parasında rassal yürüyüş modelinden daha iyi sonuçlar elde edildiği gözlemlenmiştir.
Internet technology has driven the dissemination revolution of images, but also makes the illegal reproduction and unauthorized use of images extremely rampant. At present, the registration of digital copyright of images should be authorized by authoritative management agencies. There are many problems, such as long audit cycle, no substantive review, difficulty in proof, high cost, centralized storage and so on. Based on blockchain technology and SIFT local feature extraction algorithm, this paper studies and implements a new generation of image digital copyright system. SIFT algorithm is used to extract the invariant features of image such as angle of view, brightness and rotation, etc. which will constitute the local feature vector set of the image, and these local feature vector sets are regarded as the only copyright basis of the image. Even if the image is modified by scaling, rotation and brightness, local features can still be extracted correctly, which can effectively prevent copyright registration of infringing images; Furthermore, IPFS (Inter-Planetary File System) was utilized for distributed storage of images' copyright features; Finally, Hyperledger Fabric and smart contract (chaincode) are used to realize copyright registration, copyright transfer and other functions. The experimental results show that the system has the advantages of automatic similar infringement detection, decentralized storage, tamper-proof and traceability.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
The term digital is now becoming the prefix for everything done traditionally. Now currency has also become a part of it. And we use the term digital currency or more precisely cryptocurrency for it. Blockchain the core concept or the power behind the success of Bitcoin is one of the most trending and common topics for digital currency these days. The blockchain serves as a public ledger and transactions stored using this methodology are almost impossible to tamper. Blockchain offers a lot of features like decentralization, auditable recordkeeping, persistent storage, efficiency, and security. Blockchain and its use are not only limited to the cryptocurrency but in various other fields as well. There are advantages of blockchain in digital currency but it does not mean that it's all perfect, it has some disadvantages and limitations as well. In this paper, we have first explained what blockchain technology is and what is a digital currency. Then we have presented a list of work done in the field of blockchain and digital currency previously. Finally, we have also discussed the future research direction in this field.
Temiloluwa I. Adegboruwa, Steve A. Adeshina, Moussa Mahamat Boukar
Bitcoin is the first digital currency that uses decentralization to solve the issue of trust in performing the functions of a digital currency successfully. This digital currency has shown extraordinary growth and intermittent plunge in value and market capitalization over time. This makes it important to understand what determines the volatility of bitcoin and to what extent they are predictable. Long Short Term Memory Neural Networks (LSTM-NN) have recently grown popular for time series prediction systems but there has been no consensus on methods to model time series inputs for LSTMs, this paper proposes the need for this problem to be solved by conducting an experimental research on the efficacy of an LSTM-NN given the form of its time-series input features.
The world has more than 5000 digital-currencies, bitcoin is one of it, which has more than 5.8 million dynamic client and approximately more than 111 exchanges throughout the world. So, the aim for this paper is to do the near prediction of the price of Bitcoin in USD. Precious details are taken from the price index of Bitcoin. A Bayesian recurrent hierarchical (RNN) neural network and a long-term memory (LSTM) network can accomplish this function. The total identification accuracy of 52% and an 8% RMSE is obtained by the LSTM. In contrast to the profound training systems, the common ARIMA method for the prediction of time series. This model have not much efficient as deep learning model can be performed. The deep learning methods were predicted to outperform the poorly performing ARIMA prediction. So here we used Gated Recurrent Network model (GRU) to forecasting Bitcoin price Eventually, all deep learning models have a GPU and CPU that beat the GPU implemented by 94.70 percent for their GPU training time.
In the Architecture, Engineering, construction and Operations (AEcO) there is a growing interest in the use of the building Information modelling (bIm). Through integration of information and processes in a digital model, bIm can optimise resources along the lifecycle of a physical asset. Despite the potential savings are much higher in the operational phase, bIm is nowadays mostly used in design and construction stages and there are still many barriers hindering its implementation in Facility management (Fm). Its scarce integration with live data, i.e. data that changes at high frequency, can be considered one of its major limitations in Fm. The aim of this research is to overcome this limit and prove that buildings or infrastructures operations can benefit from a digital model updated with live data. The scope of the research concerns the optimisation of Fm operations. The optimisation of operations can be further enhanced by the use of maintenance smart contracts allowing a better integration between users' behaviour and maintenance implementation. In this case study research, the Image recognition (Imr), a type of Artificial Intelligence (AI), has been used to detect users' movements in an office building, providing real time occupancy data. This data has been stored in a bIm model, employed as single reliable source of information for Fm. This integration can enhance maintenance management contracts if the bIm model is coupled with a smart contract. Far from being a comprehensive case study, this research demonstrates how the transition from bIm to the Asset Information model (AIm) and, finally, to the Digital Twin (i.e. a near-real-time digital clone of a physical asset, of its conditions and processes) is desirable because of the outstanding benefits that have already been measured in other industrial sectors by applying the principles of Industry 4.0.
We present a new Bitcoin coin selection algorithm, "coin selection with leverage", which aims to improve upon cost savings than that of standard knapsack like approaches. Parameters to the new algorithm are available to be tuned at the users discretion to address other goals of coin selection. Our approach naturally fits as a replacement for the standard knapsack ingredient of full coin selection procedures.
Internet of Things devices provide data from existing sensors and usually have limited resources from computing performance to storage. That happens because IoT devices are required to be able to save much energy as possible, so the network lifetime of the IoT devices will be more optimal. The limitations of computing and storage reduce the level of security and trust in the IoT network environment itself. Blockchain can guarantee data security and reliability, as well as solve security problems in the IoT network. There is some research focused on modifying blockchain without eliminating security features and data reliability. This technology can be applied to the IoT network. This type of blockchain is usually called a lightweight blockchain. For example, a lightweight blockchain called LightChain, it modifies Proof-of-Work consensus algorithm. It is reported the use of this modified consensus algorithm can reduce computing power by 39.32%. This study will show some lightweight blockchain concepts that exist today and allow them to be applied in conjunction with IoT technology.
Khin Su Su Wai, Ei Chaw Htoon, Nwe Nwe Myint Thein
Student records (SR) are needed to be regularly protected for safe access and security control. The blockchain system can support security, confidentiality, unchangeable, transparency and access control service. Although Hyperledger Fabric blockchain is a scalability modular architecture, various configuration elements affect the performance of transaction access time. Moreover, it cannot provide an efficient indexing capability on the transaction. In this paper, a storage structure that provides better access time is presented. Firstly, the suitable block size is proposed for transactions based on the configuring parameter and the transaction arrival rate to reduce the latency of transaction storage time. Secondly, the metadata of the SR block is replicated on an off-chain database to overcome the limitation of indexing capability and performance issue. SR data will be accessed transparently with greater performance and lower the costs of manpower and time.
Muneer Bani Yassein, Farah Shatnawi, Saif Rawashdeh, Wail Mardin
The Blockchain technology is the most widely used and known of the cybersecurity techniques in recent years. This technology contained a lot of techniques, which are economic models, mathematics, cryptography, and algorithms. It is vital for several reasons, which are solving the synchronization problem and does not require the presence of more than two parties. In this paper, we survey Blockchain technology in terms of the consensus algorithms, the architecture, and the main features of this technology. This survey is constructed by explaining the importance of the privacy and security of the blockchain, issues, and some solutions if possible exists. This paper contributes to supporting the researchers who want to study the Blockchain Technology in terms of concept, applications, "security and privacy issues and solutions", and work mechanism of it.
Blockchain is the name given to the technology that allows any data set to be stored in a distributed manner. It provides a secure structure with its distributed structure and provides a transparent system with the data set easily accessible by each user. Bitcoin application using blockchain infrastructure has gained attention with its reliability, robustness and performance. Thus, the blockchain is provided to reach large masses. Although the blockchain stands out as the technology of the future, it presents several disadvantages according to the application fields. In this study, blockchains performed on application basis were compared. The advantages and disadvantages of this system, which is called the technology of the future, are examined and compared in detail.
Technology has become an integral part of our life. One of the most emerging technologies of the 21st century is blockchain. It is a revolution for the digital world as it brings a new perspective of security, efficiency, and productivity of different frameworks. It works as a distributed database that is shared among a decentralized network of computers. It stores information about the transaction that is made with cryptocurrency and is maintained with the help of different computers which are linked in a peer-to-peer network. No single user can control the transactions, but everyone can inspect it. The information about the transactions is assembled as a “block” and these blocks are linked with each other as a “chain”. That's why it is called blockchain. The information inside blocks is immutable. The technology of blockchain is so efficient that it is not only used in securing financial information but also in credit history, real estate, public transport, music streaming, healthcare and so forth. According to Don and Alex Tapscott (2016), blockchain records not just financial transactions but virtually everything valuable. Currently, there is a wide spectrum of blockchain applications. The purpose of the research paper is to discuss some of the utilization of blockchain and they are Cybersecurity, Internet of Things (IoT), Fintech, Cloud Storage, Media, Travel, and Education. Furthermore, this paper examines both aspects, advantages, and disadvantages, of the blockchain. Finally, it identifies the problem areas of the technology that can be studied further to increase the effectiveness of blockchain.