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.
Taiguara Melo Tupinambás, Rafael Aeraf Leao Cadence, André Lemos
Cryptocurrencies prices forecasting is a complex theme due to the chaotic market behavior and the influence of external events. Therefore, inference models should offer, in addition to a satisfying accuracy, reasonable interpretability, so that investors can decide based on their own knowledge. However, many studies in this subject focus on model accuracy and leave much to be desired in terms of simplicity and interpretability. This work proposes the use of Mamdani interpretable fuzzy inference models for forecasting cryptocurrency price variation. For that, a genetic algorithm to optimize models accuracy is employed, limiting the quantity of rules and antecedents arbitrarily. A set of infeasible rules had to be discarded, in order to generate interesting models, that produce a relevant amount of trades. Data from Kraken exchange were utilized for training, validation and results assessment. Results have shown that, for the cryptocurrencies with the highest validation performances, there are gains in comparison to the simple currency appreciation. Using the interpretable aspect of the models, it should be possible to obtain even higher profits.
Bing Mo, Kuiren Su, Songjie Wei, Cai Liu · 5 authors
Blockchain technology is a generic term for data organization structures, cryptography algorithms, distributed consensus mechanisms, and peer-to-peer communications that are used to implement distributed ledgers. Its core value lies in the establishment of mutual trust between non-coordinated participants. However, the current blockchain applications are inclined towards software and network, missing strong connection with the real world. The Internet of Things technology connects various smart devices and sensors to Internet to facilitate recognition and management of information. This paper presents a blockchain-based Internet of Things solution, where RFID chips with built-in asymmetric encryption algorithm and scanners uploading information directly to blockchain. Compared to traditional Internet of Things designs, the proposed solution combines the advantages of both decentralized blockchain, and the Waltonchain implementation demonstrates such advantages with both data security and application flexibility.
Bit coin is a crypto-currency that is based on a block-chain technology. All transactions in bit coin recorded in the block-chain and the transactions are validated through mining. When mining, honest miners are rewarded in proportion to their computing power. However, it has been proven that selfish mining can get more mining rewards beyond computing power. Selfish mining intentionally makes block fork of the block-chain and wastes the computing power of honest miners. In this paper, we analyze selfish mining and existing countermeasures, and propose a new method to prevent selfish mining by adding the transaction creation time to the transaction data structure. The proposed method is the highest threshold compared to existing methods, which is 33% threshold required for successful selfish mining. The threshold is also the most optimized result with the probability of an honest miner mining in selfish mining pools to zero.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
With Bitcoin, the legitimacy of a block of transaction data is verified by randomly selected nodes (hereinafter, verifiers) and notified to all nodes. To ensure the random selection of the verifier of each block, Proof of Works (PoW) is used. However, there is a serious problem with PoW, in that the amount of computation becomes huge. Although Proof of Stake (PoS) has been proposed to reduce the amount of computation, there remains the problem that if there is collusion among nodes, it is possible to control the probability of being the verifier. In this paper, a novel technique, Proof-of-Lucky-ID (PoL), is proposed. PoL is a kind of lottery that guarantees the randomness of the selection of the verifier, even if the node is collaborating unfairly, by using multiple digital signatures created by other nodes as input. Since this technique can determine the verifier with about two hash calculations per node, it significantly reduces the amount of processing compared with PoW, which requires more than 10^19 hash calculations as of 2017. In addition, since the input value cannot be controlled even if there is node collusion, it is impossible to control the probability of a win. Furthermore, compared to PoW and PoS, the certainty of consensus can be estimated with high accuracy in a short time. Numerical calculations show that both the randomness of verifier selection by the proposed method and the accuracy of the certainty of consensus range estimation are sufficiently high.
Manasa Sastry J. K, Astha Pandey, M. S. Dahiya, L Magwa M
Background: From the time immemorial there have been several types of crimes. With the advancement in science and technology, digital crimes have become very prominent. One among which is Bit-Coin crypto-currency frauds which are gaining momentum in the types of frauds encountered by law enforcement agencies. Bit-Coin is a growing form of digital crypto-currency that is created and held electronically that has no centralized control systems, that governs the transactions. It is the most secretive form of money transfer between two anonymous people all over the world. It is on a superficial layer used to purchase or sell goods electronically, similar to the conventional dollars that are traded digitally where individual ledgers are maintained by all the bit coin users to have access to the building block-chain. However, a masked layer consists of a dark-net where enormous amounts of money are concealed in cold storage where illegal websites and illicit commerce like ATM/ Debit/ Credit Card scams subjecting to illegal transactions rule over the deep net by utilizing the innocent public money. Case Presentation: The present study involves a case study where it was noted that innumerable ATM Debit/Credit Cards were skimmed and the illicit money was exchanged with this crypto-currency using an illicit website for bit coin mining and storing huge amounts of anonymous public money that was dictated by a few Nigerian Fraudsters running this racket all over the nation.
M Vaidehi, Alivia Pandit, Bhaskar Jindal, Minu Kumari · 5 authors
After the boom and bust in cryptocurrencies’ prices in recent years, Bitcoin has been totally regarded as an investment asset. As it is highly volatile in nature, there has been a need for good predictions for carrying base investment decisions. Although current study has used machine learning for more accurate Bitcoin price prediction, some of them did focused on the feasibility of applying different modeling techniques to the samples that has different data structures and dimension features. To predict Bitcoin price on different frequencies after using machine learning techniques, firstly we have to classify the Bitcoin price with daily price and high-frequency price. Here, we attempt to predict Bitcoin price as accurately as possible by taking into consideration various protocols that affect the Bitcoin value. Using the provided data we would predict the sign of daily price change with highest possible accuracy. We have used Random Forest Classifier and compared with benchmark results as daily price prediction, we achieve a better performance, with the highest accuracies of the statistical methods and machine learning algorithms of 99%. my investigation in Bitcoin price prediction can be considered as a pilot study for the importance of the sample dimension in the machine learning techniques. Keywords Bitcoin, Crypto Currency, Machine Learning, Blockchain, Long Short Term Memory(LSTM), Recurrent Neural Network(RNN), Prediction
N.I. Indera, Ahmad Ihsan Mohd Yassin, Azlee Zabidi, Zairi Ismael Rizman
This paper presents a Multi-Layer Exogeneous Inputs (NARX) Bitcoin price forecasting model using the opening, closing, minimum and maximum past prices together with Moving Average (MA) technical indicators.
Bitcoin is the first decentralized cryptocurrency to be traded. There has been drastic increase in the price of bitcoin since 2013. Granger Causality analysis has been carried out to examine whether the price of commodities and the exchange rates helps in predicting the future price of bitcoin. For this study, the price of bitcoin, commodity prices and exchange rates have been considered from Jan 2103-Sep 2017. After the analysis it can be concluded that the price of commodities and the exchange rates does not help in predicting the future price of bitcoin. The past data of the price of bitcoin helps in predicting the future price of copper and British pound exchange rate with that of U.S dollars. Using Regression analysis, it can be determined that when the price increases by 0.0084 dollars there is one unit increase in the volume of transaction. Using variance analysis it can be observed that the price of bitcoin is more volatile compared to the price of commodities and the exchange rates.
Phan The Duy, Do Thi Thu Hien, Do Hoang Hien, Van-Hau Pham
In the "Industry 4.0" era, blockchain as well as related distributed ledger technologies has been an unmissable trend for both academy and industry recently. Blockchain technology has become famous as the innovative technology that underlies cryptocurrencies such as Bitcoin and Ethereum platform. It also has been spreading with multiple industries exploring their capabilities and new blockchain use cases springing up on a daily basis. Its emergence has brought a great deal of impact on how the information will be stored and processed securely. Furthermore, almost of advocates say that blockchain will disrupt and change everything from education to financial payments, insurance, intellectual property, healthcare,... in the years to come. However, a comprehensive survey on potential and issues of blockchain adoption in academy and industry has not been yet accomplished. This paper tries to conduct a comprehensive survey on the blockchain technology adoption by discussing its influences as well as the opportunities and challenges when utilizing it in the real-world scenarios.
Blockchain is being termed as the fifth disruptive innovation in computing. In simplest words, it is a distributed ledger of records that is immutable and verifiable. Since its advent in 2008, blockchain as a concept has been used in various ways. The largest impact or application is seen as a multitude of cryptocurrencies that have sprung up. However, with time, it has become clear that blockchain as a technology is likely to have an impact much wider than just the cryptocurrency domain and much deeper than simple distributed ledger storage. This detailed survey intends to bring together all the key developments so far in terms of putting blockchain to practice. While the most common adoption of blockchain is in finance and banking domain, there are experiments being conducted by many big players in various other domains. This paper will explore the various domains where blockchain has had an impact and where future implementations may be expected.
Bitcoin is a computerized digital money and exchange network, represents an essential change in financial sectors, an interesting number of customers and excellent evaluation of channel inspection. In this research, dataset related to ten cryptocurrencies are used and created a new dataset by taking the closing price of each cryptocurrency for the research goal to ascertain how the direction and accuracy of price of the Bitcoin can be predicted by using data mining methods. Features engineering evaluated that all the ten cryptocurrencies are strongly correlated with each other. The task is achieved by implementation of supervised learning method in which random forest, support vector classifier, gradient boosting classifier, and neural network classifier are used under classification category and linear regression, recurrent neural network, gradient boosting regressor are used under regression category. In the classification category, support vector classifier achieved the highest accuracy of 62.31% and precision value 0.77. In regression category, gradient boosting regressor got the highest R-squared value 0.99.
IoT (Internet of Things) has a large portion of our life. This is manifested by the large number of connected devices. With the exponential growth of IoT devices, IoT security is becoming important. In particular, Smart Door Lock system is extremely important because it is closely related to the safety of the user. However, the data sent and received of existing Smart Door Lock system is vulnerable to forgery and hacking. To improve these security issues, we propose a Smart Door Lock system based on blockchain. Also, this provides data integrity and non-repudiation. Lastly, we propose an algorithm that the Smart Door Lock system judge some situations around itself and operates based on data sent from sensors.
A blockchain maintains a permanent record of all the transactions that happen in a bitcoin network. It is an append-only ledger which is distributed to every node in the network. We have made use of blockchain technology for recording the transactions of peers without any supervision of a central authority. A cryptographic protocol using the Merkle tree and SHA-256 hashing technique is described which makes it possible to confirm the transactions are integrity protected and to archive the transactional history using Merkle tree in an append only ledger. Paper also discusses miners, who contribute to proof of work and validation of transactions in the peer to peer network.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Currently in this digital world, passport is still a physical entity. It is carried at all places along with other travel related documents such as VISA and Immigration stamps that are also part of the passport(s). Each country maintains its own database of travel related information of the people entering and leaving the country. This paper is written with a vision of digitizing Passport, VISA and Immigration documents. Digitizing Passport and VISA helps in streamlining and simplifying Passport and VISA issuing, renewing, revoking, verification and validation process. For this process, we are proposing a solution based on distributed ledger for storing and retrieving information. Once implemented, this framework will help do-away with fake passports and VISA, unauthorized and repetitive data verification process. Blockchain-based distributed ledger implementation will solve several issues pertaining to paper-based authentication and make services more streamlined, improving efficiency and potentially lower costs at all levels.
This paper identifies trust factor and rewarding nature of bitcoin system, and analyzes bitcoin features which may facilitate bitcoin to emerge as a universal currency. Paper presents the gap between proposed theoretical-architecture and current practical-implementation of bitcoin system in terms of achieving decentralization, anonymity of users, and consensus. Paper presents three different ways in which a user can manage bitcoins. We attempt to identify the security risk and feasible attacks on these configurations of bitcoin management. We have shown that not all bitcoin wallets are safe against all possible types of attacks. Bitcoin core is only safest mode of operating bitcoin till date as it is secure against all feasible attacks, and is vulnerable only against block-chain rewriting.
The popularity of Blockchain technology and the huge extent of its application, results with much ongoing research in different practical and scientific areas. Although still new and in experimenting phase, the Blockchain is being seen as a revolutionary solution, addressing modern technology concerns like decentralization, trust, identity, data ownership and data-driven decisions. At the same time, the world is facing an expansion in quantity and diversity of digital data that are generated by both users and machines. While actively searching for the best way to store, organize and process Big Data, the Blockchain technology comes in providing significant input. Its proposed solutions about decentralized management of private data, digital property resolution, IoT communication and public institutions' reforms are having significant impact on how Big Data may evolve. This paper presents the novel solutions associated with some of the Big Data areas that can be empowered by the Blockchain technology.
A comparative study across the most widely known blockchain technologies is conducted with a bottom-up approach. Blockchains are disentangled into building blocks. Each building block is then hierarchically classified in main and subcomponents. Then, alternative layouts for the subcomponents are identified and compared between them. Finally, a taxonomy tree summarises the study and provides a navigation tool across different blockchain architectural configurations.