Blockchain Papers

Junying Gao, Bo Li, Zhihuai Li

No abstract is available for this record.

Do Hyung Kwon, Ju Bong Kim, Ju Sung Heo, Chan Myung Kim · 5 authors

No abstract is available for this record.

Toshiyuki Takatsuji, Hiroshi Watanabe, Yuichiro Yamashita

No abstract is available for this record.

Gautam Srivastava, Shalini Dhar, Ashutosh Dhar Dwivedi, Jorge Crichigno

Blockchain is one of the hottest topics nowadays at many societal, industrial and academic conferences. The Blockchain is the core mechanism of digital currencies like Bitcoin. It has far reaching possibilities for applications in healthcare, public document management, and voting systems to name just a few. However, due to the many intrinsic technical aspects of blockchain technology, it is not easy for the general audience to understand the concepts well. This paper deals with the most natural methodology to educate Blockchain technology to young students and the general audience in a manner intended to those who have a very limited technical background.

Darya Korepanova, Stanislav Kruglik, Yash Madhwal, Timur Myaldzin · 8 authors

Counterfeit stamps cause considerable financial damage to the states and companies. The blockchain-based supply chain management system for their market is proposed in the article. It can make stamps circulation transparent and guarantee invariability of stamps volume produced and used. The technical description and performance tests of the proposed system are provided.

A. N. Shwetha, C P Prabodh

The Central and State governments of India uses the Public Distribution System(PDS) to distribute food grains to the citizen of India at subsidized rates to ensure food security. The system is prone to losses of food grains because of prevalent corruption among the officials serving the system and also due to physical losses during storage and transport. Blockchains have become a commonly used audit trail verification utility because of its inherent nature, that it is a distributed ledger for recording transactions. This makes it a key candidate to replace the current centralized system that exists for the tracking of commodities being distributed by the PDS. Like any centralized system the current centralized system can be sabotaged by the people in administration, as it relies heavily on trust on the central authority. In this paper we propose an intelligent scheme for tracking the commodities in PDS using IoT based sensors that monitor the arrival and dispatch of commodities and generate corresponding transactions. These transactions should be stored permanently to keep track of the commodities for which a decentralized Blockchain based system is used that continuously logs every valid transaction. As the amount of transactions increase so does the data to be stored on the blockchain, hence we propose a hierarchical blockchain approach where in transaction summaries of a local blockchain are recorded as transactions in a higher level blockchain after which the local blockchains can start afresh recording newer transactions only. This approach results in reduction in the amount of data to be stored on the blockchain. At the same time one can find aggregate information at a higher level which can be used to determine the supply demand ratio. Anyone can verify the current availability of the food grains throughout the distribution network of the PDS and track the commodities right from the network of warehouses to the end point sales-the fair price shops where the food grains are delivered to the consumers. These transactions can be audited at any time as all transactions are recorded in the Blockchain which can prevent any misuse or corruption.

Chaehyeon Lee, Heegon Kim, Sajan Maharjan, Kyungchan Ko · 5 authors

Blockchain technology provides the advantage of maintaining a network without third party intervention, providing transparency because all participants have distributed ledgers with the same data. Using these characteristics, blockchain technology is being used in various fields, but the anonymity of blockchain can be exploited for illegal trades in the Darknet market. Therefore, a monitoring system for transactions occurring on the blockchain is needed. This paper proposes a monitoring system and an explorer to show the results collected from the system.

Ayushi Singh, Gulafsha Shujaat, Isha Singh, Abhishek Tripathi · 5 authors

Bitcoin is a popular cryptocurrency that records all transactions in an allotted append-handiest public ledger referred to as a blockchain. The security of Bitcoin heavily relies on the motivation-suitable proof-of-work (PoW) founded dispensed consensus protocol, which is run with the aid of the community nodes known as miners. Because of its inception, blockchain technological know-how has proven promising application possibilities. The spectrum of blockchain functions stages from financial, healthcare, automobile, hazard administration, internet of matters (IoT) to public and social offerings. Several reports focal point on utilizing the blockchain information structure in various applications. These vulnerabilities result in the execution of different security threats to the ordinary functionality of Bitcoin. We then examine the feasibility and robustness of the brand new safety solutions. Moreover, we discuss the current anonymity concerns in Bitcoin and the privatenessrelated threats to Bitcoin customers together with the evaluation of the comprehensive privacy-keeping solutions.

Dhyanendra Jain, Ashu Jain, Amit Pandey, Jogender Kumar

Abstract Bitcoin is one of the crypto currencies and is most unpredictable currencies. In the world of crypto currencies, the value of a coin can unpredictably upgrade or degrade. In this study, the model has been trained to predict the value of Bitcoin in USD at any given time stamp. For this prediction, three algorithms of machine learning - Linear Regression (LR), Support Vector Regression (SVR) and Neural Network Regression (NNR) have been used. The model is trained using the collected dataset. After the collection of data set, we first applied SVR algorithm, then we used LR and then NNR to calculate the error compared to the actual value. Root mean squared error (RMSE) is used as the predictive measure. Out of the three algorithms, LR was found out to be more accurate for predicting the value of bitcoin.

Amin Azari

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 $w$.

Betty Jepkemei, Andrew Kipkebut

Blockchain as technology promises to be a hugely disruptive and empowering technology both in public and private finance applications. As a method to order transactions in a distributed ledger, blockchains offer a record of consensus with a cryptographic audit trail that can be maintained and validated by multiple nodes. It lets contracting parties dynamically track assets and agreements using a common protocol, thus streamlining and even completely collapsing many in-house and third-party verification processes. Block chain originally conceived as the basis of cryptocurrencies, aspects of blockchain technology have far-reaching potential in finance. Although it promises a secure distributed framework to facilitate sharing, exchanging, and the integration of information across all users and third parties, it is important for stakeholders to analyze it in depth for its suitability in business applications. There is a wide spectrum of blockchain applications ranging from cryptocurrency, financial services, risk management among others ,however there is no comprehensive survey on the blockchain as disruptive technology in finance and its application, To fill this gap, we conduct a comprehensive survey on the blockchain technology, its challenges , advances in managing these challenges and the future of block chain technology in the financial industry.

Rana Muhammad Amir Latif, Samar Iqbal, Osama Rizwan, Syed Umair Aslam Shah · 6 authors

Food provenance is one of the most challenging problems that FSC. companies face today. A global supply chain network with multiple operating procedures and asymmetrical food regulations between countries makes end-to-end food tracking incidental to the food industry. Blockchain empowers new kinds of distributed applications design. Initially, Blockchain technology has been embraced in electronic money, yet this tech is significantly more promising for different areas loo. In this paper, are getting to present Blockchain technology easily. Additionally, we are talking that Blockchain technological innovation is also utilized in the industrial process from the retail industry to its advantage towards the client and additionally for that merchant to fantastic scope. During its heart, Blockchain is mainly thrilling because of the ability that it must empower increased confidence, transparency, and cooperation round constituencies which will otherwise battle to reach up to now belter. As distribution chain sophistication rises, there is an apparent chance to induce efficiency as a result of higher cooperation and transparency in between various constituencies like manufacturing companies, vendors and delivery carriers, insurance, importers, wholesalers, and merchants. Being aware of in Real-time the specific supply, spot, and condition of most inventory while in the machine might be quite a game-changer for most organizations, notably those working in perishable or luxury-goods. Unlike present systems, that rely heavily upon every element to keep its clear and dispersed database significance restricted and frequently postponed penetration to the standing of products anyplace from the machine Blockchain eases real-time and dependable information sharing one of the components and may provide consensus regarding the actual condition of their machine into parties.

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.

Sakshi Tandon, Shreya Tripathi, Pragya Saraswat, Chetna Dabas

This research paper reports the proposed model for price prediction of the popular Bitcoin crypto currency while applying different neural network approaches namely Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) along with 10-fold cross validation. In this work, the analysis of various trends of Bitcoin market is carried out and learning of important features used for price prediction is done. Daily price change is estimated by the neural network models. New activation functions are utilized in this research paper for improving efficiency. Further, this research paper compares the proposed model with other existing models namely; RNN with LSTM, Linear Regression and Random Forest applied in the same domain. The dataset utilized in this work is taken from the website named coinmarket and live streaming data is considered for the experimental work. Keras, Tensorflow and Scikit Learn have been used for performing the experimental work of the proposed model. The performance analysis of the proposed model with the existing ones has been carried out in terms of the Mean Absolute Error (MAE). It is observed from the results retrieved as a part of this work that the MAE for the proposed model came out to be 0.0043s which was significantly less than its existing counterparts.

Martin Westerkamp, Friedhelm Victor, Axel Küpper

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.

S. Shreyas Ramachandran, A. K. Veeraraghavan, Uvais Karni, K. Sivaraman

No abstract is available for this record.

S. V. Aswathy, K. V. Lakshmy

No abstract is available for this record.

Wjatscheslav Baumung, Vladislav V. Fomin

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.

Pavan Manjunath, Michael Herrmann, Hüseyin Şen

No abstract is available for this record.

Piyush Keshari, Santanu Koley, Kunal Kumar Mandal, Pradeep Kumar Singh

No abstract is available for this record.

Vladislav Killiakov

In this project, I will investigate the performance of several major neural network architectures for the task of Bitcoin price prediction. Bitcoin is a cryptocurrency that is recently becoming increasingly more popular, and more widely adopted as a financial instrument. As a result, more efforts have been made in the past several years to model and predict its price. However, to this moment a large portion of work on Bitcoin price modeling was done using statistical or classical machine learning techniques. At the same time, other artificial intelligence based prediction techniques, and specifically neural networks, have not been explored to the same extent. Further, multi-layer perceptron (MLP), recurrent neural networks (RNNs), and convolutional neural networks (CNNs) that are currently successfully applied in many fields of engineering and science are often overlooked when it comes to financial time series modeling. Thus, the main goal of the project is to partially fill in this research gap by evaluating the performance of the three widely used neural network architectures – MLP, RNN and CNN, in the task of Bitcoin price prediction.

Abhishek Sharma, Ying-Hsun Hung, Punit Kumar Agarwal, Muskan Kalra

No abstract is available for this record.

Arzu Tay Bayramoğlu, Çağatay Başarır

No abstract is available for this record.

Dharmin Dave, Shalin Parikh, Reema Patel, Nishant Doshi

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.