With the everyday use of big data technology, using big data resources effectively has become a key area of research. Media consumption creates enormous amounts of data in people’s digital lives. This data is not only very valuable to the company, but it also presents a number of concerns, including privacy breaches and data exploitation. Along with the continuous improvement of blockchain technology, the rational use of big data resources has become possible. Blockchain technology has expanded from the initial Bitcoin to the financial field and has become more widely used in the legal and media industries. This study catches the actual cases of blockchain technology in the media industry through Qingbo Big Data, analyzes the current global blockchain and media industry’s overall development status and the existing problems, and puts forward corresponding countermeasures to accelerate the integration and development of blockchain and media industry in the context of big data. The results show that the technical features of blockchain can solve the painful problems of copyright risk, algorithmic black box, and weak trust mechanism in the media industry, and the combination of the two can form a new burst of media productivity. The article discusses the broad application prospects of blockchain in the media industry, which is essential for big data and blockchain research. This paper composes the pioneering literature on the blockchain, catches the information on blockchain by keywords, analyzes the application prospect of blockchain in the media industry, and promotes the research and application of blockchain technology.
Open access
Blockchain Technology Applications and Security
Big Data Technologies and Applications
Advanced Steganography and Watermarking Techniques
The world had started digitization, even before the global pandemic had struck, which led to various processes, like verification and application of documents, going online. This also leads to an increase in the amount of data and traffic on the internet, causing an increase in cyber fraud, such as document (digital) forgery. All this has led to the need for a secure digital document management platform. With the help of Blockchain Technology, a safe alternative for the same can be developed. In this paper, we have studied the use cases where digital forms of documents are involved, and based on Blockchain Technology, we have created a secure web application for all the processing of the documents. The web application generates new certificates as requested for pre-defined templates and stores their identifier securely in the distributed Blockchain network (Polygon) and the document on an IPFS (InterPlanetary File System). Further, it provides the facility to verify the authenticity of the document. It also allows users to share access to their documents securely for a specific time.
The aim of the paper is to analyze the sustainability of cryptocurrency in blockchain technology in African countries for securing financial business transactions. Following the subprime crisis that shook the world economy, a new perception of money has emerged. It is a fully digital currency whose transactions are made through a distributed network. This algorithm-encrypted currency, reputed to be tamper-proof, transparent and inclusive, relies on a distributed network called the Blockchain. By comparison with traditional registers in which operations are paginated and successively recorded, transactions in blockchain technology are aggregated within the chain of blocks. It is decentralized since it is replicated on several geographic sites around the world. It enables peer-to-peer transactions, automated in real-time, reliable, secure, without intermediaries and non-repudiable. To ensure maximum security during financial transactions, blockchain miners use cryptography. This distributed system is, therefore, a major technological innovation capable of securing the financial infrastructure and mitigating failures by reducing operational risks. According to our analysis based on the Merkle tree model and blockchain energy consumption, the sustainability of cryptocurrency is a major issue for developing countries. Especially in Africa, its practicality poses a number of constraints.
Since its inception, the cryptocurrency's exceptional growth has put financial institutions at high risk of exposure to money laundering. In financial institutions, specifically banks, Anti-Money Laundering and Bank Secrecy Act (AML/BSA) risk specialists, bank managers, and compliance officers get challenged in identifying cryptocurrency-related transactions and customers who conceal illegal funds. Interviews conducted with the AML/BSA risk specialists, bank managers, and compliance officers were analyzed to understand how banks combat the cryptocurrency-related money laundering in the USA banking system. Interview with the Director of Financial Investigations & Education at CipherTrace as an expert in blockchain forensics was evaluated to recognize bank regulation and compliance. The case studies were assessed to understand the banks' program and regulation deficiencies and their inability to identify suspicious accounts. Interviews and case studies findings suggest that cryptocurrency-related money laundering is a risk for banks who lack proper tools, programs, and adequate well-trained and well-educated staff in mitigating cryptocurrency-related risks. Support provided by FinCEN regulation and guidance and external vendors is seen as critically valuable in assisting banks to combat cryptocurrency-related money laundering financial crimes.
Artificial intelligence-driven cryptocurrencies are cryptocurrencies created by Artificial intelligence using the traditional human cryptocurrency development framework without human intervention. An AI explores the data from each different stream and arriving at the framework which can host these cryptocurrencies following the standards of legality. Cryptography is the encryption of specific data to conceal it and keep it a secret from unwanted third parties. Cryptocurrencies are encrypted currencies with unique keys as developed by developers. Artificial intelligence is an advanced machine programmed to simulate and emulate human intelligence by carrying tasks and reaching conclusions with little or no human intervention. This work considered the use of AI through machine learning and deep learning in the development of cryptocurrencies. The AI machine will set all the parameters and structure of the cryptocurrency. This will include how data is added, removed, and verified on the stream. Blockchain is an open ledger of a cryptocurrency's transactions. It stores files in the system, arranged in blocks, and connected on a list called chains. The article considers how AI-driven cryptocurrency will run using the blockchain network and its impact on it. Artificial intelligence and cryptocurrency are technological very essential technological development currently. The effect of the combination of both technologies would be enormous in the future as both technologies will develop each other remarkably.
Die Allgegenwärtigkeit des Internets macht es zu einer wertvollen Datenquelle. Produkte wie Twitter und Google Trends implementieren APIs die es erlauben diese Daten zu nützen. Da diese zwei Produkte große Mengen von Nutzerdaten speichern, kann man Sie nützen um Vorhersagen über das Benutzerverhalten in bestimmten Bereichen zu machen. In dieser Arbeit, beschreiben und implementieren wir statistische Method um Vorhersagen über den Bitcoin Wechselkurs mittels Stimmungsanalyse, der Frequenz von Tweets über Bitcoin und dem Interessenniveau zum Suchbegriff Bitcoin. Weiters zeigen wir wie das stündliche Handelsvolumen von Bitcoin mittels der stündlichen Rate von Tweets über Bitcoin und Google Trends Daten vorhergesagt werden kann. In dieser Arbeit analysieren wir Daten aus dem Zeitraum Juli 2018 bis August 2018, d.h. zwei Monate. Erstens benützen wir die stündlichen Informationen über Tweet Stimmung, Tweet Frequenz und Google Suchdaten über Bitcoin um eine kausale Verbindung zwischen diesen Daten und dem aktuellen Preis von Bitcoin. Zweitens entwickeln wir ein vektorautoregressives Modell (VAR) dass erfolgreich den Bitcoin Wechselkurs und das Bitcoin Handelsvolumen vorhersagt. Weiters, verwenden wir zwei unterschiedliche Algorithmen, SentiStrength and Stanford Core NLP, um Stimmungsinformation zu erhalten. Wir zeigen dass mit dem SentiStrength Algorithmus welcher für kurze Nachrichten wie Tweets geeignet ist unser Modell bessere Resultate erzielt. Spezifisch, zeigen wir dass unser Modell wenn kombiniert mit SentiStrength eine Genauigkeit von 63% für Vorhersagen bezüglich dem Anstieg und Abstieg des Bitcoin Wechselkurses aufweist. Auf der anderen Seite, wenn man unser Modell mit Stanford Core NLP kombiniert erhalten wir eine Genauigkeit von 59%. Drittens, benutzen wir die Tweet-Frequenz und Suchinformationen um das Bitcoin Handelsvolumen mit einem mittleren quadratischen Fehler von 172.76 vorherzusagen. Zusammenfassend, zeigen wir in dieser Arbeit dass Informationen von Twitter und Google Trends sehr hilfreich sind wenn es um die Vorhersage zwei wichtiger Bitcoin Eigenschaften, Wechselkurs und Handelsvolumen, geht.
In econophysics, statistical-physics techniques are used to model economical systems. In this thesis, we investigate the entropy and the Computational Information Density (CID) of the Bitcoin blockchain. The CID is defined as the compression ratio of some particular algorithm when applied to the raw data of the state of the system. It is related to entropy as both CID and entropy are measures of information.\nWe find a strong correspondence between the CID and entropy for the Bitcoin blockchain, where features are similar, but without one being a clear function of the other. This can be explained by intercorrelations between one agent and the next, which the entropy does not count. We also calculate some correlations to see if the CID and the entropy have some predictive power for the price, and we find a small correlation, but very small in comparison to the predictive power of the price itself.\nThese results the power of the CID-entropy correspondence and how the Bitcoin blockchain may be used as a useful large-scale toy model for econophysics. We anticipate that these results can be used for a further look into the CID-entropy relation, as the similarities are visible but there is no exact correspondence. Besides this, these results can form a basis for a further look into the predictive power of the CID or the entropy for the price.
E-voting is the process of conducting the voting process through online. The voters can cast their votes from different locations and these votes are collected and recorded electronically. Therefore, there is a need for a system to provide control and security to the whole procedure. Blockchain, a distributed ledger technology can be integrated to provide a decentralized system. Blockchain uses distributed ledger technology (DLT) to avoid forged voting option & non-repudiation and one time login of the user is also ensured. By integrating the above techniques, a secure user authentication for e-voting supported blockchain in p2p network is projected. This system would increase the safety by avoiding the forgery of votes. Similarly, the blockchain are often integrated to a spread of voting situations and a few alternative applications.
Open access
2 source records
Blockchain Technology Applications and Security
Internet Traffic Analysis and Secure E-voting
Advanced Steganography and Watermarking Techniques
The characteristics of blockchain as decentralization, transparency, business activity undeniable proof mechanism etc. have achieved extensive attention from the academic circles and industrial circles. In view of the current deficiency of poor data sharing in G2B system, data authenticity, data security, and transaction subject identity's confidentiality cannot be effectively guaranteed, and the lack of authentication for government management departments (organization institutions) providing service or implementing management to enterprise businesses, this paper proposed to construct G2B system based on blockchain. Based on maintaining the architecture of traditional G2B system and the serviced or managed characteristics of enterprise businesses, was constructed respective G2B system based on blockchain for each section of enterprise business process. Each G2B system was based on blockchain correlated by the virtual links of enterprises and serviced or managed data for enterprises' business, and constituted blockchain interconnection network. The protocol was designed and the characteristics of G2B system analyzed based on blockchain. Application mode for G2B system was designed based on blockchain. A case based on blockchain was designed, including business operation principle, consensus mechanism, and supervision to government (organization).
A protocol for enabling smart, social currency for publishers and content businesses across the internet 1 Delegated Proof of Stake Position Paper.Grigg, 2017.https://steemit
David Froelicher, Juan Ramón Troncoso-Pastoriza, João M. C. Sousa, Jean‐Pierre Hubaux
Data sharing has become of primary importance in many domains such as\nbig-data analytics, economics and medical research, but remains difficult to\nachieve when the data are sensitive. In fact, sharing personal information\nrequires individuals' unconditional consent or is often simply forbidden for\nprivacy and security reasons. In this paper, we propose Drynx, a decentralized\nsystem for privacy-conscious statistical analysis on distributed datasets.\nDrynx relies on a set of computing nodes to enable the computation of\nstatistics such as standard deviation or extrema, and the training and\nevaluation of machine-learning models on sensitive and distributed data. To\nensure data confidentiality and the privacy of the data providers, Drynx\ncombines interactive protocols, homomorphic encryption, zero-knowledge proofs\nof correctness, and differential privacy. It enables an efficient and\ndecentralized verification of the input data and of all the system's\ncomputations thus provides auditability in a strong adversarial model in which\nno entity has to be individually trusted. Drynx is highly modular, dynamic and\nparallelizable. Our evaluation shows that it enables the training of a logistic\nregression model on a dataset (12 features and 600,000 records) distributed\namong 12 data providers in less than 2 seconds. The computations are\ndistributed among 6 computing nodes, and Drynx enables the verification of the\nquery execution's correctness in less than 22 seconds.\n
This article examines the bitcoin, at present the most popular cryptocurrency. The bitcoin grew on the major pillars of the neoliberal market economy, such as liberalization, deregulation and privatization. But in the end, it turned out to be a cure for the dysfunctions of the financial system, which was based on neoliberal assumptions. The difficulty in capturing the character and status of the bitcoin still makes it elusive for the existing rules of law. Some governments observe the evolution of the bitcoin market with interest; others try to work against it. All of this makes the bitcoin an intriguing subject for research.The aim of this article is to present the original assumptions of the bitcoin system; trace the reactions to the bitcoin’s emergence in virtual reality, and next on the very real financial market; and analyze the reinterpretation of the idea that underlies the creation of the cryptocurrency. This article attempts to assess the bitcoin’s potential of achieving a seemingly impregnable position on the global financial market.
Current research has led to a rejection of the hypothesis of a normal distribution of financial assets returns. Under these conditions, portfolio variance cannot serve as a good risk measure. In this paper analyzed the daily returns of the most common cryptocurrencies: Bitcoin, Bitcoin Cash, Litecoin, XRP, Ethereum, NEM. It is shown that the asset returns are not normally distributed, but with good precision follow the Cauchy distribution. The analytical expressions for risk measure were obtained using the Cauchy distribution function and the VaR technique. The efficient frontiers of cryptocurrencies portfolios were constructed using modified Markowitz model. The purpose of the article is to assess the risks of major cryptocurrencies and to diversify the risk of cryptocurrency investing by applying a portfolio model
Due to conclusion could not rely on only one test, in this study, we apply various approaches to verify the actuary of VaR model to find out whether VaR model, especially historical VaR and delta normal VaR model, can provide the accurate risk measurement results for cryptocurrencies risk, especially CRIX, BTC, ETH and XRP. We use Kupiec’s POF test, Independence Test - Christoffersen (1998) and Joint Test that widely use for backtesting VaR model. Performance test results for risk measurement by historical VaR provide a fairly accurate over delta normal VaR when we use Kupiec’s POF-test for the accuracy of VaR model. Christoffersen (1998) independence test, the exceptions (failures) of historical VaR and delta normal VaR model show independence exceptions in accordance with an only high confidence level of critical values (0.99). Otherwise, the low confidence level of critical values (0.90 and 0.95) appears dependence exceptions. For the Joint test, we combine POF-test and independence test because each model has different advantages and disadvantages. The results show that historical VaR model is suitable for measuring cryptocurrency risk over delta normal VaR only high confidence level of critical values.
The development of Energy-Internet is currently suffering from a series of issues, such as the conflicts among high capital requirement, low-cost, high efficiency, the spreading gap between capital demand and supply, as well as the lagged trading & valuation mechanism, any of which would hinder Energy-Internet's evolution. However, with the development of Blockchain and big-data technology, it is possible to work out solutions for these issues. Based on current situation of Energy-Internet and its requirements for future progress, this paper demonstrates the validity of employing blockchain technology to solve the problems encountered by Energy-Internet during its development. It proposes applying the blockchain and big-data technologies to pricing and trading energy products through Energy-Internet and to accomplish cyber-based energy or power's transformation from physic products to financial assets.
The cryptocurrency Artificial intelligence price emulator is a software programmed to collect cryptocurrency market data, analyze the data and predict the market price using the collected data. Computer emulators are programmed to mimic and copy behaviors or other software/hardware. The reason for emulation is to get to a particular result as quickly as possible. Machine learning is the ability of computers to read and process data while learning from the data with human interference or influence. This work focused majorly on how cryptocurrency market prices can be emulated using Artificial Intelligence with machine learning abilities. It also looked into the advantages of using the software for crypto investors. Some of which is the reduced time of research, reduction of risk, among others.