Owen Chaffard, Pablo Mollá, Marc Cavazza, Helmut Prendinger
In the recent advancements in application of deep learning to time series forecasting, focus has shifted from training transformers end-to-end to efficiently leveraging the predictive capabilities of Large Language Models (LLMs). Models that encode the time series data to interact with a frozen LLM backbone have been shown to outperform transformers on all benchmark datasets. However, their efficiency on complex datasets, which do not show clear seasonality or trend, remains an open question. In this work, we seek to evaluate the performance of reprogrammed LLMs on the Bitcoin price chart, a financial time series known for its complexity and high volatility. We propose effective methods to improve the performance of Time-LLM, a State-of-the-art (SOTA) method, on such a time series. First, we propose structural improvements to Time-LLM. Second, we suggest an efficient way to handle the non-stationarity of the dataset. Finally, we propose an efficient method for passing additional financial information to the LLM. Our results demonstrate a 50% improvement on the average percentage loss and a 5% increase on accuracy of our adapted Time-LLM architecture on Bitcoin data when compared to SOTA models, including the original Time-LLM model. This highlights the impact on forecast accuracy of domain-specific decision making in data processing and feature selection.
HKUST Electronic Theses Novel reputation ranking system in Web3 and perpetual futures market models in DeFi by Do Van Thuat thesis 2024 1 online resource (xix, 168 pages) : illustrations (some color) This dissertation examines the evolution of the blockchain…Read more ›
Beginning in late 2021, the search volume of the keyword “Web3” on the Internet has grown rapidly. People started talking about Web3, and it seemed that the Web3 dream could become a reality tomorrow.Web3 is not a product that appeared out of thin air but a continuation of the spirit of cyberpunk and cypherpunk in the 1980s and 1990s. The current Web3 revolution resembles a renaissance with the economic stimulus flowing into cyberspace.
When migrating smart contracts from one blockchain platform to another, there are potential security risks. This is because different blockchain platforms have different environments and characteristics for executing smart contracts. The focus of this paper is to study the security risks associated with the migration of smart contracts from Ethereum to Arbitrum. We collected relevant data and analyzed smart contract migration cases to explore the differences between Ethereum and Arbitrum in areas such as Arbitrum cross-chain messaging, block properties, contract address alias, and gas fees. From the 36 types of smart contract migration cases we identified, we selected four typical types of cases and summarized their security risks. The research shows that smart contracts deployed on Ethereum may face certain potential security risks during migration to Arbitrum, mainly due to issues inherent in public blockchain characteristics, such as outdated off-chain data obtained by the inactive sequencer, logic errors based on time, failed permission checks, and denial of service (DOS) attacks. To mitigate these security risks, we proposed avoidance methods and provided considerations for users and developers to ensure a secure migration process. It is worth noting that this study is the first to conduct an in-depth analysis of the secure migration of smart contracts from Ethereum to Arbitrum.
We will discuss Web3 Storage, Sharding and Pruning, Security Risks to Blockchain Ecosystems, Secure transaction ledgers, Blockchains in the Quantum Era, and Storing private keys.
Development of management system standards for the cryptocurrency industry is an ongoing research project. This document is the first draft of a proposed standard for mining. It defines the obligations of firms engaged in cryptocurrency mining with respect to carbon footprint and safety. It follows the structure of ISO 27001. Firms could potentially be audited for adherence to such a standard (among potentially others) as a way of signaling their ethics.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves
In this study, we analyse systematic risk associated with the two leading cryptocurrencies - Bitcoin and Ethereum, from 2015 to 2023. Our findings show a significant escalation in the systematic risk levels, with beta estimates rising from 0.032 to 0.834 for Bitcoin, and from 0.087 to 1.003 for Ethereum. This hike in risk levels has dramatically reduced the diversification benefits of cryptocurrency that were documented in prior studies. In addition, we also identify increased autocorrelation of cryptocurrency systematic risk.
Crypto Pi is a hardware crypto wallet that has different benefits. The wallet aims to show the users how a hardware wallet works. It is an alternative to Trezor Model One, so it has all its benefits. It is not hard to use or set up. We chose to work on this project because we believe in the future potential of using cryptocurrencies as a form of payment.
Stablecoins are cryptocurrencies whose price is pegged to that of another asset (typically one with low price volatility). The market for stablecoins has grown tremendously - up to almost $200 billion USD in 2022. These coins are being used extensively in newly developing paradigms for digital money and commerce as well as for decentralized finance technology. This work provides a technical description of stablecoin technology to enable reader understanding of the variety of ways in which stablecoins are architected and implemented. This includes a descriptive definition, commonly found properties, and distinguishing characteristics, as well as an exploration of stablecoin taxonomies, descriptions of the most common types, and examples from a list of top stablecoins by market capitalization. This document also explores related security, safety, and trust issues with an analysis conducted from a computer science and information technology security perspective as opposed to the financial analysis and economics focus of much of the stablecoin literature.
Scott Fan, Elliot Gyllensvärd, Erich Farkas, Julian Schutzner
This paper seeks to analyse the environmental effects of China's recent regulatory steps taken against cryptocurrencies and compare them with two policy alternatives. To evaluate the environmental impact, two baseline scenarios are used-a ban scenario and a no-ban scenario-which are then employed to compare China's intervention with two alternative policies; an emissions trading system or carbon taxes. It is estimated that China's decision to ban cryptocurrencies will result in a 25.7% reduction in CO2 emissions from the global Bitcoin network between mid-2021 and 2030. In comparison, under a hypothetical emission trading system (ETS) and carbon tax intervention the most stringent scenario is estimated to reduce global Bitcoin CO2 emissions by 2.9% and 8.5% between mid-2021 and 2030, respectively. Furthermore, this paper shows that the ETS and carbon tax are both restricted in their absolute ability to reduce CO2 emissions due to the difficulties associated with the practical implementation of such policies. This provides evidence for why, in terms of an environmental perspective, a cryptocurrency ban is the most effective policy in reducing the Bitcoin blockchain network's CO2 emissions. However, the paper also shows that the transition to Proof-of-Stake (PoS) blockchains may create an environment in which there is less of an argument for active government intervention in the cryptocurrency markets due to the protocol's high energy efficiency.
Digital identity management system is the securi-ty infrastructure of computer and internet applications. However, currently, most of the digital identity management systems are faced with problems such as the difficulty of cross-domain authentication and interoperation, the lack of credibility of identity authentication, the weakness of the security of identity data. Although the advantages of block-chain technology have attached the attentions of experts and scholars in the field of digital identity management and many digital identity management systems based on block-chain have been built, the systems still can't completely solve the problems mentioned above. Therefore, in this pa-per, an effective digital identity management system model is proposed which combines technologies of self-sovereign identity and oracle with blockchain so as to pave a way in solving the problems mentioned above and constructing a secure and reliable digital identity management system.
In decentralized finance (DeFi), lenders can offer flash loans to borrowers, i.e., loans that are only valid within a blockchain transaction and must be repaid with fees by the end of that transaction. Unlike normal loans, flash loans allow borrowers to borrow large assets without upfront collaterals deposits. Malicious adversaries use flash loans to gather large assets to exploit vulnerable DeFi protocols. In this paper, we introduce a new framework for automated synthesis of adversarial transactions that exploit DeFi protocols using flash loans. To bypass the complexity of a DeFi protocol, we propose a new technique to approximate the DeFi protocol functional behaviors using numerical methods (polynomial linear regression and nearest-neighbor interpolation). We then construct an optimization query using the approximated functions of the DeFi protocol to find an adversarial attack constituted of a sequence of functions invocations with optimal parameters that gives the maximum profit. To improve the accuracy of the approximation, we propose a novel counterexample driven approximation refinement technique. We implement our framework in a tool named FlashSyn. We evaluate FlashSyn on 16 DeFi protocols that were victims to flash loan attacks and 2 DeFi protocols from Damn Vulnerable DeFi challenges. FlashSyn automatically synthesizes an adversarial attack for 16 of the 18 benchmarks. Among the 16 successful cases, FlashSyn identifies attack vectors yielding higher profits than those employed by historical hackers in 3 cases, and also discovers multiple distinct attack vectors in 10 cases, demonstrating its effectiveness in finding possible flash loan attacks.
The construction of smart grid has triggered comprehensive changes in power equipment. At the same time, massive data are waiting to be screened, analyzed and processed. However, there are many data sources and complex data structure in smart grid, and smart grid requires higher security, reliability, traceability, non-repudiation and real-time performance of data processing, which poses unprecedented challenges to the traditional data management. Blockchain technology has the advantages of decentralization, autonomy, leakage prevention and openness. It can match the demands of power data management in terms of operation mode, security protection, complement power data, and better meet the security and credibility requirements of energy Internet. Therefore, this paper designs the smart grid data management system based on blockchain, and constructs the system security evaluation model by using AHP and expert consultation method. Firstly, the characteristics of smart grid big data and blockchain technology are analyzed; Then the technical architecture of data management system is designed by using alliance chain, and the technical architecture is analyzed in detail; Finally, the index factors affecting system security are combed, and the system security evaluation model is constructed by AHP. Distributed storage, asymmetric encryption, consensus mechanism, and other technologies of blockchain technology can well solve the problems of power grid data storage and application, and better ensure the security of smart grid data.
Oluwatobi A. Adekunle, Adedeji Daniel Gbadebo, Joseph Akande
Bitcoin price exhibits patterns predictable on its historical pasts. We adopt ARIMA(auto), ARIMA(fix)models and the Holt-Winters filter (HWF) with trend plus additive seasonal HWF (𝛾[0,1]), and no seasonality HWF (𝛾[False]) to forecast the price of Bitcoin under three datasets–Actual (observed), Polynomial (fitted) and STL-Trend (fitted). We apply daily time-series from 1/09/2014–28/12/2020,and establish 18 models to forecast the price of Bitcoin. The results show that HWF (𝛾[0,1]) with lower limit fitted on STL-Trend provides the best prediction on the first training-sample, while ARIMA(fix) fitted on actual data outperform in the second training-set with the smallest Mean-Absolute-Error (MAE). The training-set forecast performance of the ARIMA(fix) for the actual function provides better performance with the least MAE. The HWF is appropriate for prediction of the daily Bitcoin price with the generalise STL-Trend function, but ARIMA(fix) is more accurate for the actual series.
This exploration paper is about the conception of a World Wide Web grounded for the conception grounded around machine-readability, also called Web3.0. Web3.0 will review how we interact with the digital world and the change won't just be for individualities. The effect of Web3.0 blockchain on businesses – both traditional and disruptive will be inversely massive. The transition from Web2.0 to Web3.0 still, won't be overnight. This means businesses will have time to look back at their process and see where they fit on the decentralization and translucency radar. But indeed though Web3.0 is in the future, the reality of the moment is that businesses need to start preparing. Let our Blockchain experts help you. Some technologists and intelligencers have varied it with Web2.0, wherein they say data and content are consolidated in a small group of companies occasionally appertained to as"Big Tech". The term"Web3" was chased in 2014 by Ethereumco- founder Gavin Wood, and the idea gained interest in 2021 from cryptocurrency suckers, large technology companies, and adventure capital enterprises. Some experts argue that web3 will give increased data security, scalability, and sequestration for druggies and combat the influence of large technology companies. Others have raised enterprises about a decentralized web, citing the eventuality of low temperance and the proliferation of dangerous content, the centralization of wealth to a small group of investors and individualities, or a loss of sequestration due to further extensive data collection. Crucial Words World Wide Web; Web3.0; Big Tech; cryptocurrency; decentralized web
K. Renuka Devi, S. Suganyadevi, S Karthik, N Ilayaraja
In the modern world, there is a purpose of storing, retrieving and analysing huge volumes of data. So, big data becomes one of the reliable aspects to analyse the large volumes of data to come to a better decision. Usually, big data is used to analyse large data set of information which cannot be handled by the traditional data processing software. This includes both structured and unstructured data and analyses the hidden patterns, correlations to retrieve the accurate results which would be helpful to improve the market results in organizations. So, securing the big data is one of the tedious processes in this real world in order to guard the data from attacks, theft or other malicious activities to maintain the confidentiality. The main characteristics of big data include Volume, Velocity, Variety, Veracity and Value. This paper mainly focused on several challenges in big data faced by healthcare domain and the technologies to maintain the security in it.
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.