The paper presents a model for decentralizing building information modelling, through implementing its infrastructure using the decentralized web. We discuss the shortcomings of BIM in terms of its infrastructure, with a focus on tracing identities of design authorship in this collective design tool. In parallel we examine the issues with BIM in the cloud and propose a decentralized infrastructure based on the Ethereum blockchain and the Interplanetary filesystem (IPFS). A series of computing nodes, that act as nodes on the Ethereum Blockchain, host disk storage with which they participate in a larger storage pool on the Interplanetary Filesystem. This storage is made available through an API is used by architects and designers creating and editing a building information model that resides on the IPFS decentralised storage. Through this infrastructure central servers are eliminated, and BIM libraries and models can be shared with others in an immutable and transparent manner. As such Architecture practices are able to exploit their intellectual property in novel ways, by making it public on the internet. The infrastructure also allows the decentralised creation of a resilient global pool of data that allows the participation of computation agents in the creation and simulation of BIM models.
Currently, there are no convincing proxies for the fundamentals of cryptocurrency assets. We propose a new market-to-fundamental ratio, the price-to-utility (PU) ratio, utilizing unique blockchain accounting methods. We then proxy various existing fundamental-to-market ratios by Bitcoin historical data and find they have little predictive power for short-term bitcoin returns. However, PU ratio effectively predicts long-term bitcoin returns than alternative methods. Furthermore, we verify the explainability of PU ratio using machine learning. Finally, we present an automated trading strategy advised by the PU ratio that outperforms the conventional buy-and-hold and market-timing strategies. Our research contributes to explainable AI in finance from three facets: First, our market-to-fundamental ratio is based on classic monetary theory and the unique UTXO model of Bitcoin accounting rather than ad hoc; Second, the empirical evidence testifies the buy-low and sell-high implications of the ratio; Finally, we distribute the trading algorithms as open-source software via Python Package Index for future research, which is exceptional in finance research.
This paper analyses the volume-return relationships across the top 30 most traded cryptocurrencies from April 2013 to June 2019 using high-frequency intraday data. We use a novel approach for the classification of cryptocurrencies with respect to multiple qualitative factors, such as geographical location of headquarters, founder and founder’s origin, platform on which the cryptocurrency is built, and consensus algorithm, among others. We identify significant bidirectional causalities between trading volume and returns at different high-frequency intervals; however, those linkages are weakening with decreasing data frequencies. The findings confirm the leading position of the Bitcoin trading volume in the cryptocurrency price formation. This evidence will help investors to design effective trading strategies in cryptocurrency markets providing useful insights from cryptocurrency categorisation.
This article deals with the emerging topic of stablecoins, which is an umbrella term used to refer to a stable cryptocurrency. The authors shall address a number of questions, namely: what are stablecoins; when are they used; what are the most common characteristics of stablecoins. The authors shall also present a taxonomy of stablecoins based on the mechanism employed to stabilize their value. A more thorough exploration of the market for stablecoins will follow, with particular attention given to the controversies surrounding the most popular of stablecoins – Tether.
Jan 1, 2020·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
With the rapid development of the Internet, cryptocurrencies have been gaining increasing amounts of attention dramatically. As a digital currency, it is not only used worldwide for online payments, but also traded as an investment tool on the market. Therefore, the ability to predict the price volatility will facilitate future investment and payment decisions. However, there are many uncertainties in the price movement of cryptocurrencies, and the prediction is extremely difficult. To this end, based on the transaction data of three different markets and the number and content of user comments and responses from online forums, this paper constructs a price prediction model of cryptocurrencies using a variety of machine learning and deep learning algorithms. It turns out that the trading price premium rate in different markets will affect the price to be predicted, and adding social media comment features can significantly improve the accuracy of the forecast. This article is conducive to investors who encrypt currencies to make more scientific decisions.
Abstract This paper aims to model the joint dynamics of cryptocurrencies in a nonstationary setting. In particular, we analyze the role of cointegration relationships within a large system of cryptocurrencies in a vector error correction model (VECM) framework. To enable analysis in a dynamic setting, we propose the COINtensity VECM, a nonlinear VECM specification accounting for a varying systemwide cointegration exposure. Our results show that cryptocurrencies are indeed cointegrated with a cointegration rank of four. We also find that all currencies are affected by these long term equilibrium relations. The nonlinearity in the error adjustment turned out to be stronger during the height of the cryptocurrency bubble. A simple statistical arbitrage trading strategy is proposed showing a great in-sample performance, whereas an out-of-sample analysis gives reason to treat the strategy with caution.
Abstract In this paper, cryptocurrencies are analysed as investment instruments. The study aims to verify whether they can be classified as an asset class and what kind of benefits they may bring to the investor's portfolio. We used 6 indices as proxies for the major asset classes, including the cryptocurrency index CRIX, for all cryptographic assets. Cryptocurrencies relatively fully satisfied 7 asset class requirements, namely stable aggregation, investability, internal homogeneity, external heterogeneity, expected utility, selection skill and cost-effective access. It was found that crypto assets have diversification properties. Portfolio optimisation with the Modern Portfolio Theory showed an increase in the Sharpe ratio of tangency portfolios with the inclusion of CRIX. However, the Post-Modern Portfolio Theory identified significant deterioration of the downside risk and the Sortino ratio.
As a decentralized distributed ledger, blockchain has developed rapidly since its birth and has been highly valued by governments, academia, and industry. Start in the financial field, blockchain technology has been rapidly applied to various fields such as the Internet of Things, supply chain, and healthcare. Blockchain technology has made sufficient development and innovation, but it also faces many challenges, such as security, scalability, and waste of resources. This paper starts with the development history of blockchain and combines the characteristics and technical principles of it to analyze the current academic research status and application scenarios. Meanwhile, this paper analyzes the existing outstanding blockchain projects and elaborates on their key advantages and current challenges. With discussing the ongoing development trend of blockchain, the development direction, and the research trend of blockchain in the future, this paper provides a useful reference for related research.
Mahmood A. Rashid, Krishneel Deo, Divnesh Prasad, K. Ranjith Singh · 6 authors
Abstract Blockchain is an emerging technology framework for creating and storing transaction in distributed ledgers with a high degree of security and reliability. In this paper, we present a blockchain-based platform to create and store contracts in between students and their higher education sponsors facilitated by intermediary brokers denoted as fundraisers. The sponsorship might be in any form, such as scholarship, donation, or loan. The fund will be arranged and managed by a group of competitive fundraisers who will hold the distributed ledgers and act as the miners in the blockchain network.
In Internet of Things ecosystems, where various entities trade data and data analysis results, public key infrastructure plays an important role in establishing trust relationships between these entities to specify who trusts whose private keys. The owner of a private key is provided with a public key certificate issued by a certificate authority (CA) representing a trusted third party. Although this certificate ensures the reliability of the ecosystem by verifying the data source and preventing the denial of trading, it often causes an overconcentration of trust in a particular CA. Consequently, if that CA is infringed, all the related trust relationships become compromised. The paper proposes a distributed authentication infrastructure called Meta-PKI that decentralizes such overconcentration via a cross-certification procedure performed by multiple CAs. Although cross-certification is capable of establishing mutual trust relationships, it does not evaluate the trustworthiness of other CAs in a standardized manner. Therefore, this paper also proposes a new cross-certification method using a distributed ledger technology for building trust relationships based on unified criteria. It also describes the implementation of a Meta-PKI system for Hyperledger Fabric as a proof of concept. Once trust relationships have been established, it takes approximately 65.7 ms to validate them using the proposed system, which is secure against CA takeover and spoofing by outsider attackers.
Industry 4.0 encompasses a promise of a new industrial revolution in terms of providing secure, intelligent, autonomous and self-adaptive industrial IoT (IIoT) networks. Key industrial applications and systems will be significantly more complex due to the involvement of the vast number of different devices and diverse nature of various stakeholders and service providers. These complex industrial processes, services and applications also have strict requirements in terms of performance - latency in particular - and resource-efficiency, together with high standards for security and trust. In this context, Blockchain and Edge Computing emerge as prominent technologies to address the mentioned essential requirements and to further strengthen the rise of the new era of digitization. The Edge computing paradigm ensures low latency services for IIoT applications while optimizing the network usage, whereas Blockchain provides a decentralized way for ensuring data integrity, trust and security. In this paper, we propose a `BlockEdge' framework that combines these two enabling technologies to address some of the critical issues faced by the current IIoT networks. We verify the feasibility of our approach by evaluating the performance and resource-efficiency of BlockEdge in terms of latency, power consumption and network usage, through simulations against non-Blockchain solution.
The Internet of Medical Things (IoMT) is a kind of connected infrastructure of smart medical devices along with software applications, health systems and services. These medical devices and applications are connected to healthcare systems through the Internet. The Wi-Fi enabled devices facilitate machine-to-machine communication and link to the cloud platforms for data storage. IoMT has the ability to make accurate diagnoses, with fewer mistakes and lower costs of care. IoMT with smartphone applications permits the patients to exchange their health related confidential and private information to the healthcare experts (i.e., doctors) for the better control of diseases, and also for tracking and preventing chronic illnesses. Due to insecure communication among the entities involved in IoMT, an attacker can tamper with the confidential and private health related information for example an attacker can not only intercept the messages, but can also modify, delete or insert malicious messages during communication. To deal this sensitive issue, we design a novel blockchain enabled authentication key agreement protocol for IoMT environment, called BAKMP-IoMT. BAKMP-IoMT provides secure key management between implantable medical devices and personal servers and between personal servers and cloud servers. The legitimate users can also access the healthcare data from the cloud servers in a secure way. The entire healthcare data is stored in a blockchain maintained by the cloud servers. A detailed formal security including the security verification of BAKMP-IoMT using the widely-accepted Automated Validation of Internet Security Protocols and Applications (AVISPA) tool is performed to demonstrate its resilience against the different types of possible attack. The comparison of BAKMP-IoMT with relevant existing schemes is conducted which identifies that the proposed system furnishes better security and functionality, and also needs low communication and computational costs as compared to other schemes. Finally, the simulation of BAKMP-IoMT is conducted to demonstrate its impact on the performance parameters.
The distributed ledger technology has been widely hailed as the break-through technology. It has realised a great number of application scenarios, and improved workflow of many domains. Nonetheless, there remain a few major concerns in adopting and deploying the distributed ledger technology at scale. In this white paper, we tackle two of them, namely the throughput scalability and confidentiality protection for transactions. We learn from the existing body of research, and build a scale-out blockchain platform that champions privacy called RVChain. RVChain takes advantage of trusted execution environment to offer confidentiality protection for transactions, and scales the throughput of the network in proportion with the number of network participants by supporting parallel shadow chains.
Access control management is an integral part of maintaining the security of an application. Although there has been significant work in the field of cloud access control mechanisms, however, with the advent of Distributed Ledger Technology (DLT), on-chain access control management frameworks hardly exist. Existing access control management mechanisms are tightly coupled with the business logic, resulting in governance issues, non-coherent with existing Identity Management Solutions, low security, and compromised usability. We propose a novel framework to implement dynamic role-based access control for decentralized applications (dApps). The framework allows for managing access control on a dApp, which is completely decoupled from the business application and integrates seamlessly with any dApps. The smart contract architecture allows for the independent management of business logic and execution of access control policies. It also facilitates secure, low cost, and a high degree of flexibility of access control management. The proposed framework promotes decentralized governance of access control policies and efficient smart contract upgrades. We also provide quantitative and qualitative metrics for the efficacy and efficiency of the framework. Any Turing complete smart contract programming language is an excellent fit to implement the framework. We expect this framework to benefit enterprise and non-enterprise dApps and provide greater access control flexibility and effective integration with traditional and state of the art identity management solutions.
OAuth 2.0 is the industry-standard protocol for authorization. It facilitates secure service provisioning, as well as secure interoperability among diverse stakeholders. All OAuth 2.0 protocol flows result in the creation of an access token, which is then used by a user to request access to a protected resource. Nevertheless, the definition of access tokens is transparent to the OAuth 2.0 protocol, which does not specify any particular token format, how tokens are generated, or how they are used. Instead, the OAuth 2.0 specification leaves all these as design choices for integrators. In this paper, we propose a new type of OAuth 2.0 token backed by a distributed ledger. Our construction is secure, and it supports proof-of-possession, auditing, and accountability. Furthermore, we provide added-value token management services, including revocation, delegation, and fair exchange by leveraging smart contracts. We realized a proof-of-concept implementation of our solution using Ethereum smart contracts and the ERC-721 token specification.