A treasury system is a community-controlled and decentralized collaborative decision-making mechanism for sustainable funding of blockchain development and maintenance. During each treasury period, project proposals are submitted, discussed, and voted for; top-ranked projects are funded from the treasury. The Dash governance system is a real-world example of such kind of systems. In this work, we, for the first time, provide a rigorous study of the treasury system. We modelled, designed, and implemented a provably secure treasury system that is compatible with most existing blockchain infrastructures, such as Bitcoin, Ethereum, etc. More specifically, the proposed treasury system supports liquid democracy/delegative voting for better collaborative intelligence. Namely, the stake holders can either vote directly on the proposed projects or delegate their votes to experts. Its core component is a distributed universally composable secure end-to-end verifiable voting protocol. The integrity of the treasury voting decisions is guaranteed even when all the voting committee members are corrupted. To further improve efficiency, we proposed the world's first honest verifier zero-knowledge proof for unit vector encryption with logarithmic size communication. This partial result may be of independent interest to other cryptographic protocols. A pilot system is implemented in Scala over the Scorex 2.0 framework, and its benchmark results indicate that the proposed system can support tens of thousands of treasury participants with high efficiency.
The purpose of this study is to develop robust estimation of association between two types of crypto-currencies namely Bitcoin and Ethereum. Daily data of crypto-currencies are collected from https://coinmarketcap.com. The period for data analysis is started from January 2017 until October 2018. The value of mean return for Bitcoin is 13.18 %. Meanwhile, the value of mean return for Ethereum is 27.85 %. The standard deviation for Bitcoin is 30.27 % and Ethereum is 64.24 %. Then, this study performed Person product moment coefficient analysis to evaluate the correlation between these two crypto-currencies. Result indicates the association coefficient value is 0.50. The correlation shows there is strong positive correlation between Bitcoin return and Ethereum return. As conclusion, there is significant relationship between Bitcoin and Ethereum return data with strong positive correlation (r = 0.503, n = 21, p =0.020).The significant of this study is to help investors to make better decision in selecting appropriate investment portfolio for their investment fund that contributes better return and lower risk.
There has been a burgeoning Fintech literature in the past years, especially on cryptocurrencies. However, there is lack of research handling cryptocurrencies in a mainstream macroeconomic model. To bridge the gap, we develop a model for Bitcoin-like cryptocurrency as risky and costly bubbles in an infinite-horizon production economy. This model is consistent with the following facts: i) the surging Bitcoin market presents enormous volatility, ii) its price dynamics are significantly sensitive to both market sentiment and policy stances. Entrepreneurial firms choose to hold Bitcoins as liquid assets to buffer idiosyncratic investment distortions. The intrinsically worthless Bitcoins can emerge as rational bubbles when the market sentiment is optimistic enough. On the one hand, bubbly Bitcoins provide market liquidity to facilitate investment in the real sector, while on the other hand, they deteriorate the investment efficiency and crowd out aggregate production. Our quantitative exercise produces various cyclical features of Bitcoin bubbles and find that the collapse of Bitcoin bubbles can improve social welfare by decreasing distortion-driven real investment.
Jan 1, 2018·Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences
Due to the disruptive role of the Bitcoin in the financial sector, both scholars and practitioners are increasingly wondering whether it is possible to replicate the impact of the Blockchain technology in the supply chain context. As a distributed ledger technology characterized by the decentralized consensus, Blockchain is touted by many as the proper platform to collect all the information about supply chains from the producer to the consumer. However, the current technology immaturity and the lack of successful supply chain implementations pave the way for doubt about the disruptive role of this technology in supply chains. To the authors’ knowledge, this work is one of the very first attempts to link the blockchain technology to supply chain and logistics. This paper investigates the state-of-the-art application of blockchain in supply chains, exploring both the literature and the industry initiatives, contributing to the increase of the managerial insight and providing a future research agenda.
Sepideh Avizheh, Reihaneh Safavi–Naini, Siamak F. Shahandashti
BIP70 is the Bitcoin payment protocol for communication between a merchant and a pseudonymous customer. McCorry et al. (FC~2016) showed that BIP70 is prone to refund attacks and proposed a fix that requires the customer to sign their refund request. They argued that this minimal change will provide resistance against refund attacks. In this paper, we point out the drawbacks of McCorry et al.'s fix and propose a new approach for protection against refund attacks using the Bitcoin multi-signature mechanism. Our solution does not rely on merchants storing refund requests, and unlike the previous solution, allows updating refund addresses through email. We discuss the security of our proposed method and compare it with the previous solution. We also propose a novel application of our refund mechanism in providing anonymity for payments between a payer and payee in which merchants act as mixing servers. We finally discuss how to combine the above two mechanisms in a single payment protocol to have an anonymous payment protocol secure against refund attacks.
Ilaria Bertazzi, Sylvie Huet, Guillaume Deffuant, Floriana Gargiulo
Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bit- coin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason, a web of trust is implemented on the website. The availability of all the historic of the users interaction data makes this dataset a unique playground for studying reputation dynamics through others evaluations. We analyze the structure and the dynamics of this web of trust with a multilayer network approach distin- guishing the rewarding and the punitive behaviors. We show that the rewarding and the punitive behavior have similar emergent topological properties (apart from the clustering coefficient being higher for the rewarding layer) and that the resultant reputation originates from the complex interaction of the more regular behaviors on the layers. We show which are the behaviors that correlate (i.e. the rewarding activity) or not (i.e. the punitive activity) with reputation. We show that the network activity presents bursty behaviors on both the layers and that the inequality reaches a steady value (higher for the rewarding layer) with the network evolution. Finally, we characterize the reputation trajectories and we identify prototypical behaviors associated to three classes of users: trustworthy, untrusted and controversial.
We develop a strong diagnostic for bubbles and crashes in bitcoin, by analyzing the coincidence (and its absence) of fundamental and technical indicators. Using a generalized Metcalfe's law based on network properties, a fundamental value is quantified and shown to be heavily exceeded, on at least four occasions, by bubbles that grow and burst. In these bubbles, we detect a universal super-exponential unsustainable growth. We model this universal pattern with the Log-Periodic Power Law Singularity (LPPLS) model, which parsimoniously captures diverse positive feedback phenomena, such as herding and imitation. The LPPLS model is shown to provide an ex-ante warning of market instabilities, quantifying a high crash hazard and probabilistic bracket of the crash time consistent with the actual corrections; although, as always, the precise time and trigger (which straw breaks the camel's back) being exogenous and unpredictable. Looking forward, our analysis identifies a substantial but not unprecedented overvaluation in the price of bitcoin, suggesting many months of volatile sideways bitcoin prices ahead (from the time of writing, March 2018).
George Bissias, Brian Neil Levine, David Thibodeau
Abrupt changes in the miner hash rate applied to a proof-of-work (PoW) blockchain can adversely affect user experience and security. Because different PoW blockchains often share hashing algorithms, miners face a complex choice in deciding how to allocate their hash power among chains. We present an economic model that leverages Modern Portfolio Theory to predict a miner's allocation over time using price data and inferred risk tolerance. The model matches actual allocations with mean absolute error within 20% for four out of the top five miners active on both Bitcoin (BTC) and Bitcoin Cash (BCH) blockchains. A model of aggregate allocation across those four miners shows excellent agreement in magnitude with the actual aggregate as well a correlation coefficient of 0.649. The accuracy of the aggregate allocation model is also sufficient to explain major historical changes in inter-block time (IBT) for BCH. Because estimates of miner risk are not time-dependent and our model is otherwise price-driven, we are able to use it to anticipate the effect of a major price shock on hash allocation and IBT in the BCH blockchain. Using a Monte Carlo simulation, we show that, despite mitigation by the new difficulty adjustment algorithm, a price drop of 50% could increase the IBT by 50% for at least a day, with a peak delay of 100%.
Jan 1, 2018·International Conference on International Conference on Emerging Technologies in Computing 2018 (iCETiC '18) , 23rd -24th August, 2018, at London Metropolitan University, London, UK, Published by Springer-Verlag
Blockchain (BC), the technology behind the Bitcoin cryptocurrency system, is starting to be adopted for ensuring enhanced security and privacy in the Internet of Things (IoT) ecosystem. Fervent research is currently being focused in both academia and industry in this domain. Proof of Work (PoW), a cryptographic puzzle, plays a vital role in ensuring BC security by maintaining a digital ledger of transactions, which are considered to be incorruptible. Furthermore, BC uses a changeable Public Key (PK) to record the identity of users, thus providing an extra layer of privacy. Not only in cryptocurrency has the successful adoption of the BC been implemented, but also in multifaceted non-monetary systems, such as in: distributed storage systems, proof of location and healthcare. Recent research articles and projects or applications were surveyed to assess the implementation of the BC for IoT Security and identify associated challenges and propose solutions for BC enabled enhanced security for the IoT ecosystem.
As the underlying technology in Bitcoin, the blockchain technology has gained wide attention. Blockchain is a kind of feasible method to solve the consistency problem of distributed system. Consensus mechanism is the core of the blockchain technology. Delicate consensus mechanism can improve system performance and promote the application of blockchain in many fields. Based on the consensus mechanisms in existing design of blockchain, this paper summarizes the basic consensus mechanisms including proof of work, proof of stake and Byzantine consistency agreement, and evaluates them from various aspects such as security, scalability, performance, etc. The future research on the blockchain consensus mechanism will be based on the different characteristics of the consensus mechanisms, and design should be carried out around the combination of different consensus mechanisms.
This thesis is one in a group of several theses that are researching different subjects in the development of a new cryptocurrency. For a few years now, the cryptocurrency market has grown dramatically, in the lead of the original cryptocurrency Bitcoin. Today, most cryptocurrencies' validation-technology, including Bitcoin's, are based on Proof-of-Work (PoW), i.e., a system where transaction validation is made by servers calculating mathematical problems. PoW results in high energy consumption and slow transaction speed. In this cryptocurrency, the validation mechanism will build on a technology called Proof-of-Stake (PoS). PoS does not yield as high energy consumption and often leads to faster transaction speed. The specific technique for validation in this system is that validators bet their coins to validate transactions and get rewards in the form of transaction fees if they end up conforming the transactions that reach consensus among the validators. In particular, the purpose of this report is to research the risk and reward for validators in the betting process and from this develop a reward policy which yields a fast and secure validation. The methods used for solving the problems are simulations based on Monte Carlo methods. From the simulations, the results are discussed and compared. Also, this report will cover economic theories behind cryptocurrencies, mainly focusing on monetary policy and the transaction markets. The findings of this report are several risk functions for different topologies and winning conditions considered during the development of the cryptocurrency. Further, a conclusion was that the expected value of profit for validators need to be constant, independent of when the bets are made with regard to previous bets. From this, a reward function which distributes rewards between winning validators was formed. Another, economical conclusion from this was that, in the long run, the expected value of profit of betting should converge to zero due to a perfect competition market.
Abstract Cryptocurrencies are expected to have a significant impact on banking, finance, and monetary systems. Due to the uncertainty as to the possible future trajectories of the evolving cryptocurrency ecosystem, governments have taken a relatively hands-off approach to regulating such currencies. This approach may be justified within the theoretical information-economics framework of this paper, which draws parallels between the information economics of money and quasi-money creation within the current central banking, commercial banking, and shadow banking systems with that of the cryptocurrency ecosystem. In particular, drawing lessons from the literature on the role of information in creating ‘safe assets’, in this paper the authors find that by building on symmetric (common) knowledge as to the inner workings of the Bitcoin Blockchain—though in a different way—bitcoin possesses a degree of endogenous information insensitivity typical of safe assets. This endogenous information insensitivity could support bitcoin’s promise of maturing into a viable store of value and a niche medium of exchange. This finding should not be overlooked in the policy discussions for potential future regulatory interventions in the cryptocurrency ecosystem.
Unspent Transaction Outputs (UTXOs) are the internal mechanism used in many cryptocurrencies to represent coins. Such representation has some clear benefits, but also entails some complexities that, if not properly handled, may leave the system in an inefficient state. Specifically, inefficiencies arise when wallets (the software responsible for transferring coins between parties) do not manage UTXOs properly when performing payments. In this paper, we study three cryptocurrencies: Bitcoin, Bitcoin Cash and Litecoin, by analysing the state of their UTXO sets, that is, the status of their sets of spendable coins. These three cryptocurrencies are the top-3 UTXO-based cryptocurrencies by market capitalization. Our analysis shows that the usage of each cryptocurrency presents some differences, and led to different results. Furthermore, it also points out that the management of the transactions has not always been performed efficiently and therefore, the current state of the UTXO sets is far from ideal.
Predicting currency prices remains a difficult endeavour. Investors are continually seeking new ways to extract \nmeaningful information about the future direction of price changes. Recently, cryptocurrencies have attracted \nhuge attention due to their unique way of transferring value as well as its value as a hedge. A method proposed \nin this project involves using data mining techniques: mining text documents such as news articles and tweets \ntry to infer the relationship between information contained in such items and cryptocurrency price direction. \nThe Long Short-Term Memory Recurrent Neural Network (LSTM RNN) assists in creating a hybrid model \nwhich comprises of sentiment analysis techniques, as well as a predictive machine learning model. The success \nof the model was evaluated within the context of predicting the direction of Bitcoin price changes. Findings \nreported here reveal that our system yields more accurate and real-time predictions of Bitcoin price fluctuations \nwhen compared to other existing models in the market.
Fintech (or financial technology) is the current driving force behind innovations in the financial services industry. One of the most debated innovations is cryptocurrency, or digital currency, which uses blockchain technology to make a direct electronic payment between two people possible, without going through a third party (like a bank) or expensive intermediaries in order to save costs. This future money is pressurising central banks to manage the looming threat of redundancy as it overshadows fiat currency in a world of infinite fintech possibilities. Bitcoin, being the first decentralised cryptocurrency, will be the focus of this research. This digital currency is not produced by minting money in an unlimited supply, but through a virtual mining process designed to control the supply of money and make it more valuable. The increasing pace in financial innovation is pushing regulators to make a change in the way they define money and what money can be. Traditionally money is used to serve as a medium of exchange, legal tender for repayment of debt, standard of value, unit of accounting measure and a means to save or store purchasing power. Bitcoin may not fulfill all the functions of money but its scarcity value, anonymity (or pseudonymity), transparency, and autonomy from the government, make it attractive to users who are speculators, traders, merchants, consumers and netizens disenchanted with fiat money. Despite the alluring features of Bitcoin, it is not spared from potential abuses such as webcrimes, tax evasion, fraud, online black markets, money laundering and terrorism financing. In this paper, a forensic examination of Bitcoins benefits and risks will help regulators decide whether to adopt cryptocurrency and provide an appropriate framework to regulate it based on other jurisdictions approach. This paper recommends that Malaysia should fully embrace cryptocurrency due to global trends - the Islamic Development Bank is developing Shariah compliant contracts using blockchain technology; China is leading the drive to develop its own national cryptocurrency to complement fiat money; and a Shariah-compliant cryptocurrency has already entered the market backed by gold (Onegram). Financial and regulatory architectures in Malaysia should accommodate these changes to remain relevant. In addition, future research is recommended focusing on developing a Shariah compliant national cryptocurrency that is unique to Malaysia.