This paper aims to gain and improve understanding of the three most common cryptocurrencies (Bitcoin, Ethereum and Ripple) by applying standard econometric tools upon their time-series data.Cryptocurrencies' returns are compared to six major stock indices: two American (S&P500 and Russell 2000), one European (Stoxx 600), one Japanese (Nikkei 225), one Chinese (Hong Kong Hang Seng) and a global index (S&P Global 1200).The findings indicate that observed cryptocurrencies could be regarded as a new asset class, a fully digital, sui-generis financial instruments, as they are not coherently connected to the stock market.However, allocating capital into cryptocurrencies remains in the domain of pure speculation due to their strong volatility.
Mikael Beyene, Kannengießer, Niclas, Pandl, Konstantin D, Thiebes, Scott · 5 authors
A concept for distributed gene-drug interaction data sharing based on Ethereum Smart Contracts. The data is stored in a map with, both, keys and values utilizing a mixed-radix integer encoding that relies on the finiteness of the domains of given genes, drugs, and interactions. Thus, we get random access and, further, data queries are reduced to cheap bit comparisons.
Open access
Innovative Microfluidic and Catalytic Techniques Innovation
After demonetization, the emphasis was given on cashless economy by the Government of India. Keeping in view the concept of cashless economy, importance of Crypto currency can not be denied. Crypto currency (CC) is a virtual currency and it works as a medium of exchange by using cryptography for security. It comprises diverse currencies such as Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), Litecoin (LTC), Cardano (ADA), Neo (NEO), Stellar Lumens (XLM) and so on. Many countries like Canada, Australia, Bulgaria, Chile, Denmark, Estonia, Finland, Germany and Luxembourg have adopted Bitcoin in order to moving towards a digital eco-system. The research was conducted to find out the awareness, perception and understanding about the functioning of bitcoin among individuals. This paper is all about awareness of bitcoin amongst Individuals and prospective if allowed by the Government of India.
Paulo Vítor Jordão da Gama Silva, Augusto F.C. Neto, Marcelo Cabús Klötzle, Antônio Carlos Figueiredo Pinto · 5 authors
Research has shown that behavioral anomalies affect investors' choices and decisions in the financial markets. One such behavioral anomaly is feedback trading, a phenomenon wherein the investor uses past data to make future decisions. Using Sentana and Wadhwani's (1992) methodology, the 50 most liquid digital currencies (with the most extensive daily data reporting) were analyzed during the period 2013–2018. Results analysis suggests negative feedback trading in Tether Dollar and positive feedback trading in Bitcoin, Ethereum, CassinoCoin and ECC.
Blockchain, as an emerging technology, has become one of the hottest issues of discussion among researchers and businessmen. Different from traditional centralized database architecture where applications use central servers and databases under the authority’s control for information processing, blockchain proposes distributed digital ledgers to store data. This project explores the possibility of using blockchain technology to automate the Singapore general election polling process. Ethereum is chosen to be the blockchain protocol in this case due to its capability in executing smart contracts. For this approach, a smart contract defining general election process will be deployed to a Ethereum blockchain. Users will then connect to the network to monitor the contract. The main advantage of blockchain over the traditional client-server model in this context is system transparency and integrity which enhances the trust level citizens can place on the polling process. However, the fully distributed blockchain approach requires a huge amount of citizen data to be transferred to the distributed ledger for identity verification, which is practically infeasible in a short run due to the amount of work involved as well as citizens’ concern over privacy. In the eyes of this consideration, this project proposes a hybrid model combining the traditional centralized approach for identity verification and access control and the distributed approach for voting.
In recent years, there is growing interest in the ways the European aviation industry can leverage the multi-source data fusion towards augmented domain intelligence. However, privacy, legal and organisational policies together with technical limitations, hinder data sharing and, thus, its benefits. The current paper presents the ICARUS data policy and assets brokerage framework, which aims to (a) formalise the data attributes and qualities that affect how aviation data assets can be shared and handled subsequently to their acquisition, including licenses, IPR, characterisation of sensitivity and privacy risks, and (b) enable the creation of machine-processable data contracts for the aviation industry. This involves expressing contractual terms pertaining to data trading agreements into a machine-processable language and supporting the diverse interactions among stakeholders in aviation data sharing scenarios through a trusted and robust system based on the Ethereum platform.
Applications of blockchain technologies got a lot of attention in recent years. They exceed beyond exchanging value and being a substitute for fiat money and traditional banking system. Nevertheless, being able to exchange value on a blockchain is at the core of the entire system and has to be reliable. Blockchains have built-in mechanisms that guarantee whole system's consistency and reliability. However, malicious actors can still try to steal money by applying well known techniques like malware software or fake emails. In this paper we apply supervised learning techniques to detect fraudulent accounts on Ethereum blockchain. We compare capabilities of Random Forests, Support Vector Machines and XGBoost classifiers to identify such accounts basing on a dataset of more than 300 thousands accounts. Results show that we are able to achieve recall and precision values allowing for the designed system to be applicable as an anti-fraud rule for digital wallets or currency exchanges. We also present sensitivity analysis to show how presented models depend on particular feature and how lack of some of them will affect the overall system performance.
The Ethereum platform supports the decentralized execution of smart contracts, i.e. computer programs that transfer digital assets between users. The most common language used to develop these contracts is Solidity, a Javascript-like language which compiles into EVM bytecode, the language actually executed by Ethereum nodes. While much research has addressed the formalisation of the semantics of EVM bytecode, relatively little attention has been devoted to that of Solidity. In this paper we propose a minimal calculus for Solidity contracts, which extends an imperative core with a single primitive to transfer currency and invoke contract procedures. We build upon this formalisation to give semantics to the Ethereum blockchain. We show our calculus expressive enough to reason about some typical quirks of Solidity, like e.g. re-entrancy.
There are more and more Distributed Ledger Technologies (DLT) and it becomes difficult to assess them due to unfounded marketing claims and their open networks, which can easily be under attack. This paper presents an initial DLT assessment framework as discussed as part of the ITU focus group on application of distributed ledger technology and how it has been applied to assess one of the major existing DLT platforms at time of writing, i.e., Ethereum.
Ethereum smart contracts are executable programs, deployed on a peer-to-peer network and executed in a consensus-based fashion. Their bytecode is public, immutable and once deployed to the blockchain, cannot be patched anymore. As smart contracts may hold Ether worth of several million dollars, they are attractive targets for attackers and indeed some contracts have successfully been exploited in the recent past, resulting in tremendous financial losses. The correctness of smart contracts is thus of utmost importance. While first approaches on formal verification exist, they demand users to be well-versed in formal methods which are alien to many developers and are only able to analyze individual contracts, without considering their execution environment, i.e., calls to external contracts, sequences of transaction, and values from the actual blockchain storage. In this paper, we present Annotary, a concolic execution framework to analyze smart contracts for vulnerabilities, supported by annotations which developers write directly in the Solidity source code. In contrast to existing work, Annotary supports analysis of inter-transactional, inter-contract control flows and combines symbolic execution of EVM bytecode with a resolution of concrete values from the public Ethereum blockchain. While the analysis of Annotary tends to weight precision higher than soundness, we analyze inter-transactional call chains to eliminate false positives from unreachable states that traditional symbolic execution would not be able to handle. We present the annotation and analysis concepts of Annotary, explain its implementation on top of the Laser symbolic virtual machine, and demonstrate its usage as a plugin for the Sublime Text editor.