La blockchain propose un système d'enregistrement décentralisé, immuable et transparent. Elle offre un réseau de nœuds sans entité de gouvernance centralisée, ce qui la rend "indéchiffrable" et donc plus sûr que le système d'enregistrement centralisé sur papier ou centralisé telles que les banques. L’approche traditionnelle basée sur l’enregistrement ne fonctionne pas bien avec les relations numériques où les données changent constamment. Contrairement aux canaux traditionnels, régis par des entités centralisées, blockchain offre à ses utilisateurs un certain niveau d'anonymat en leur permettant d'interagir sans divulguer leur identité personnelle et en leur permettant de gagner la confiance sans passer par une entité tierce. En raison des caractéristiques susmentionnées de la blockchain, de plus en plus d'utilisateurs dans le monde sont enclins à effectuer une transaction numérique via blockchain plutôt que par des canaux rudimentaires. Par conséquent, nous devons de toute urgence mieux comprendre comment ces opérations sont gérées par la blockchain et combien de temps cela prend à un nœud du réseau pour confirmer une transaction et l’ajouter au réseau de la blockchain. Dans cette thèse, nous visons à introduire une nouvelle approche qui permettrait d'estimer le temps il faudrait à un nœud de la blockchain Ethereum pour accepter et confirmer une transaction sur un bloc tout en utilisant l'apprentissage automatique. Nous explorons deux des approches les plus fondamentales de l’apprentissage automatique, soit la classification et la régression, afin de déterminer lequel des deux offrirait l’outil le plus efficace pour effectuer la prévision du temps de confirmation dans la blockchain Ethereum. Nous explorons le classificateur Naïve Bayes, le classificateur Random Forest et le classificateur Multilayer Perceptron pour l’approche de la classification. Comme la plupart des transactions sur Ethereum sont confirmées dans le délai de confirmation moyen (15 secondes) de deux confirmations de bloc, nous discutons également des moyens pour résoudre le problème asymétrique du jeu de données rencontré avec l’approche de la classification. Nous visons également à comparer la précision prédictive de deux modèles de régression d’apprentissage automatique, soit le Random Forest Regressor et le Multilayer Perceptron, par rapport à des modèles de régression statistique, précédemment proposés, avec un critère d’évaluation défini, afin de déterminer si l’apprentissage automatique offre un modèle prédictif plus précis que les modèles statistiques conventionnels.
This study examines the volatility of certain cryptocurrencies and how they are influenced by the three highest capitalization digital currencies, namely the Bitcoin, the Ethereum and the Ripple. We use daily data for the period 1 January 2018-16 September 2018, which represents the bearish market of cryptocurrencies. The impact of the decline of these three cryptocurrencies on the returns of the other virtual currencies is examined with models of the ARCH and GARCH family, as well as the DCC-GARCH. The main conclusion of the study is that the majority of cryptocurrencies are complementary with Bitcoin, Ethereum and Ripple and that no hedging abilities exist among principal digital currencies in distressed times.
Emmanuelle Anceaume, Marina Papatriantafilou, Maria Potop-Butucaru, Philippas Tsigas
This paper continues the recent line of academic effort dedicated to formalizing distributed ledgers. This work is the first one to propose a specification of distributed ledger register that matches the Lamport hierarchy from safe to atomic. Moreover, we propose implementations of distributed ledger registers with safe, regular and atomic guaranties in a model of communication specific to distributed ledgers technology that we also formalize. Then, we propose an implementation of a distributed ledger register that satisfies the atomic specification and the k-consistency property that characterises the permissionless distributed blockchains such as Bitcoin and Ethereum.
Internet of Things (IoT) is growing at an exponential rate but the area of privacy and security in IoT still remains unexplored. The existing algorithms or methods are mainly centralized and hence they are vulnerable due to their single point authentication topology. As it has been estimated that by 2020 there will be more ‘things’ than people on this earth the problem of security becomes a major concern in IoT networks, as a person having control to an IoT network will be able to control a large portion of an organization. Blockchain has recently been used to provide security to peer-to-peer networks. Blockchains are computationally expensive, heavyweight and are considered unsuitable for IoT architecture. In this paper a new lightweight and secure architecture for IoT by using Ethereum Blockchain retaining most of its security providing powers is proposed. Since Blockchain is decentralized it solves the single point authentication problem existing in IoT networks. A Smart Home System as a representative case study has been implemented for broader IoT applications. The two parameters measured are temperature and intrusion detection. The proposed model tackles some more challenges that exist in IoT networks. The Qualitative evaluation of the proposed architecture highlights how it tackles various attacks.
The Blockchain for Education platform helps us to make the tamper-proof certificates and their correct and the overall permanent allocation of these certificates to learners, as well as verification of certificates. It can reduce the overall frauds and tampering of the degrees and certificates. Blockchain technology can be used to solve many educational problems and can help educators as well as learners to monitor the learning outcomes. The data can be stored securely and tamper proof format when it’s stored onto the blockchain network. Here smart contracts can be designed and deployed on to the Ethereum blockchain that can be designed using the solidity programming language. Blockchain can be applied to private, public and consortium sectors depending upon the usage and the scope of the blockchain. Education system can take benefit of this scalability of the blockchain and can be effectively useful in the educational institutions.
The Ethereum blockchain is essentially a globally replicated public database.\nPrograms called smart contracts can access this database. Over 10 million smart\ncontracts have been deployed on the Ethereum blockchain. Executing a method of\na smart contract generates a transaction that is also stored on the blockchain.\nThere are over 1 billion Ethereum transactions to date. Smart contracts that\nare transparent about their function are more successful than opaque contracts.\nWe have therefore developed a tool (ContractVis) to explore the transparency of\nsmart contracts. The tool generates a replay script for the historic\ntransactions of a smart contract. The script executes the transactions with the\nsame arguments as recorded on the blockchain, but in a minimal test\nenvironment. Running a replay script provides insights into the contract, and\ninsights into the blockchain explorer that was used to retrieve the contract\nand its history. We provide five concrete recommendations for blockchain\nexplorers like Etherscan to improve the transparency of smart contracts.\n
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3 source records
Blockchain Technology Applications and Security
Auction Theory and Applications
Advanced Steganography and Watermarking Techniques
La blockchain ha sido conocida primero a través de uno de sus más atractivos desarrollos: las criptomonedas (Ver Código QR). Hoy, palabras como Bitcoin, Ethereum, Ripple, Litecoin son oídas a diario en los noticieros, portales, redes sociales, etc., pues las monedas digitales han establecido un paradigma para todo el sistema monetario. Hoy la gestión de la salud debe pensarse como una Smart Health Care (SHC). El aprovechamiento de las tecnologías debe trascender el ejercicio de la salud, desde la atención por parte del personal médico, la gestión de centros médicos, la comunicación paciente-médico, hasta la gestión del big data, resultado de las múltiples entradas de datos en el entorno de la salud.
Petar Kochovski, Sandi Gec, Vlado Stankovski, Marko Bajec · 5 authors
Trust is a crucial aspect when cyber-physical systems have to rely on resources and services under ownership of various entities, such as in the case of Edge, Fog and Cloud computing. The DECENTER’s Fog Computing Platform is developed to support Big Data pipelines, which start from the Internet of Things (IoT), such as cameras that provide video-streams for subsequent analysis. It is used to implement Artificial Intelligence (AI) algorithms across the Edge-Fog-Cloud computing continuum which provide benefits to applications, including high Quality of Service (QoS), improved privacy and security, lower operational costs and similar. In this article, we present a trust management architecture for DECENTER that relies on the use of blockchain-based Smart Contracts (SCs) and specifically designed trustless Smart Oracles. The architecture is implemented on Ethereum ledger (testnet) and three trust management scenarios are used for illustration. The scenarios (trust management for cameras, trusted data flow and QoS based computing node selection) are used to present the benefits of establishing trust relationships among entities, services and stakeholders of the platform.
In this paper, we propose a blockchain powered automated self-incited fire detection sensors connected to smart buildings.This solution is based on utilizing Ethereum smart contracts to coordinate and monitor the interaction between the
The Internet of things (IoT) presents new opportunities and challenges due to its scale and dynamic nature. One significant challenge for the IoT is the need for security, in particular access control solutions, that are designed to meet the characteristics of these systems. Delegation of rights, from one entity to another, is a crucial component of an access control system. The IoT requires a secure, flexible, and fine-grained delegation model. While there has been considerable work in the area of delegation, much of it assumes a centralized, well-resourced system and these solutions have limited capacity in the context of the IoT. Where delegation models for the IoT have been proposed they typically provide only coarse-grained control over the delegation of rights. Moreover, many of them require a centralized trusted authority, which can suffer from a single-point failure and is not an ideal base for a large and dynamic system like the IoT. In this paper, we propose an identity-less, asynchronous, and decentralized delegation model for the IoT based on blockchain technology. We describe system components, architecture, and key aspects related to the security of the system. We use attributes to validate an entity rather than depending upon unique identities. We demonstrate the feasibility of our model through use-case examples and analyze the performance with a proof of concept testbed implementation using Ethereum private blockchain.
We study the time varying co-movement patterns of the crypto-currency prices with the help of wavelet-based methods; employing daily bilateral exchange rate of four major crypto-currencies namely Bitcoin, Ethereum, Lite and Dashcoin. First, we identify Bitcoin as potential market leader using Wavelet multiple correlation and Cross correlation. Further, Wavelet Local Multiple Correlation for the given crypto-currency prices are estimated across different time-scales. From the results, it is found that that the correlation follows an aperiodic cyclical nature, and the crypto-currency prices are driven by Bitcoin price movements. Based on the results obtained, we suggest that constructing a portfolio based on crypto-currencies may be risky at this point of time as the other crypto-currency prices are mainly driven by Bitcoin prices, and any shocks in the latter is immediately transformed to the former.
Oliver James Scholten, David Zendle, James Alfred Walker
This paper describes the York Combined Transaction Set (YCTS), which offers a single consolidated list of publicly available gambling related transactions derived from the Ethereum blockchain. This data includes over 1.4M individual transactions across 17,000+ unique addresses, which represent spending on decentralised gambling smart contracts. These contracts, and corresponding applications, have been selected based on their popularity as presented by an officially recognised ranking service, and have transacted over £240M by naive estimation over the past 10 months. Given the historical opacity of data driven gambling research, our contribution is to identify, and make available in a simple form, the transaction data found on the Ethereum blockchain such that existing questions surrounding player spending can be explored, and differences between decentralised and traditional forms of gambling can be identified.
Nowadays, it has been recognized that blockchain can provide the technological infrastructure for developing decentralized, secure, and reliable smart energy grid management systems. However, an open issue that slows the adoption of blockchain technology in the energy sector is the low scalability and high processing overhead when dealing with the real-time energy data collected by smart energy meters. Thus, in this paper, we propose a scalable second tier solution which combines the blockchain ledger with distributed queuing systems and NoSQL (Not Only SQL database) databases to allow the registration of energy transactions less frequently on the chain without losing the tamper-evident benefits brought by the blockchain technology. At the same time, we propose a technique for tamper-evident registration of smart meters' energy data and associated energy transactions using digital fingerprinting which allows the energy transaction to be linked hashed-back on-chain, while the sensors data is stored off-chain. A prototype was implemented using Ethereum and smart contracts for the on-chain components while for the off-chain components we used Cassandra database and RabbitMQ messaging broker. The prototype proved to be effective in managing a settlement of energy imbalances use-case and during the evaluation conducted in simulated environment shows promising results in terms of scalability, throughput, and tampering of energy data sampled by smart energy meters.
Francesco Longo, Letizia Nicoletti, Antonio Padovano, Gianfranco d’Atri · 5 authors
Despite Information and Communication Technologies (ICT) have reduced the information asymmetry and increased the degree of interorganizational collaboration, the companies participating a supply chain are less inclined to share data when information is sensible and partners cannot be fully trusted. In such a context, Blockchain is a decentralized certificate authority that may provide economic and operational benefits but companies operating in a supply chain claim to have little knowledge about Blockchain due to its novelty and to the lack of use cases and application studies. In this work, a software connector has been designed and developed to connect an Ethereum-like blockchain with the enterprises' information systems to allow companies to share information with their partners with different levels of visibility and to check data authenticity, integrity and invariability over time through the blockchain, thus building trust. In order to explore the potential of deploying the blockchain in a supply chain, a simulation model has been developed to recreate the supply chain operations and integrated with the blockchain through the same software connector to carry out a scenario statistical analysis. Application results shows how blockchain technology is a convenient instrument to overcome collaboration and trust issues in a supply chain, to increase the supply chain overall performance, to minimize the negative consequences of information asymmetry over the echelons of a supply chain but also to discourage companies from any misconduct (e.g. counterfeiting data or low data accuracy).
We present solc-verify, a source-level verification tool for Ethereum smart contracts. Solc-verify takes smart contracts written in Solidity and discharges verification conditions using modular program analysis and SMT solvers. Built on top of the Solidity compiler, solc-verify reasons at the level of the contract source code, as opposed to the more common approaches that operate at the level of Ethereum bytecode. This enables solc-verify to effectively reason about high-level contract properties while modeling low-level language semantics precisely. The contract properties, such as contract invariants, loop invariants, and function pre- and post-conditions, can be provided as annotations in the code by the developer. This enables automated, yet user-friendly formal verification for smart contracts. We demonstrate solc-verify by examining real-world examples where our tool can effectively find bugs and prove correctness of non-trivial properties with minimal user effort.
Mark Mossberg, Felipe Andrés Manzano, Eric Hennenfent, Alex Groce · 8 authors
An effective way to maximize code coverage in software tests is through dynamic symbolic execution$-$a technique that uses constraint solving to systematically explore a program's state space. We introduce an open-source dynamic symbolic execution framework called Manticore for analyzing binaries and Ethereum smart contracts. Manticore's flexible architecture allows it to support both traditional and exotic execution environments, and its API allows users to customize their analysis. Here, we discuss Manticore's architecture and demonstrate the capabilities we have used to find bugs and verify the correctness of code for our commercial clients.
The subject of the research is the NEO and Ethereum cryptocurrencies. The relevance of the research is due to the following. First, these cryptocurrencies are expected to play the key role in establishing the future digital economy. Second, cryptocurrency developers are competing to gain leading positions in the development of financial technologies of the digital revolution. Third, the above cryptocurrencies are designed to perform almost identical functions, therefore, to determine the advantages of either of them, a comparative analysis is needed and appropriate conclusions for the Russian economy should be made. The purpose of the paper was to perform a comparative analysis of the Ethereum and NEO cryptocurrencies to identify trends in the digital economy of the future and determine the main targets to enable Russia’s entry into the top five largest world economies. The information sources include articles, books, regulations, departmental documents and conference materials on FinTech, crypto-markets and the digital economy. The research made it possible to reveal specific features of the cryptocurrencies and the corresponding digital platforms that are important for the development of the digital economy of the future. The goal of Ethereum developers is to create a platform for decentralized applications, based on which it will be possible to form a global, easy-to-access, free and reliable Internet of the future. The paper concludes that at present, the NEO has advantages over the Ethereum in terms of both the transaction speed and operational fitness for the development of prospective technologies of the digital economy. However, it may happen that in the near future, the Ethereum developers will be able to improve their blockchain technology so as to ensure the priority of their project in the competition for leadership in the development of the digital economy of the future. Given the contradictions revealed and taking into account the raw materials orientation of the Russian economy, a number of targets are proposed to bring Russia into the five largest world economies.
Blockchain je u proteklih nekoliko godina dobio široku pozornost zbog njegove primjene na kripto valutama i tehnologijama distribuiranih knjiga (Distributed Ledger), kao što su Bitcoin i Ethereum. Složena i decentralizirana priroda blockchain tehnologija otežava razumijevanje ponašanja pojedinih komponenata i njihovog učinka na blockchain sustav. Dolaskom novih konsenzus algoritama, kao što je Proof of Authority (PoA), razumijevanje ovog složenog sustava postaje izazovan zadatak. U ovom radu predlažemo PoASim, podesiv, diskretni simulacijski alat za simulaciju dvaju glavnih PoA algoritama, nazvanih Clique i Aura. PoASim može pomoći korisnicima da bolje razumiju temeljne slojeve Ethereum blockchain-a, kao i razumijevanje razlika konsenzusa i nedostataka između dva konsenzus algoritma. PoASim tako može poslužiti kao koristan alat za bolje razumijevanje ponašanja svakog konsenzusa pokretanjem simulacija s različitim parametrima i analizom ponašanja sustava.
The automotive industry has seen an increased need for connectivity, both as a result of the advent of autonomous driving and the rise of connected cars and truck fleets. This shift has led to issues such as trusted coordination and a wider attack surface have come to light, leading to higher costs and bureaucratic interventions. Due to the increasing adoption of connected vehicles, as well as other connected infrastructure, trustless peer to peer systems including blockchain are being explored as potential solution to this efficiency problem. All the while, scalability is still a significant concern for industry players. Current blockchain based systems have difficulty scaling: Bitcoin can only process seven transactions per second (tx/s) whereas Ethereum's fifteen tx/s is not a major improvement. Combined with the high cost of consensus and low throughput, such platforms are unusable with the mobility sector. This paper will address the latest advances in the field that aim to resolve parts of this problem as well as inform its readers about the scalability technologies that could push blockchain automotive infrastructure into the mainstream. This paper will also introduce the theoretical tools and advancements that, if implemented, could bring the mobility industry closer toward adopting efficient, scalable, and cost effective decentralized solutions.
Since the invention of Bitcoin one decade ago, numerous cryptocurrencies have sprung into existence. Among these, proof-of-work is the most common mechanism for achieving consensus, whilst a number of coins have adopted "ASIC-resistance" as a desirable property, claiming to be more "egalitarian,"S where egalitarianism refers to the power of each coin to participate in the creation of new coins. While proof-of-work consensus dominates the space, several new cryptocurrencies employ alternative consensus, such as proof-of-stake in which block minting opportunities are based on monetary ownership. A core criticism of proof-of-stake revolves around it being less egalitarian by making the rich richer, as opposed to proof-of-work in which everyone can contribute equally according to their computational power. In this paper, we give the first quantitative definition of a cryptocurrency's \emph{egalitarianism}. Based on our definition, we measure the egalitarianism of popular cryptocurrencies that (may or may not) employ ASIC-resistance, among them Bitcoin, Ethereum, Litecoin, and Monero. Our simulations show, as expected, that ASIC-resistance increases a cryptocurrency's egalitarianism. We also measure the egalitarianism of a stake-based protocol, Ouroboros, and a hybrid proof-of-stake/proof-of-work cryptocurrency, Decred. We show that stake-based cryptocurrencies, under correctly selected parameters, can be perfectly egalitarian, perhaps contradicting folklore belief.
Today, the world is on the threshold of a digital revolution that will affect all spheres of public life. The application of cryptocurrencies and blockchain technology has gone a long way since its introduction. Now it has reached a new milestone as it gets implemented in the energy sector. Blockchain and cryptographic technology have the potential to radically change the energy industry of the usual. Blockchain and cryptocurrencies are changing the energy sector and in the article is considered how it will affect the energy industry. Blockchain systems and cryptocurrencies no longer require either intermediaries or a central authority. But it is still difficult today to put such models into practice. In addition, there are a number of legal and regulatory requirements that blockchain projects must also comply with. Cryptocurrency is one of the most relevant topics when it comes to digitalization. On the basis of the analysis of the foreign practice of the use of cryptocurrency in the electric power industry, the prospects of implementation of such projects for Ukraine and their legal support are analyzed. Emphasized the advantages of blockchain and cryptocurrencies and demonstrates the mechanism of their work. The situation regarding the definition of the legal status of cryptographic goods in foreign countries and Ukraine is analysed. The main points to be solved in the course of approval of the right regulation of cryptocurrencies in Ukraine are determined. Foreign and certain domestic experience of using the blockchain technology and cryptology in the field of electric power industry indicates the prospect of further development of this direction. In the implementation of such instruments,it seems that it will allow accelerating the payments in electricity supply relations, will allow them to be more transparent, and at the same time protected from unauthorized interference, enhance the culture of contractual relations. REFERENCES1. Maidanyk R.A. Virtualna valiuta v tsyvilnomu pravi Ukrainy: stan, tendentsii, perspektyvy. Visn. Nats. akad. prav. nauk Ukrainy. 2018. Vol. 25, No. 2. P. 114-129 [in Ukrainian].2. Husieva I.I., Petrova T.O. Tendentsii rozvytku kryptovaliut na rynku Ukrainy. Naukovyi visnyk Mizhnarodnoho humanitarnoho universytetu. 2017. Iss. 24 (1). P. 48050 [in Ukrainian].3. Lukianov V.S. Zarodzhennia rynku kryptovaliuty v informatsiino-merezhevii paradyhmi. Aktualni problemy ekonomiky. 2014. No. 8 (158). P. 4360441 [in Ukrainian].4. Svon M. Blokchejn: Shema novoj jekonomiki. M.: Olimp-biznes, 2017. 240 p. [in Russian].5. Blokchein — novi mozhlyvosti dlia vyrobnykiv ta spozhyvachiv elektroenerhii? Ohliad svitovoi elektroenerhetyky, pidhotovlenyi PwC. Pricewaterhouse Coopers International Limited (PwCIL), 2016. URL: https://www.pwc.ru/ru/publications/blockchain/blockchain_opportunity-for-energy-producers%20and-consumers_RUS.pdf [in Ukrainian].6. Directive (EU) 2015/849 of the European Parliament and of the Council of 20 May 2015 on the prevention of the use of the financial system for the purposes of money laundering or terrorist financing. EUR-Lex: Access to European Union law. URL: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex%3A32015L08497. Federal act on banks and savings banks. URL: https://www.admin.ch/opc/de/classifiedcompilation/19340083/index.html8. O razvitii cifrovoj jekonomiki: Dekret Prezidenta Respubliki Belarus' ot 21.12.2017 № 8. URL: http://president.gov.by/ru/official_documents_ru/view/dekret-8-ot-21-dekabrja-2017-g-17716/ [in Russian].9. Zelena knyha rehuliuvannia rynku kryptovaliut: Ofis efektyvnoho rehuliuvannia. Traven 2018. URL: https://cdn.regulation.gov.ua/fe/5b/20/42/regulation.gov.ua_Zelena-Knyha.-Rynok-Kryptovaliut.pdf [in Ukrainian].10. Bitcoins: Aufsichtliche Bewertung und Risiken für Nutzer. Bundesanstalt für Finanzdienstleistungsaufsicht. 19.12.2013. URL: https://www.bafin.de/SharedDocs/Veroeffentlichungen/DE/Fachartikel/2014/fa_bj_1401_bitcoins.html [in German].11. Blockchain: Hype or Innovation: CoinForum.de. 26.02.2016. URL: https://Bitcoinblog.de/2016/02/26/rwe-undslock-it-wollen-ethereum-fuer-elektroautos-nutzen/12. Kryptovaliuta SolarCoin ta soniachni elektrostantsii. "SolarCoin" Nova kryptovaliuta yaka stymuliuie montazh dzherel alternatyvnoi elektroenerhetyky. 17.01.2018. URL: https://prel.prom.ua/a322224-kriptovalyuta-solarcoinsonyachni.html [in Ukrainian].13. Pro obih kryptovaliuty v Ukraini: proekt Zakonu Ukrainy vid 06.10.2017 No. 7183. URL: http://w1.c1.rada.gov.ua/pls/zweb2/webproc4_1?pf3511=62684 [in Ukrainian].14. Pro stymuliuvannia rynku kryptovaliut ta yikh pokhidnykh v Ukraini: proekt Zakonu Ukrainy vid 10.10.2017 No. 7183-1. URL: http://w1.c1.rada.gov.ua/pls/zweb2/webproc4_1?pf3511=62710 [in Ukrainian].