A. Goriacheva, N. Jakubenko, O. Pogodina, Dmitry S. Silnov
This article is devoted to the exploration of services of anonymizing transactions, based on the Mixer, CoinJoin and CoinSuffle technologies, as well as to the description of the core principles of operation of these technologies and technical details. It analyzes the advantages and disadvantages of different realizations of this service. It formulates the problem of cryptocurrency laundering through anonymization services and offers solutions to this problem.Keywords: cryptocurrency, blockchain, bitcoin, mixing service, mining, money laundering.
The paper gives the author's understanding of the real matter of a bitcoin actual paradigm, economic and legal issues related to bitcoin functioning are investigated, perspectives of bitcoin evolution in Russia are observed on the basis of the systematic approach. In conclusion recommendations for the payment system in Russia are given. Keywords: Russia, bitcoin, economic and legal issues, bitcoin industry stakeholders, stability of payment system.
Maria Luisa Di Silvestre, Pierluigi Gallo, Mariano Giuseppe Ippolito, Eleonora Riva Sanseverino · 5 authors
The present paper considers some technical issues related to the “energy blockchain” paradigm applied to microgrids. In particular, what appears from the study is that the superposition of energy transactions in a microgrid creates a variation of the power losses in all the branches of the microgrid. Traditional power losses allocation in distribution systems takes into account only generators while, in this paper, a real-time attribution of power losses to each transaction involving one generator and one load node is done by defining some suitable indices. Besides, the presence of P-V nodes increases the level of reactive flows and provides a more complex technical perspective. For this reason, reactive power generation for voltage support at P-V nodes poses a further problem of reactive power flow exchange, which is worth of investigation in future works in order to define a possible way of remuneration. The experimental section of the paper considers a medium voltage microgrid and two different operational scenarios.
Chuka Oham, Salil S. Kanhere, Raja Jurdak, Sanjay Jha
The advent of autonomous vehicles is envisaged to disrupt the auto insurance liability model.Compared to the the current model where liability is largely attributed to the driver,autonomous vehicles necessitate the consideration of other entities in the automotive ecosystem including the auto manufacturer,software provider,service technician and the vehicle owner.The proliferation of sensors and connecting technologies in autonomous vehicles enables an autonomous vehicle to gather sufficient data for liability attribution,yet increased connectivity exposes the vehicle to attacks from interacting entities.These possibilities motivate potential liable entities to repudiate their involvement in a collision event to evade liability. While the data collected from vehicular sensors and vehicular communications is an integral part of the evidence for arbitrating liability in the event of an accident,there is also a need to record all interactions between the aforementioned entities to identify potential instances of negligence that may have played a role in the accident.In this paper,we propose a BlockChain(BC) based framework that integrates the concerned entities in the liability model and provides untampered evidence for liability attribution and adjudication.We first describe the liability attribution model, identify key requirements and describe the adversarial capabilities of entities. Also,we present a detailed description of data contributing to evidence.Our framework uses permissioned BC and partitions the BC to tailor data access to relevant BC participants.Finally,we conduct a security analysis to verify that the identified requirements are met and resilience of our proposed framework to identified attacks.
Chuka Oham, Salil S. Kanhere, Raja Jurdak, Sanjay Jha
The advent of autonomous vehicles is envisaged to disrupt the auto insurance\nliability model.Compared to the the current model where liability is largely\nattributed to the driver,autonomous vehicles necessitate the consideration of\nother entities in the automotive ecosystem including the auto\nmanufacturer,software provider,service technician and the vehicle owner.The\nproliferation of sensors and connecting technologies in autonomous vehicles\nenables an autonomous vehicle to gather sufficient data for liability\nattribution,yet increased connectivity exposes the vehicle to attacks from\ninteracting entities.These possibilities motivate potential liable entities to\nrepudiate their involvement in a collision event to evade liability. While the\ndata collected from vehicular sensors and vehicular communications is an\nintegral part of the evidence for arbitrating liability in the event of an\naccident,there is also a need to record all interactions between the\naforementioned entities to identify potential instances of negligence that may\nhave played a role in the accident.In this paper,we propose a BlockChain(BC)\nbased framework that integrates the concerned entities in the liability model\nand provides untampered evidence for liability attribution and adjudication.We\nfirst describe the liability attribution model, identify key requirements and\ndescribe the adversarial capabilities of entities. Also,we present a detailed\ndescription of data contributing to evidence.Our framework uses permissioned BC\nand partitions the BC to tailor data access to relevant BC\nparticipants.Finally,we conduct a security analysis to verify that the\nidentified requirements are met and resilience of our proposed framework to\nidentified attacks.\n
Die Digitalisierung erfasst alle Lebens- und Rechtsbereiche, auch das Gesellschaftsrecht. Der Beitrag befasst sich mit den Einflüssen der Digitalisierung auf die verschiedenen Formen der Kommunikation im Gesellschaftsrecht, sei es der virtuellen Gesellschafterversammlung oder des Einsatzes digitaler Medien in den Organen, aber auch gegenüber potentiellen Investoren. Dabei werden die jeweiligen rechtlichen Rahmenbedingungen auch jenseits des Gesellschaftsrechts beleuchtet, etwa medien- oder datenschutzrechtliche Fragen. Die Digitalisierung wirkt sich aber auch auf die Haftung der Organe aus, indem mehr verfügbare Daten und verbesserte Algorithmen dazu führen, dass die Organe die verbesserten Informationen zur Entscheidungsfindung nutzen müssen. Umgekehrt ist IT-Sicherheit heute „Chefsache“ geworden, da durch die Digitalisierung der Wertschöpfungsprozesse Unternehmen bei Ausfall ihrer IT-Systeme in ihrer Existenz bedroht werden können. Ferner ermöglicht die neue Technologie der Blockchain die eindeutige Nachvollziehung von Transaktionen, damit auch von Abstimmungen, bis hin zum Einsatz in der Rechnungslegung. Besondere Fragen werfen neue Investitionsformen unter Einsatz der Blockchain-Technologie auf, etwa die DAO Ethereum. Abschließend wird ein Blick auf die Formen der engen vertraglichen Kooperation bei Industrie 4.0 geworfen.
Sheng Wang, Tien Tuan Anh Dinh, Qian Lin, Zhongle Xie · 10 authors
Existing data storage systems offer a wide range of functionalities to accommodate an equally diverse range of applications. However, new classes of applications have emerged, e.g., blockchain and collaborative analytics, featuring data versioning, fork semantics, tamper-evidence or any combination thereof. They present new opportunities for storage systems to efficiently support such applications by embedding the above requirements into the storage. In this paper, we present ForkBase, a storage engine specifically designed to provide efficient support for blockchain and forkable applications. By integrating the core application properties into the storage, ForkBase not only delivers high performance but also reduces development effort. Data in ForkBase is multi-versioned, and each version uniquely identifies the data content and its history. Two variants of fork semantics are supported in ForkBase to facilitate any collaboration workflows. A novel index structure is introduced to efficiently identify and eliminate duplicate content across data objects. Consequently, ForkBase is not only efficient in performance, but also in space requirement. We demonstrate the performance of ForkBase using three applications: a blockchain platform, a wiki engine and a collaborative analytics application. We conduct extensive experimental evaluation of these applications against respective state-of-the-art system. The results show that ForkBase achieves superior performance while significantly lowering the development cost.
The role of the state in the processes of European integration and decentralization is analyzed, the factors of threats for it are determined. The following common features of decentralization processes in the EU member states are highlighted as strengthening the role of the regional level, the need to choose between different models of separation of powers between different levels of government (exclusive or joint authority) and the search for ways to adequately finance transferred powers. Decentralization also actualizes the problem of territorial inequality and patronage for European countries. It is proved that the national state is a central actor in the process of decentralization, despite the fact that this process creates certain threats to the state itself. On the one hand, the EU as a supranational organization has already limited some aspects of the sovereignty of its member states, in particular, in the area of monetary policy. With the deepening of European integration, the powers of national states and in other areas are increasingly limited. On the other hand, the gradual increase in the share of powers conveyed by the state to decentralized and regional authorities further weakens its role. Moreover, the increasing influence of liberalism on state policy and the introduction of competition among the main providers of public services also limits the possibility of the state’s influence on its internal policies. Such a dynamics gives grounds for questioning the ability of states to effectively manage their territories. At the same time, it was noted that in most EU member states, the bodies of state power have long been the guarantor of national unity in both social and territorial terms. Such a “unity of opposites” (decentralization and centralization) is unlikely to change in the medium term.
Eduardo Castelló Ferrer, Ognjen Rudovic, Thomas Hardjono, Alex Pentland
Robots have potential to revolutionize the way we interact with the world around us. One of their largest potentials is in the domain of mobile health where they can be used to facilitate clinical interventions. However, to accomplish this, robots need to have access to our private data in order to learn from these data and improve their interaction capabilities. Furthermore, to enhance this learning process, the knowledge sharing among multiple robot units is the natural step forward. However, to date, there is no well-established framework which allows for such data sharing while preserving the privacy of the users (e.g., the hospital patients). To this end, we introduce RoboChain - the first learning framework for secure, decentralized and computationally efficient data and model sharing among multiple robot units installed at multiple sites (e.g., hospitals). RoboChain builds upon and combines the latest advances in open data access and blockchain technologies, as well as machine learning. We illustrate this framework using the example of a clinical intervention conducted in a private network of hospitals. Specifically, we lay down the system architecture that allows multiple robot units, conducting the interventions at different hospitals, to perform efficient learning without compromising the data privacy.
It is undeniable that artificial intelligence (AI) and blockchain concepts are spreading at a phenomenal rate. Both technologies have distinct degree of technological complexity and multi-dimensional business implications. However, a common misunderstanding about blockchain concept, in particular, is that blockchain is decentralized and is not controlled by anyone. But the underlying development of a blockchain system is still attributed to a cluster of core developers. Take smart contract as an example, it is essentially a collection of codes (or functions) and data (or states) that are programmed and deployed on a blockchain (say, Ethereum) by different human programmers. It is thus, unfortunately, less likely to be free of loopholes and flaws. In this article, through a brief overview about how artificial intelligence could be used to deliver bug-free smart contract so as to achieve the goal of blockchain 2.0, we to emphasize that the blockchain implementation can be assisted or enhanced via various AI techniques. The alliance of AI and blockchain is expected to create numerous possibilities.
Today, more than 100 blockchain projects created to transform government systems are being conducted in more than 30 countries. What leads countries rapidly initiate blockchain projects? I argue that it is because blockchain is a technology directly related to social organization; Unlike other technologies, a consensus mechanism form the core of blockchain. Traditionally, consensus is not the domain of machines but rather humankind. However, blockchain operates through a consensus algorithm with human intervention; once that consensus is made, it cannot be modified or forged. Through utilization of Lawrence Lessig’s proposition that “Code is law,” I suggest that blockchain creates “absolute law” that cannot be violated. This characteristic of blockchain makes it possible to implement social technology that can replace existing social apparatuses including bureaucracy. In addition, there are three close similarities between blockchain and bureaucracy. First, both of them are defined by the rules and execute predetermined rules. Second, both of them work as information processing machines for society. Third, both of them work as trust machines for society. Therefore, I posit that it is possible and moreover unavoidable to replace bureaucracy with blockchain systems. In conclusion, I suggest five principles that should be adhered to when we replace bureaucracy with the blockchain system: 1) introducing Blockchain Statute law; 2) transparent disclosure of data and source code; 3) implementing autonomous executing administration; 4) building a governance system based on direct democracy and 5) making Distributed Autonomous Government(DAG).
This paper investigates a critical access control issue in the Internet of Things (IoT). In particular, we propose a smart contract-based framework, which consists of multiple access control contracts (ACCs), one judge contract (JC), and one register contract (RC), to achieve distributed and trustworthy access control for IoT systems. Each ACC provides one access control method for a subject-object pair, and implements both static access right validation based on predefined policies and dynamic access right validation by checking the behavior of the subject. The JC implements a misbehavior-judging method to facilitate the dynamic validation of the ACCs by receiving misbehavior reports from the ACCs, judging the misbehavior and returning the corresponding penalty. The RC registers the information of the access control and misbehavior-judging methods as well as their smart contracts, and also provides functions (e.g., register, update, and delete) to manage these methods. To demonstrate the application of the framework, we provide a case study in an IoT system with one desktop computer, one laptop and two Raspberry Pi single-board computers, where the ACCs, JC, and RC are implemented based on the Ethereum smart contract platform to achieve the access control.
Bitcoin is one of the most prominent decentralized digital cryptocurrencies. Ability to understand which factors drive the fluctuations of the Bitcoin price and to what extent they are predictable is interesting both from the theoretical and practical perspective. In this paper, we study the problem of the Bitcoin short-term volatility forecasting based on volatility history and order book data. Order book, consisting of buy and sell orders over time, reflects the intention of the market and is closely related to the evolution of volatility. We propose temporal mixture models capable of adaptively exploiting both volatility history and order book features. By leveraging rolling and incremental learning and evaluation procedures, we demonstrate the prediction performance of our model as well as studying the robustness, in comparison to a variety of statistical and machine learning baselines. Meanwhile, our temporal mixture model enables to decipher the time-varying effect of order book features on volatility. It demonstrates the prospect of our temporal mixture model as an interpretable forecasting framework over heterogeneous Bitcoin data.
In this paper, we study the ability to make the short-term prediction of the exchange price fluctuations towards the United States dollar for the Bitcoin market. We use the data of realized volatility collected from one of the largest Bitcoin digital trading offices in 2016 and 2017 as well as order information. Experiments are performed to evaluate a variety of statistical and machine learning approaches.
Cryptocurrencies are becoming an attractive asset class and are the focus of recent quantitative research. The joint dynamics of the cryptocurrency market yields information on network risk. Utilizing the adaptive LASSO approach, we build a dynamic network of cryptocurrencies and model the latent communities with a dynamic stochastic blockmodel. We develop a dynamic covariate-assisted spectral clustering method to uniformly estimate the latent group membership of cryptocurrencies consistently. We show that return inter-predictability and crypto characteristics, including hashing algorithms and proof types, jointly determine the crypto market segmentation. Based on this classification result, it is natural to employ eigenvector centrality to identify a cryptocurrency’s idiosyncratic risk. An asset pricing analysis finds that a cross-sectional portfolio with a higher centrality earns a higher risk premium. Further tests confirm that centrality serves as a risk factor well and delivers valuable information content on cryptocurrency markets.
Cryptocurrencies return cross-predictability yields information on risk
propagation and market segmentation. To explore these effects, we build a
dynamic network of cryptocurrencies based on the evolution of return
cross-predictability and develop a dynamic covariate-assisted spectral
clustering method to consistently estimate the latent group membership of
cryptocurrencies. We show that return cross-predictability and
cryptocurrencies' characteristics, including hashing algorithms and proof
types, jointly determine the cryptocurrencies market segmentation. Portfolio
analysis reveals that more centred cryptocurrencies in the network earn higher
risk premiums.
Cryptocurrencies return cross-predictability and technological similarity yield information on risk propagation and market segmentation. To investigate these effects, we build a time-varying network for cryptocurrencies, based on the evolution of return cross-predictability and technological similarities. We develop a dynamic covariate-assisted spectral clustering method to consistently estimate the latent community structure of cryptocurrencies network that accounts for both sets of information. We demonstrate that investors can achieve better risk diversification by investing in cryptocurrencies from different communities. A cross-sectional portfolio that implements an inter-crypto momentum trading strategy earns a 1.08% daily return. By dissecting the portfolio returns on behavioral factors, we confirm that our results are not driven by behavioral mechanisms.
Crowdsourcing relies on people's contributions to meet product- or system-level objectives. Crowdsourcing-based methods have been implemented in various cyber-physical systems and realtime markets. This paper explores a framework for Crowdsourced Energy Systems (CES), where small-scale energy generation or energy trading is crowdsourced from distributed energy resources, electric vehicles, and shapable loads. The merits/pillars of energy crowdsourcing are discussed. Then, an operational model for CESs in distribution networks with different types of crowdsourcees is proposed. The model yields a market equilibrium depicting traditional and distributed generator and load setpoints. Given these setpoints, crowdsourcing incentives are designed to steer crowdsourcees to the equilibrium. As the number of crowdsourcees and energy trading transactions scales up, a secure energy trading platform is required. To that end, the presented framework is integrated with a lightweight Blockchain implementation and smart contracts. Numerical tests are provided to showcase the overall implementation.
In this Perspective talk, I will explore how distributed ledger technology (DLT), often referred to as the Blockchain, can revolutionize the way we interact with data, can establish a network of trust amongst untrusting parties, and align incentives with sustainable practices. Recently, the UNFCCC has officially recognized the potential of DLT in fighting climate change. At the core of this technology is a distributed database that is continuously updated and verified by pre-defined algorithms run by the users. All data entering the distributed ledger (DL) is tamper-proof, chronological and distributed, and thus inherently durable, reliable, and secure. Additionally, the DL enables programmable (smart) contracts that self-execute and self-enforce based on captured data, preventing corruption and data manipulation. All machine-readable data can be stored and archived on a DL and used to validate claims. In a few years’ time, apps will make DLT feasible to use in most communities. Interesting use cases for the conservation of marine biodiversity include the transparent tracking of supply chains for fisheries, crowd-sourced reputation rankings for companies, automatic monetary incentives for measurable conservation actions in coastal communities, or secure and trustable peer-to-peer financing in underinvested areas, for example to develop resilient coastal social-ecological systems.
The Internet pervades many aspects of modern life offering up seemingly boundless opportunities to connect, inform and be informed. As the range and number of sources for information online explode, how people go about selecting and interpreting information has become a pertinent area for study, not least in the recent light of the prevalence of fake-news—as people are well known to act upon information they believe to be trustworthy. Where the decision to act incurs risk, an inability to accurately select and assess the credibility of information presents a challenge. <br/><br/>This extended abstract summarizes findings from a study of 57 Bitcoin users. Our analysis shows that this self-identifying technical and expert community was not significantly influenced by confirmation bias (a facet of fake-news). However, the same users also failed to demonstrate a true reliance upon the facts contained in news articles, often deferring trust to the source of the news which could still render them susceptible to fake-news, and, in turn, place their speculation of the crypto-currency at risk.
This research work aims to study the intrinsic characteristics of the most \nrepresentative virtual currency among all the existing cryptocurrencies in the market, \nBitcoin, considering it under two points of view: as a means of payment in the \nexchange of goods and services and as a financial or investment asset for \nspeculative purposes in the short and medium term. \nLikewise, reference will be made to the different regulatory flows in terms of their \nlegal nature and, in particular, to the tax treatment in the European Union, the United \nStates and other selected jurisdictions. \nThe ultimate goal of this research is to analyze the current deficiencies of the global \nlegal status of Bitcoin in order to carry out the corresponding recommendations that \nallow an approximation to the global control of taxation and consumer protection.
Se tratan algunas cuestiones clave que, desde la óptica legal, y en particular del derecho de la contratación, comienza a plantear en España la introducción y generalización en la práctica de sistemas de contratación electrónica fundados en la tecnología denominada de cadenas de bloques o registros distribuidos, y en el empleo de los llamados contratos inteligentes.
Abstract This paper outlines how the digital currency and network technology of bitcoin functions and explores the context from which it emerged. Bitcoin was conceived in 2008 as an attempt to alleviate trust in government and banks which was at a low during this period of financial crisis. However, with bitcoin trust does not dissipate, rather it shifts. Trust moves from trust in banks or states to trust in algorithms and encryption software. There is a move from conventional trust in the gold standard—“In Gold We Trust”—to the trust announced on U.S. currency—“In God We Trust”—to trust in software and networks—“In Digital We Trust”. The hyperbole of bitcoin discourse is deemed to be an expression of the Californian Ideology, which itself often conceals a right-wing agenda. The paper analyses the hype behind the celebration of decentralised digital networks. It proposes that a form of network fetishism operates here. The failure of bitcoin as a currency (rather than as a hoarded commodity in an emergent bubble) and as an idea might be attributed to the failure to see how ultra-modern digital networks conceal very traditional consolidation of power and capital. The rise and fall of bitcoin, in terms of its original ambition, serves as a cautionary tale in the digital age—it reveals how ingenious innovations that might challenge power and the consolidation of capital become co-opted and colonised by capital. Finally, the paper offers a discussion of the possible progressive uses of the digital technology bitcoin has facilitated.
Tin Leelavimolsilp, Long Tran-Thanh, Sebastian Stein
Eyal and Sirer's selfish mining strategy has demonstrated that Bitcoin system is not secure even if 50% of total mining power is held by altruistic miners. Since then, researchers have been investigating either to improve the efficiency of selfish mining, or how to defend against it, typically in a single selfish miner setting. Yet there is no research on a selfish mining strategies concurrently used by multiple miners in the system. The effectiveness of such selfish mining strategies and their required mining power under such multiple selfish miners setting remains unknown. In this paper, a preliminary investigation and our findings of selfish mining strategy used by multiple miners are reported. In addition, the conventional model of Bitcoin system is slightly redesigned to tackle its shortcoming: namely, a concurrency of individual mining processes. Although a theoretical analysis of selfish mining strategy under this setting is yet to be established, the current findings based on simulations is promising and of great interest. In particular, our work shows that a lower bound of power threshold required for selfish mining strategy decreases in proportion to a number of selfish miners. Moreover, there exist Nash equilibria where all selfish miners in the system do not change to an honest mining strategy and simultaneously earn their unfair amount of mining reward given that they equally possess sufficiently large mining power. Lastly, our new model yields a power threshold for mounting selfish mining strategy slightly greater than one from the conventional model.