The alleged undue influence of interest groups used to be and is one of the most critical problems in campaign and party financing in the United States and the Federal Republic. This chapter focuses on some issues which are debated vigorously in the United States and Germany. The party finance scandals in Germany have been about tax evasion, fraud, and in a very few instances corruption; they were not about illegally high amounts of donations. Corporate as well as union contributions are much more decentralized in the US than in Germany, paralleling the decentralized structure of American interest groups. In Germany public funding has been largely a reaction to increasing campaign costs. The party leadership in Germany should be made more accountable to the membership in financial matters. In both countries there is considerable suspicion that both candidates and parties depend financially on interest groups.
Alejandro Ranchal Pedrosa, Maria Potop-Butucaru, Sara Tucci-Piergiovanni
Bitcoin, the most popular blockchain system, does not scale even under very optimistic assumptions. Lightning networks, a layer on top of Bitcoin, composed of one-to-one lightning channels make it scale to up to 105 Million users. Recently, Duplex Micropayment Channel factories have been proposed based on opening multiple one-to-one payment channels at once. Duplex Micropayment Channel factories rely on time-locks to update and close their channels. This mechanism yields to situation where users funds time-locking for long periods increases with the lifetime of the factory and the number of users. This makes DMC factories not applicable in real-life scenarios.
Krishnendu Chatterjee, Amir Kafshdar Goharshady, Ehsan Kafshdar Goharshady
Smart contracts are programs that are stored and executed on the Blockchain and can receive, manage and transfer money (cryptocurrency units). Two important problems regarding smart contracts are formal analysis and compiler optimization. Formal analysis is extremely important, because smart contracts hold funds worth billions of dollars and their code is immutable after deployment. Hence, an undetected bug can cause significant financial losses. Compiler optimization is also crucial, because every action of a smart contract has to be executed by every node in the Blockchain network. Therefore, optimizations in compiling smart contracts can lead to significant savings in computation, time and energy.
The Physical Internet and hyperconnected logistics concepts promise an open, more efficient, and environmentally friendly supply chain for goods. Blockchain and Internet of Things (IoT) technologies are increasingly regarded as main enablers of improvements in this domain. We describe how blockchain and smart contracts present the potential of being applied to hyperconnected logistics by showing a concrete example of its implementation.
In this paper, we develop a more general framework of block-structured Markov processes in the queueing study of blockchain systems, which can provide analysis both for the stationary performance measures and for the sojourn time of any transaction or block. In addition, an original aim of this paper is to generalize the two-stage batch-service queueing model studied in Li et al. (Blockchain queue theory. In: International conference on computational social networks. Springer: New York; 2018 . p. 25–40) both “from exponential to phase-type” service times and “from Poisson to MAP” transaction arrivals. Note that the MAP transaction arrivals and the two stages of PH service times make our blockchain queue more suitable to various practical conditions of blockchain systems with crucial factors, for example, the mining processes, the block generations, the blockchain building and so forth. For such a more general blockchain queueing model, we focus on two basic research aspects: (1) using the matrix-geometric solution, we first obtain a sufficient stable condition of the blockchain system. Then, we provide simple expressions for the average stationary number of transactions in the queueing waiting room and the average stationary number of transactions in the block. (2) However, on comparing with Li et al. ( 2018 ), analysis of the transaction–confirmation time becomes very difficult and challenging due to the complicated blockchain structure. To overcome the difficulties, we develop a computational technique of the first passage times by means of both the PH distributions of infinite sizes and the RG factorizations. Finally, we hope that the methodology and results given in this paper will open a new avenue to queueing analysis of more general blockchain systems in practice and can motivate a series of promising future research on development of blockchain technologies.
Increased interest in scalable and high-throughput blockchains has led to an explosion in the number of committee selection methods in the literature. Committee selection mechanisms allow consensus protocols to safely select a committee, or a small subset of validators that is permitted to vote and verify a block of transactions, in a distributed ledger. There are many such mechanisms, each with substantially different methodologies and guarantees on communication complexity, resource usage, and fairness. In this paper, we illustrate that, despite these implementation-level differences, there are strong statistical similarities between committee selection mechanisms. We concretely show this by proving that the committee selection of the Avalanche consensus protocol can be used to choose committees in the Stellar Consensus Protocol that satisfy the necessary and sufficient conditions for Byzantine agreement. We also verify these claims using simulations and numerically observe sharp phase transitions as a function of protocol parameters. Our results suggest the existence of a "statistical taxonomy" of committee selection mechanisms in distributed consensus algorithms.
The development of technology has led to the creation of new phenomena in the financial world.One of these phenomena is crypt, digitally decentralized currencies created for the "world of
Cryptocurrencies are digital (virtual) currencies, which, although they are a means of payment, are not yet strictly regulated by law in most states, and in some, they are even prohibited.Many people, including IT professionals and programmers, do not know much about this topic, and the general public equates the terms blockade and bitcoin.The crypto-market today amounts to nearly $ 770 billion.Since the emergence of the first digital currencies to date, over 1,300 active crypto sites have appeared, which differ in their properties and uses.Before the bitcoin, there were a lot of unsuccessful attempts to create digital currencies (DigiCash, Hashcash, Facebook credit, etc.).Utopian idea that mathematics and physics can solve social problems began its life through the appearance of bitcoin.The genial idea on which is a bitcoin functioned is based on blockchain technology, whose potential reaches far
Muhammad Saad, Jeffrey Spaulding, Laurent Njilla, Charles Kamhoua · 7 authors
In this paper, we systematically explore the attack surface of the Blockchain technology, with an emphasis on public Blockchains. Towards this goal, we attribute attack viability in the attack surface to 1) the Blockchain cryptographic constructs, 2) the distributed architecture of the systems using Blockchain, and 3) the Blockchain application context. To each of those contributing factors, we outline several attacks, including selfish mining, the 51% attack, Domain Name System (DNS) attacks, distributed denial-of-service (DDoS) attacks, consensus delay (due to selfish behavior or distributed denial-of-service attacks), Blockchain forks, orphaned and stale blocks, block ingestion, wallet thefts, smart contract attacks, and privacy attacks. We also explore the causal relationships between these attacks to demonstrate how various attack vectors are connected to one another. A secondary contribution of this work is outlining effective defense measures taken by the Blockchain technology or proposed by researchers to mitigate the effects of these attacks and patch associated vulnerabilities
Much has been written about the likely impact of blockchain technology. Early scholarship on this topic has focused on the legal and financial implications of virtual currencies which is based on blockchain technology. Rapid introduction and diffusion of technological changes throughout society, such as blockchain, continue to exceed the ability of law and regulation to keep pace. Will blockchain prove as disruptive to business models and entrenched societal institutions as: electricity, radio, television, or the internet? What beneficial aspects of the blockchain have been identified thus far and what future applications are probable? Should we expect blockchain technology to result in massive global changes? The primary goal of this article about blockchain is to present an all-encompassing basic explanation of: what it is; how it works; and what it's important. This article contributes to the scholarly literature and our understanding by providing a cogent description of this important technology and look at potential uses.
Iain Barclay, Alun Preece, Ian Taylor, Dinesh Verma
Machine Learning systems rely on data for training, input and ongoing feedback and validation. Data in the field can come from varied sources, often anonymous or unknown to the ultimate users of the data. Whenever data is sourced and used, its consumers need assurance that the data accuracy is as described, that the data has been obtained legitimately, and they need to understand the terms under which the data is made available so that they can honour them. Similarly, suppliers of data require assurances that their data is being used legitimately by authorised parties, in accordance with their terms, and that usage is appropriately recompensed. Furthermore, both parties may want to agree on a specific set of quality of service (QoS) metrics, which can be used to negotiate service quality based on cost, and then receive affirmation that data is being supplied within those agreed QoS levels. Here we present a conceptual architecture which enables data sharing agreements to be encoded and computationally enforced, remuneration to be made when required, and a trusted audit trail to be produced for later analysis or reproduction of the environment. Our architecture uses blockchain-based distributed ledger technology, which can facilitate transactions in situations where parties do not have an established trust relationship or centralised command and control structures. We explore techniques to promote faith in the accuracy of the supplied data, and to let data users determine trade-offs between data quality and cost. Our system is exemplified through consideration of a case study using multiple data sources from different parties to monitor traffic levels in urban locations.
Nguyen B. Truong, Kai Sun, Gyu Myoung Lee, Yike Guo
The General Data Protection Regulation (GDPR) gives control of personal data back to the owners by appointing higher requirements and obligations on service providers who manage and process personal data. As the verification of GDPR-compliance, handled by a supervisory authority, is irregularly conducted; it is challenging to be certified that a service provider has been continuously adhering to the GDPR. Furthermore, it is beyond the data owner's capability to perceive whether a service provider complies with the GDPR and effectively protects her personal data. This motivates us to envision a design concept for developing a GDPR-compliant personal data management platform leveraging the emerging blockchain and smart contract technologies. The goals of the platform are to provide decentralised mechanisms to both service providers and data owners for processing personal data; meanwhile, empower data provenance and transparency by leveraging advanced features of the blockchain technology. The platform enables data owners to impose data usage consent, ensures only designated parties can process personal data, and logs all data activities in an immutable distributed ledger using smart contract and cryptography techniques. By honestly participating in the platform, a service provider can be endorsed by the blockchain network that it is fully GDPR-compliant; otherwise, any violation is immutably recorded and is easily figured out by associated parties. We then demonstrate the feasibility and efficiency of the proposed design concept by developing a profile management platform implemented on top of the Hyperledger Fabric permissioned blockchain framework, following by valuable analysis and discussion.
Compared to initial public offerings (IPOs) that are sales of company ownerships, and loans that are sales of debt claims, initial coin offerings (ICOs) are sales of promises of cryptocurrency appreciation. However, regulatory uncertainties continue to prohibit successful widespread adoption. This paper examines ICOs with varying levels of success, including Mastercoin (now Omni) and Kin, as well as fraudulent ICOs, like REcoin and OneCoin. The discussion of the benefits and flaws within the ICO market examines regulatory challenges concerning risks transferred to investors through information asymmetry, while questioning the ability of regulations to enhance investor protection mechanisms without undermining the fundamental value of cryptocurrencies and ICOs as a viable funding structure.
Globalization of IC supply chain has increased the risk of counterfeit, tampered, and re-packaged chips in the market. Counterfeit electronics poses a security risk in safety critical applications like avionics, SCADA systems, and defense. It also affects the reputation of legitimate suppliers and causes financial losses. Hence, it becomes necessary to develop traceability solutions to ensure the integrity of supply chain, from the time of fabrication to the end of product-life, which allows a customer to verify the provenance of a device or a system. In this article, we present an IC traceability solution based on blockchain. A blockchain is a public immutable database that maintains a continuously growing list of data records secured from tampering and revision. Over the lifetime of an IC, all ownership transfer information is recorded and archived in a blockchain. This safe, verifiable method prevents any party from altering or challenging the legitimacy of the information being exchanged. However, a chain of sales record is not enough to ensure provenance of an IC. There is a need for clone-proof method for securely binding the identity of an IC to the blockchain information. In this article, we propose a method of IC supply chain traceability via blockchain pegged to embedded physically unclonable function (PUF). The blockchain provides ownership transfer record, while the PUF provides unique identification for an IC allowing it to be linked uniquely to a blockchain. Our proposed solution automates hardware and software protocols using blockchain-powered Smart Contract that allows supply chain participants to authenticate, track, trace, analyze, and provision chips throughout their entire life cycle.
Open access
Physical Unclonable Functions (PUFs) and Hardware Security
Integrated Circuits and Semiconductor Failure Analysis
Construction customers want more complex facilities delivered faster and at a lower cost. Transaction costs account for a significant proportion of each new or refurbished facility (a 2017 report from the Infrastructure Client Group in the UK suggests as high as 50%), yet they contribute no value to the customer. Blockchain is being suggested as a way to reduce transaction costs by eliminating the need for intermediaries to build trust as a prerequisite for successfully executed agreements. This study first describes the thinking that underpins blockchain technology, outlining how it works, and the potential limitations of the technology. Second, using a case study, reviews the potential cost savings from the use of blockchain for a real estate company. The results reveal a potential cost savings from blockchain deployment at 8.3% of the total cost of residential construction, with a standard deviation of 1.26%. Third, we explore the implications, risks and applications of blockchain technology for improving flow in the end-to-end design and construction process and we identify opportunities for future research on blockchain applications in construction.
This paper seeks to discuss the application of AI in conjunction with blockchain technology to improve DAOs. Through the integration of AI, DAOs can be made self - governing to reduce the possibilities of human interference while at the same time enhancing efficiency in decision - making to make governance more secure and transparent. The combination of AI and blockchain technology has various prospects to revolutionize the decentralized structures of organizations and enhance better governance.
To participate in the distributed consensus of permissionless blockchains, prospective nodes -- or miners -- provide proof of designated, costly resources. However, in contrast to the intended decentralization, current data on blockchain mining unveils increased concentration of these resources in a few major entities, typically mining pools. To study strategic considerations in this setting, we employ the concept of Oceanic Games, Milnor and Shapley (1978). Oceanic Games have been used to analyze decision making in corporate settings with small numbers of dominant players (shareholders) and large numbers of individually insignificant players, the ocean. Unlike standard equilibrium models, they focus on measuring the value (or power) per entity and per unit of resource} in a given distribution of resources. These values are viewed as strategic components in coalition formations, mergers and resource acquisitions. Considering such issues relevant to blockchain governance and long-term sustainability, we adapt oceanic games to blockchain mining and illustrate the defined concepts via examples. The application of existing results reveals incentives for individual miners to merge in order to increase the value of their resources. This offers an alternative perspective to the observed centralization and concentration of mining power. Beyond numerical simulations, we use the model to identify issues relevant to the design of future cryptocurrencies and formulate prospective research questions.
Blockchain se ha convertido en una tecnología disruptiva que tiene la capacidad de transformar la industria agroalimentaria, puesto que promete resolver muchos problemas relacionados con la falta de confianza en la trazabilidad y el producto que adquieren los consumidores. Sin embargo, las partes implicadas en la cadena de suministro de productos agroalimentarios son numerosas y están físicamente dispersas, lo que dificulta el manejo de datos e información. Como resultado, el proceso de producción no es transparente y la confianza es difícil de construir.Para ser más exitosas en la economía globalizada actual, las cooperativas deben focalizarse en ofrecer mayor transparencia. Este documento propone un sistema de trazabilidad para una cooperativa agrícola basado en la tecnología blockchain, para resolver la crisis de confianza en la cadena de suministro de los productos agroalimentarios. La aplicación de técnicas de blockchain a la trazabilidad del producto agrario no solo amplía el dominio de la aplicación de la tecnología blockchain, sino que también apoya la generación de confianza entre los diferentes agentes de la cadena. Se exploran las posibles implicaciones del blockchain para los alimentos frescos mediante el desarrollo de una prueba de concepto (PoC) en el ámbito de la trazabilidad agroalimentaria, incorporando, además, la tecnología de los contratos inteligentes. Los hallazgos de la investigación contribuyen a una mejor comprensión de la tecnología blockchain para las diversas partes interesadas en la cadena de alimentos frescos, especialmente para las cooperativas, siendo una oportunidad para la mejora de la reputación y competitividad en una economía altamente globalizada.
With the development of the energy Internet and the integration of multi-type energy situations, it is of great significance to study the competition game of a multi-agent microgrid group system for its development. As an emerging distributed database technology, blockchain technology has great application potential in the field of energy trading. Firstly, blockchain technology is coupled with the microgrid group transaction, and the information flow transaction model of a microgrid group based on blockchain technology is established. Aiming at this complex multi-objective optimization problem, an improved ant colony optimization algorithm is proposed to solve the model. Finally, the competitive trading model and solving algorithm are simulated and analyzed. The relevant results show that the near global optimum price strategy of each time based on the proposed model can effectively balance the efficiency of each subject in the market. In addition, the model ensures that there is no high-income and low-cost phenomenon in the trading process, therefore the security and quality of the market are guaranteed.
Abrar O. Alkhamisi and Fathy Alboraei Abrar O. Alkhamisi and Fathy Alboraei
In recent years, the Internet of Things (IoT) plays a vital role in our daily activities .Owing to the increased number of vulnerabilities on the IoT devices, security becomes critical in the untrustworthy IoT environment. Access control is one of the top security concerns, however, implementing the traditional access control mechanisms in the resource-constrained nature of the IoT devices is a challenging task. With the emergence of blockchain technology, several recent research works have focused on the adoption of blockchain in IoT to resolve the security concerns. Despite, integrating the blockchain in the resource-constrained IoT context is difficult. To overcome these obstacles, the proposed work presents a privacy-aware IoT security architecture to ensure the access control based on Smart contract for resource-constrained and distributed IoT devices. The design of the proposed architecture incorporates three main components such as the contextual blockchain gateway, decentralized revocation manager, and non-interactive zero-knowledge proof based validation. By modeling the contextual blockchain gateway, the proposed architecture ensures the dynamic authentication and authorization based on the contextual information and access policies. Instead of integrating the blockchain technology into resource-constrained IoT devices, the smart contract-based distributed access control system with the contextual blockchain gateway provides the scalable solution. With the association of decentralized revocation manager in the smart contract, it prevents the resource access from the unauthorized users by dynamically generating and updating the revoked user list of all the nodes in the smart contract. Moreover, the proposed architecture employs the non-interactive zeroknowledge proof cryptographic protocol to ensure the transaction privacy within the smart contract. Consequently, it maintains the trade-off between the transparency and privacy while ensuring the security for the distributed IoT environment.
Given that there are both continuous and discontinuous components in the movement of asset prices, existing asset pricing models that assume only continuous price movements should be revised. In this paper, we explore the features of jumps, which are discontinuous movements, by examining Bitcoin pricing. First, we identify jumps in the Bitcoin price on a daily basis, applying a non-parametric methodology and then break down the Bitcoin total rate of return into a jump rate of return and a continuous rate of return. In our empirical analysis, price jumps turn out to be independent of volatility. Moreover, the jumps in the Bitcoin price do not appear at regular intervals; rather, they tend to be concentrated in clusters during special periods, implying that once an economic crisis occurs, the crisis will last for a long time due to contagion effects and the economy will take a considerable amount of time to recover fully. Further, the contribution of the jump rate of return to the total rate of return of the Bitcoin price is lower than the contribution of the continuous return, implying that the pursuit of sustainable returns rather than large but temporary returns will improve the total rate of return over the long term. Finally, more jumps are observed when trading volume is lower, implying that market illiquidity drives discontinuous movement in asset prices. Overall, the features of jump risk are like two sides of the same coin and jump risks are expected to have a significant effect on asset pricing, suggesting that consideration of jumps is essential for risk management as well as asset pricing.
Bitcoin is considered the most valuable currency in the world. Besides being highly valuable, its value has also experienced a steep increase, from around 1 dollar in 2010 to around 18000 in 2017. Then, in recent years, it has attracted considerable attention in a diverse set of fields, including economics and computer science. The former mainly focuses on studying how it affects the market, determining reasons behinds its price fluctuations, and predicting its future prices. The latter mainly focuses on its vulnerabilities, scalability, and other techno-crypto-economic issues. Here, we aim at revealing the usefulness of traditional autoregressive integrative moving average (ARIMA) model in predicting the future value of bitcoin by analyzing the price time series in a 3-years-long time period. On the one hand, our empirical studies reveal that this simple scheme is efficient in sub-periods in which the behavior of the time-series is almost unchanged, especially when it is used for short-term prediction, e.g. 1-day. On the other hand, when we try to train the ARIMA model to a 3-years-long period, during which the bitcoin price has experienced different behaviors, or when we try to use it for a long-term prediction, we observe that it introduces large prediction errors. Especially, the ARIMA model is unable to capture the sharp fluctuations in the price, e.g. the volatility at the end of 2017. Then, it calls for more features to be extracted and used along with the price for a more accurate prediction of the price. We have further investigated the bitcoin price prediction using an ARIMA model, trained over a large dataset, and a limited test window of the bitcoin price, with length $w$, as inputs. Our study sheds lights on the interaction of the prediction accuracy, choice of ($p,q,d$), and window size $w$.