Bitcoin is an online communication protocol, which facilitates electronic transactions. It has grabbed the attention of investors and researchers in the recent past. The non-regulatory feature of Bitcoin makes it riskier and the element of speculation in its trading is higher than any other financial asset. The study provides an insight into the price dynamics of Bitcoin by examining the day of the week and month of the year effect for the period 2013 to 2017. The findings of the study indicate the existence of seasonality in the return behaviour of Bitcoin as returns for Monday is higher than any other day of the week. Likewise, the returns earned during the month of November are significantly different from other months of the year. The results of the study assert a violation of the assumption of weak-form market efficiency and imply that the Bitcoin market provides an opportunity for the investors to exploit the market from its predictable behavior and fetch abnormal gains.
Background/Objectives: Ethereum is a next-generation blockchain developed in 2014 by Vitalik Buterin, a cryptocurrency that can implement various smart contracts. Methods/Statistical analysis: When making any contract on a blockchain, the miner is given the corresponding compensation, the block, which is obtained earlier than the hash of the set size by applying a random nonce value and hash algorithm according to the prop-off-work method. In the case of Ethereum, the ETH will be given to the miner who uses more gas in addition to the work proof method. Findings: In this case, if the malicious miner increases the amount of gas first, obtains the priority for block generation, intercepts the value derived by the general miner and sends it to the miner, the miner will give the block to the malicious miner. As such, miner, a problem that arises due to the nature of blockchain, analyzes the problem of relying on transaction order that gives the miner a block option to the miner who uses more gas and proposes a solution. Improvements/Applications: we described how to solve the problem of pre-sales in the blockchain with public key cryptography using confidentiality. It is hoped that this approach will be fairer and safer.
Smart grid adalah salah satu komponen dari smart city yang memperkenalkan komunikasi dua arah antara pelanggan dengan perusahaan penyedia listrik. Salah satu masalah yang dapat terjadi pada jaringan smart grid adalah data pelanggan yang jatuh ke pihak yang tidak bertanggungjawab karena saluran transmisi yang tidak aman. Oleh karena itu, penggunaan blockchain dan kriptografi dapat diterapkan pada jaringan smart grid untuk menyelesaikan masalah tersebut. Blockchain memberikan keamanan tambahan untuk penyimpanan data pada pusat pengatur jaringan dan kriptografi memberikan kerahasiaan dan autentikasi pada pertukaran data dalam jaringan. Sistem yang baru diciptakan ini harus bisa menyesuaikan frekuensi pengambilan data pada jaringan smart grid. Penelitian ini bertujuan untuk mengetahui waktu komputasi yang dibutuhkan dari kedua proses tersebut dengan menyusun suatu simulasi jaringan smart grid. Simulasi dalam penelitian ini dilakukan dengan menggunakan aplikasi MATLAB dan tersusun dari dua program utama, yaitu program kriptografi menggunakan algoritma RSA dan program pembuatan blockchain sederhana. Hasil yang didapatkan menunjukkan bahwa rentang waktu komputasi RSA pada suatu jaringan smart grid lebih cepat dari frekuensi pengambilan data yang ditentukan, yaitu sebesar satu menit. Sementara itu, rentang waktu penyusunan blockchain dengan ketentuan tertentu tidak dapat memenuhi persyaratan yang sama.
Rhythm Dungeon is a rhythm game which leverages the blockchain as a shared open database. During the gaming session, the player explores a roguelike dungeon by inputting specific sequences in time to music rhythm. By integrating smart contract to the game program, the enemies through the venture are generated from other games which share the identical blockchain. On the other hand, the player may upload their characters at the end of their journey, so that their own character may appear in other games and make an influence. Rhythm Dungeon is designed and implemented to show the potential of decentralized gaming experience, which utilizes the blockchain to provide asynchronous interactions among massive players.
Michael Fröwis, Thilo Gottschalk, Bernhard Haslhofer, Christian Rückert · 5 authors
Analyzing cryptocurrency payment flows has become a key forensic method in law enforcement and is nowadays used to investigate a wide spectrum of criminal activities. However, despite its widespread adoption, the evidential value of obtained findings in court is still largely unclear. In this paper, we focus on the key ingredients of modern cryptocurrency analytics techniques, which are clustering heuristics and attribution tags. We identify internationally accepted standards and rules for substantiating suspicions and providing evidence in court and project them onto current cryptocurrency forensics practices. By providing an empirical analysis of CoinJoin transactions, we illustrate possible sources of misinterpretation in algorithmic clustering heuristics. Eventually, we derive a set of legal key requirements and translate them into a technical data sharing framework that fosters compliance with existing legal and technical standards in the realm of cryptocurrency forensics. Integrating the proposed framework in modern cryptocurrency analytics tools could allow more efficient and effective investigations, while safeguarding the evidential value of the analysis and the fundamental rights of affected persons.
Data integration and fast effective data processing are the primary challenges in today’s high-performance computing systems used for Big Data processing and analysis in practical scenarios. Blockchain (BC) is a hot, modern technology that ensures high security of data processes stored in highly distributed networks and ICT infrastructures. BC enables secure data transfers in distributed systems without the need for all operations and processes in the network to be initiated and monitored by any central authority (system manager). This paper presents the background of a generic architectural model of a BC system and explains the concept behind the consensus models used in BC transactions. Security is the main aspect of all defined operations and BC nodes. The paper presents also specific BC use cases to illustrate the performance of the system in practical scenarios..
Michael Fröwis, Thilo Gottschalk, Bernhard Haslhofer, Christian Rückert · 5 authors
Analyzing cryptocurrency payment flows has become a key forensic method in\nlaw enforcement and is nowadays used to investigate a wide spectrum of criminal\nactivities. However, despite its widespread adoption, the evidential value of\nobtained findings in court is still largely unclear. In this paper, we focus on\nthe key ingredients of modern cryptocurrency analytics techniques, which are\nclustering heuristics and attribution tags. We identify internationally\naccepted standards and rules for substantiating suspicions and providing\nevidence in court and project them onto current cryptocurrency forensics\npractices. By providing an empirical analysis of CoinJoin transactions, we\nillustrate possible sources of misinterpretation in algorithmic clustering\nheuristics. Eventually, we derive a set of legal key requirements and translate\nthem into a technical data sharing framework that fosters compliance with\nexisting legal and technical standards in the realm of cryptocurrency\nforensics. Integrating the proposed framework in modern cryptocurrency\nanalytics tools could allow more efficient and effective investigations, while\nsafeguarding the evidential value of the analysis and the fundamental rights of\naffected persons.\n
Full nodes, which synchronize the entire blockchain history and independently validate all the blocks, form the backbone of any blockchain network by playing a vital role in ensuring security properties. On the other hand, a user running a full node needs to pay a heavy price in terms of storage costs. E.g., the Bitcoin blockchain size has grown over 215GB, in spite of its low throughput. The ledger size for a high throughput blockchain Ripple has already reached 9TB, and it is growing at an astonishing rate of 12GB per day! In this paper, we propose an architecture based on 'fountain codes', a class of erasure codes, that enables any full node to 'encode' validated blocks into a small number of 'coded blocks', thereby reducing its storage costs by orders of magnitude. In particular, our proposed "Secure Fountain (SeF)" architecture can achieve a near-optimal trade-off between the storage savings per node and the 'bootstrap cost' in terms of the number of (honest) storage-constrained nodes a new node needs to contact to recover the blockchain. A key technical innovation in SeF codes is to make fountain codes secure against adversarial nodes that can provide maliciously formed coded blocks. Our idea is to use the header-chain as a 'side-information' to check whether a coded block is maliciously formed while it is getting decoded. Further, the 'rateless property' of fountain codes helps in achieving high decentralization and scalability. Our experiments demonstrate that SeF codes tuned to achieve 1000x storage savings enable full nodes to encode the 191GB Bitcoin blockchain into 195MB on average. A new node can recover the blockchain from an arbitrary set of storage-constrained nodes as long as the set contains ~1100 honest nodes on average. Note that for a 1000x storage savings, the fundamental bound on the number of honest nodes to contact is 1000: we need about 10% more in practice.
Predicting the trends in Bitcoin market prices is a very challenging task due to the many uncertainties and variables influencing the market value. The market is susceptible to quick changes, causing seemingly random fluctuations in the Bitcoin price. Due to the chaotic and highly volatile nature of Bitcoin behavior, investments come with high risk. To minimize the risk involved, knowledge of the Bitcoin price movement in the future is desirable. Different studies have shown that Machine Learning algorithms can predict, to varying degrees, the price fluctuations of Bitcoin. However, most researches do not explore the relationship between the price and other features outside the transaction network, such as market capitalization, Bitcoin mining speed, or entity behavior. Also, most of the features are extracted from the network level, which means obtaining the number of transactions, users, Bitcoins mined, etc. In this research, we focus on additional features, such as features outside the transaction network and node-based features inside the transaction network, which could improve the price prediction of Bitcoin. The investigated features are the “fairness and goodness” measure and the “1-ARW-betweenness cen- trality” measure. Fairness and goodness are entity behavior measures. The goodness of a Bitcoin address captures how much this address is liked/trusted by other addresses, while the fairness of a Bitcoin address captures how fair the address is in rating other addresses’ likeability or trust level. The 1-ARW-betweenness centrality is a feature based on absorbing random walks. The feature captures the extent to which a Bitcoin address has control over the money flow between different addresses. A benchmark, based on the machine learning algorithm Random Forest with commonly used features, is used to test the impact of the additional features. The Random Forest tries to predict the sign (up-down movement) of the price per day, using data from the two previous days. Comparing this benchmark with a similar model, but then including the additional features, will gain more information about how these additional features influence the Bitcoin price.
The Sybil attack plagues all peer-to-peer systems, and modern open distributed ledgers employ a number of tactics to prevent it from proof of work, or other resources such as space, stake or memory, to traditional admission control in permissioned settings. With SybilQuorum we propose an alternative approach to securing an open distributed ledger against Sybil attacks, and ensuring consensus amongst honest participants, leveraging social network based Sybil defences. We show how nodes expressing their trust relationships through the ledger can bootstrap and operate a value system, and general transaction system, and how Sybil attacks are thwarted. We empirically evaluate our system as a secure Federated Byzantine Agreement System, and extend the theory of those systems to do so.
Are cryptocurrency traders driven by a desire to invest in a new asset class to diversify their portfolio or are they merely seeking to increase their levels of risk? To answer this question, we use individual-level brokerage data and study their behavior in stock trading around the time they engage in their first cryptocurrency trade. We find that when engaging in cryptocurrency trading investors simultaneously increase their risk-seeking behavior in stock trading as they increase their trading intensity and use of leverage. The increase in risk-seeking in stocks is particularly pronounced when volatility in cryptocurrency returns is low, suggesting that their overall behavior is driven by excitement-seeking.
Cryptocurrencies and blockchain networks have attracted tremendous attention from their volatile price movements and the promise of decentralization. However, most projects run on business narratives with no way to test and verify their assumptions and promises about the future. The complex nature of system dynamics within networked economies has rendered it difficult to reason about the growth and evolution of these networks. This paper drew concepts from differential games, classical control engineering, and stochastic dynamical system to come up with a framework and example to model, simulate, and engineer networked token economies. A model on a generalized token economy is proposed where miners provide service to a platform in exchange for a cryptocurrency and users consume service from the platform. Simulations of this model allow us to observe outcomes of complex dynamics and reason about the evolution of the system. Speculative price movements and engineered block rewards were then experimented to observe their impact on system dynamics and network-level goals. The model presented is necessarily limited so we conclude by exploring those limitations and outlining future research directions.
Volkan Dedeoglu, Raja Jurdak, Guntur D. Putra, Ali Dorri · 5 authors
Blockchain is a promising technology for establishing trust in IoT networks, where network nodes do not necessarily trust each other. Cryptographic hash links and distributed consensus mechanisms ensure that the data stored on an immutable blockchain can not be altered or deleted. However, blockchain mechanisms do not guarantee the trustworthiness of data at the origin. We propose a layered architecture for improving the end-to-end trust that can be applied to a diverse range of blockchain-based IoT applications. Our architecture evaluates the trustworthiness of sensor observations at the data layer and adapts block verification at the blockchain layer through the proposed data trust and gateway reputation modules. We present the performance evaluation of the data trust module using a simulated indoor target localization and the gateway reputation module using an end-to-end blockchain implementation, together with a qualitative security analysis for the architecture.
Summary Contemporary blockchain such as Bitcoin and Ethereum execute transactions serially by miners and validators and determine the Proof‐of‐Work (PoW). Such serial execution is unable to exploit modern multi‐core resources efficiently, hence limiting the system throughput and increasing the transaction acceptance latency. The objective of this work is to increase the transaction throughput by introducing parallel transaction execution using a static analysis over the transaction dependencies. We propose the DiPETrans framework for distributed execution of transactions in a block. Here, peers in the blockchain network form a community of trusted nodes to execute the transactions and find the PoW in‐parallel, using a leader–follower approach. During mining, the leader statically analyzes the transactions, creates different groups (shards) of independent transactions, and distributes them to followers to execute concurrently. After execution, the community's compute power is utilized to solve the PoW concurrently. When a block is successfully created, the leader broadcasts the proposed block to other peers in the network for validation. On receiving a block, the validators re‐execute the block transactions and accept the block if they reach the same state as shared by the miner. Validation can also be done in parallel, following the same leader–follower approach as mining. We report experiments using over 5 million real transactions from the Ethereum blockchain and execute them using our DiPETrans framework to empirically validate the benefits of our techniques over a traditional sequential execution. We achieve a maximum speedup of 2.2 and 2.0 and an average speedup of 1.6 and 1.5 for the miner and the validator, respectively, with 100–500 transactions per block when using 6 machines in the community. Further, we achieve a peak of 5 end‐to‐end block creation speedup using a parallel miner over a serial miner.
Christian Gorenflo, Lukasz Golab, Srinivasan Keshav
Performance and scalability are major concerns for blockchains: permissionless systems are typically limited by slow proof of X consensus algorithms and sequential post-order transaction execution on every node of the network. By introducing a small amount of trust in their participants, permissioned blockchain systems such as Hyperledger Fabric can benefit from more efficient consensus algorithms and make use of parallel pre-order execution on a subset of network nodes. Fabric, in particular, has been shown to handle tens of thousands of transactions per second. However, this performance is only achievable for contention-free transaction workloads. If many transactions compete for a small set of hot keys in the world state, the effective throughput drops drastically. We therefore propose XOX: a novel two-pronged transaction execution approach that both minimizes invalid transactions in the Fabric blockchain and maximizes concurrent execution. Our approach additionally prevents unintentional denial of service attacks by clients re-submitting conflicting transactions. Even under fully contentious workloads, XOX can handle more than 3000 transactions per second, all of which would be discarded by regular Fabric.
Federated identity management enables users to access multiple systems using a single login credential. However, to achieve this a complex privacy compromising authentication has to occur between the user, relying party (RP) (e.g., a business), and a credential service provider (CSP) that performs the authentication. In this work, we use a smart contract on a blockchain to enable an architecture where authentication no longer involves the CSP. Authentication is performed solely through user to RP communications (eliminating fees and enhancing privacy). No third party needs to be contacted, not even the smart contract. No public key infrastructure (PKI) needs to be maintained. And no revocation lists need to be checked. In contrast to competing smart contract approaches, ours is hierarchically managed (like a PKI) enabling better validation of attribute providers and making it more useful for large entities to provide identity services for their constituents (e.g., a government) while still enabling users to maintain a level of self-sovereignty.
Blockchain based cryptocurrencies are usually unmanaged, distributed, consensus-based systems in which no single entity has control. Managed cryptocurrencies can be implemented using private blockchains but are fundamentally different as the owners have complete control to do arbitrary activity without transparency (since they control the mining). In this work we explore a hybrid approach where a managed cryptocurrency is maintained through distributed consensus based methods. The currency administrator can perform ongoing management functions while the consensus methods enforce the rules of the cryptocurrency and provide transparency for all management actions. This enables the introduction of money management features common in fiat currencies but where the managing entity cannot perform arbitrary actions and transparency is enforced. We thus eliminate the need for users to trust the currency administrator but also to enable the administrator to manage the cryptocurrency. We demonstrate how to implement our approach through modest modifications to the implicit Bitcoin specification, however, our approach can be applied to most any blockchain based cryptocurrency using a variety of consensus methods.
This paper looks at the development of blockchain technologies that promise to bring new tools for the management of private data, providing enhanced security and privacy to individuals. Particular interest presents solutions aimed at reorganizing data flows in the Internet of Things (IoT) architectures, enabling the secure and decentralized exchange of data between network participants. However, as this paper argues, the promised benefits are counterbalanced by a significant shift towards the propertization of private data, underlying these proposals. Considering the unique capacity of blockchain technology applications to imitate and even replace traditional institutions, this aspect may present certain challenges, both of technical and ethical character. In order to highlight these challenges and associated concerns, this paper identifies the underlying techno-economic factors and normative assumptions defining the development of these solutions amounting to technologically enabled propertization. It is argued that without careful consideration of a wider impact, such blockchain applications could have effects opposite to the intended ones, thus contributing to the erosion of privacy for IoT users.
En este artículo se estima la distribución multivariada para analizar la dependencia del Bitcoin (BTC), Ripple (XRP) y Ether (ETH). Se utiliza la familia Hiperbólica Generalizada de distribuciones (GH) y en particular la distribución Varianza Gamma. El procedimiento para la estimación de los parámetros de la GH es a través del algoritmo EM (Expectation-Maximization). Los resultados muestran que existe una dependencia positiva entre los tres tipos de cambio respecto del dólar americano y se estima una distribución Varianza-Gamma de dimensión tres. Esta distribución es muy flexible para el ajuste de series de los rendimientos con leptocurtosis y sesgo. Esta información se considera importante para los inversionistas que conforman sus portafolios de una manera eficiente.
Yang Zhao, Jun Zhao, Linshan Jiang, Rui Tan · 5 authors
Internet-of-Things (IoT) companies strive to get feedback from users to improve their products and services. However, traditional surveys cannot reflect the actual conditions of customers' due to the limited questions. Besides, survey results are affected by various subjective factors. In contrast, the recorded usages of IoT devices reflect customers' behaviours more comprehensively and accurately. We design an intelligent system to help IoT device manufacturers to take advantage of customers' data and build a machine learning model to predict customers' requirements and possible consumption behaviours with federated learning (FL) technology. The FL consists of two stages: in the first stage, customers train the initial model using the phone and the edge computing server collaboratively. The mobile edge computing server's high computation power can assist customers' training locally. Customers first collect data from various IoT devices using phones, and then download and train the initial model with their data. During the training, customers first extract features using their mobiles, and then add the Laplacian noise to the extracted features based on differential privacy, a formal and popular notion to quantify privacy. After achieving the local model, customers sign on their models respectively and send them to the blockchain. We use the blockchain to replace the centralized aggregator which belongs to the third party in FL. In the second stage, miners calculate the averaged model using the collected models sent from customers. By the end of the crowdsourcing job, one of the miners, who is selected as the temporary leader, uploads the model to the blockchain. Besides, to attract more customers to participate in the crowdsourcing FL, we design an incentive mechanism, which awards participants with coins that can be used to purchase other services provided by the company.
Zhen Liu, Lijun Jiang, Mohamed Osmani, Peter Demian
At present, sustainable design is experiencing energy consumption and cost-effectiveness challenges in the building industry. A recent body of literature argues that the development of emerging smart digital technologies, such as Building Information Management (BIM) and blockchain (BC), offer immediate benefits to the industry. However, the current application of BIM and BC in the sustainable design and construction process focuses on smart energy and construction management, with little attention to addressing challenges for applying BIM to sustainable design and proposing strategies in terms of the usability of these technologies in the management of building construction projects. Therefore, this paper sets out to explore the potential roles of an integrated BIM and BC approach for sustainable building design information management. The first attempt is presented to use BC aided BIM for sustainable building design coordination and collaboration in multiple building stages. BC has the potential to address challenges that hinder the industry from using BIM for sustainable design, which has been unearthed. An innovative BC enhanced transaction process in BIM is required for sustainable building development. Roles of a user level driven smart contract system of BC can be used to enhance BIM system in the sustainable buildings process. The role of BC is primarily at user level driven smart contracts and their record value exchange capabilities. A user level (BIM stakeholders) driven BC technology for transaction in BIM process flow is revealed, and the user level (sustainable building design project stakeholders/BIM clients) driven and the smart contract enabled BIM+ BC architecture to address challenges of BIM for sustainable design has been further circulated according to the literature. Subsequently, a conceptual architecture of BIM + BC for Sustainable Building Design Information Management Framework in building project management has been proposed, validated, and refined. The Framework has two level encompassing structures and flow. The high-level framework is focused on strategy, whilst the low-level framework demonstrates technical components in detail. This architecture supporting project stakeholders in managing information, has the potential to achieve and ensure the realization of sustainable design goals through the interactive realization of smart contracts integrated into the user level driven BIM + BC system and its recording value exchange function through three user-driven levels, namely user, system, and transaction.
The aim of this study is to focus on fiscal decentralization and regional financial autonomy in Slovakia. The public administration reform and fiscal decentralization process in Slovakia ought to increase the autonomy of the multi-level governance and to decrease its dependency on state budgeting and other transfers. We argue that regional territorial governance is greatly dependent on financial incentives from central state financing, which limits the expected effect of decentralization and regional fiscal autonomy. By collecting quantitative data on state transfers and revenues to regional governments we demonstrate the limits of spatial, financial and decision-making autonomy within particular regions. The selected time frame 2005-2016 reflects all stages, reforms and changes in the fiscal decentralization of the second level governance in Slovakia.
Federated identity management enables users to access multiple systems using\na single login credential. However, to achieve this a complex privacy\ncompromising authentication has to occur between the user, relying party (RP)\n(e.g., a business), and a credential service provider (CSP) that performs the\nauthentication. In this work, we use a smart contract on a blockchain to enable\nan architecture where authentication no longer involves the CSP. Authentication\nis performed solely through user to RP communications (eliminating fees and\nenhancing privacy). No third party needs to be contacted, not even the smart\ncontract. No public key infrastructure (PKI) needs to be maintained. And no\nrevocation lists need to be checked. In contrast to competing smart contract\napproaches, ours is hierarchically managed (like a PKI) enabling better\nvalidation of attribute providers and making it more useful for large entities\nto provide identity services for their constituents (e.g., a government) while\nstill enabling users to maintain a level of self-sovereignty.\n
Smart contracts built in the blockchain are quietly revolutionizing traditional transactions despite their questionable status under current law. At the same time, disputes regarding smart contracts are inevitable, and par-ties will need means for dealing with smart contract issues. This Article tackles this challenge, and proposes that parties turn to online dispute resolution (“ODR”) to efficiently and fairly resolve smart contract disputes. Furthermore, the Article acknowledges the benefits and challenges of current blockchain ODR start-ups, and proposes specific ideas for how designers could address those challenges and incorporate ODR to provide just resolutions that will not stymie efficiencies of smart contracts. Nonetheless, the Article also raises pivotal cautions and questions for ensuring the fairness and transparency of these solutions over the longer term.