Bitcoin has recently received a lot of attention from the media and the public due to its recent price surge and crash. Correspondingly, many researchers have investigated various factors that affect the Bitcoin price and the patterns behind its fluctuations, in particular, using various machine learning methods. In this paper, we study and compare various state-of-the-art deep learning methods such as a deep neural network (DNN), a long short-term memory (LSTM) model, a convolutional neural network, a deep residual network, and their combinations for Bitcoin price prediction. Experimental results showed that although LSTM-based prediction models slightly outperformed the other prediction models for Bitcoin price prediction (regression), DNN-based models performed the best for price ups and downs prediction (classification). In addition, a simple profitability analysis showed that classification models were more effective than regression models for algorithmic trading. Overall, the performances of the proposed deep learning-based prediction models were comparable.
João Amaral Santos, Pedro R. M. Inácio, Bruno M. Silva
With the advent of Bitcoin and blockchain, the growth and adaptation of cryptographic features and capabilities were quickly extended to new and underexplored areas, such as healthcare. Currently, blockchain is being implemented mainly as a mechanism to secure Electronic Health Records (EHRs). However, new studies have shown that this technology can be a powerful tool in empowering patients to control their own health data, as well for enabling a fool-proof health data history and establishing medical responsibility. With the advent of mobile health (m-Health) sustained on service-oriented architectures, the adaptation of blockchain mechanisms into m-Health applications creates the possibility for a more decentralized and available healthcare service. Hence, this paper presents a review of the current security best practices for m-Health including blockchain technologies in healthcare. Moreover, it discusses and elaborates on identified open-issues and potentialities regarding the uses of Blockchain. Finally, the paper proposes conceptual solutions for future blockchain implementations for m-Health Services and Applications.
Conventional financial models fail to explain the economic and monetary properties of cryptocurrencies due to the latter's dual nature: their usage as financial assets on the one side and their tight connection to the underlying blockchain structure on the other. In an effort to examine both components via a unified approach, we apply a recently developed Non-Homogeneous Hidden Markov (NHHM) model with an extended set of financial and blockchain specific covariates on the Bitcoin (BTC) and Ether (ETH) price data. Based on the observable series, the NHHM model offers a novel perspective on the underlying microstructure of the cryptocurrency market and provides insight on unobservable parameters such as the behavior of investors, traders and miners. The algorithm identifies two alternating periods (hidden states) of inherently different activity -- fundamental versus uninformed or noise traders -- in the Bitcoin ecosystem and unveils differences in both the short/long run dynamics and in the financial characteristics of the two states, such as significant explanatory variables, extreme events and varying series autocorrelation. In a somewhat unexpected result, the Bitcoin and Ether markets are found to be influenced by markedly distinct indicators despite their perceived correlation. The current approach backs earlier findings that cryptocurrencies are unlike any conventional financial asset and makes a first step towards understanding cryptocurrency markets via a more comprehensive lens.
Chia Yen Tan, You Beng Koh, Kok Haur Ng, Kooi Huat Ng
Motivated by the large frequent price fluctuation and excessive volatility observed in the cryptocurrency market, this study adopts Bai and Perron’s structural change model by incorporating the trading volume and autoregressive variables to examine the number and location of change points in daily closing price, return and volatility proxied by the squared return of Cryptocurrency Index, Cryptocurrency Index 30, and the top 10 cryptocurrencies ranked according to market capitalisation. Results show that the structural changes occur very frequently for the price series, followed by squared return and return series which were consistently observed between December 2017 to April 2018. In addition, the results also reveal that the two cryptocurrency indices may not be beneficial as an indicator to reflect the whole cryptocurrency market for the entire studied period as these two indices do not display consistent structural change in contrast to the top 10 cryptocurrencies that might have significant implications for modelling the cryptocurrency data.
Israel Barrutia Barreto, José Antonio Urquizo Maggia, Samuel Isaías Acevedo Torres
La pobreza en América Latina y el Caribe sigue siendo un problema sin aparente solución. Se propone en este artículo el uso de las criptomonedas y la tecnología de blockchain como una herramienta para reducir la pobreza en la región mediante actividades económicas provenientes del turismo. Para ello se efectuó un análisis detallado de las potencialidades que recogen en conjunto el turismo, las criptomonedas y la tecnología blockchain. Dada las capacidades turísticas de las regiones latinoamericana y caribeña se debe concretar un conjunto de esfuerzos por parte de los gobiernos y empresas privadas en implementar el desarrollo turístico en regiones y localidades con gran biodiversidad y recursos naturales y culturales aún sin explorar. La relativa facilidad de acceso a cuentas bitcoin mediante teléfonos inteligentes hace que las transacciones financieras mediante criptomonedas se encuentran al alcance pequeños comerciantes que, normalmente, no tienen acceso a cuentas bancarias tradicionales. Por otro lado debe fortalecerse aún más el acceso a internet vía telefonía móvil para facilitar los sistemas de pago y para que las tecnologías basadas en blockchain puedan desarrollarse a su máxima capacidad. Se concluye que para lograr una significativa reducción de la pobreza es necesario la confluencia de una adecuada regulación de las criptomonedas por parte de los Gobiernos así como también el desarrollo una infraestructura adecuada que permita la creación y/o recuperación de microempresas potenciadas por la “Oferta Inicial de Monedas”.
There is a preconception that a blockchain needs consensus. But consensus is a powerful distributed property with a remarkably high price tag. So one may wonder whether consensus is at all needed.
We introduce a new blockchain architecture called ABC that functions despite not establishing consensus, and comes with an array of advantages: ABC is permissionless, deterministic, and resilient to complete asynchrony. ABC features finality and does not rely on costly proof-of-work.
Without establishing consensus, ABC cannot support certain applications, in particular smart contracts that are open for interaction with unknown agents. However, our system is an advantageous solution for many important use cases, such as cryptocurrencies like Bitcoin.
Madalina-Mihaela Buzau, Javier Tejedor-Aguilera, Pedro Cruz-Romero, Antonio Gómez‐Expósito
Non-technical losses (NTL) in electricity utilities are responsible for major revenue losses. In this paper, we propose a novel end-to-end solution to self-learn the features for detecting anomalies and frauds in smart meters using a hybrid deep neural network. The network is fed with simple raw data, removing the need of handcrafted feature engineering. The proposed architecture consists of a long short-term memory network and a multi-layer perceptrons network. The first network analyses the raw daily energy consumption history whilst the second one integrates non-sequential data such as its contracted power or geographical information. The results show that the hybrid neural network significantly outperforms state-of-the-art classifiers as well as previous deep learning models used in NTL detection. The model has been trained and tested with real smart meter data of Endesa, the largest electricity utility in Spain.
We introduce a new permissionless blockchain architecture called ABC. ABC is completely asynchronous, and does rely on neither randomness nor proof-of-work. ABC can be parallelized, and transactions have finality within one round trip of communication. However, ABC satisfies only a relaxed form of consensus by introducing a weaker termination property. Without full consensus, ABC cannot support certain applications, in particular ABC cannot support general smart contracts. However, many important applications do not need general smart contracts, and ABC is a better solution for these applications. In particular, ABC can implement the functionality of a cryptocurrency like Bitcoin, replacing Bitcoin's energy-hungry proof-of-work with a proof-of-stake validation.
A blockchain and smart contract enabled security mechanism for IoT applications has been reported recently for urban, financial, and network services. However, due to the power-intensive and a low-throughput consensus mechanism in existing blockchain, like Bitcoin and Ethereum, there are still challenges in integrating blockchain technology into resource-constrained IoT platforms. In this paper, Microchain, based on a hybrid Proof-of-Credit (PoC)-Voting-based Chain Finality (VCF) consensus protocol, is proposed to provide a secure, scalable and lightweight distributed ledger for IoT systems. By using a bias-resistant randomness protocol and a cryptographic sortition algorithm, a random subset of nodes are selected as a final committee to perform the consensus protocol. The hybrid consensus mechanism relies on PoC, a pure Proof of stake (PoS) protocol, to determine whether or not a participant is qualified to propose a block, given a fair initial distribution of the credit assignment. The voting-based chain finality protocol is responsible for finalizing a history of blocks by resolving conflicting checkpoint and selecting a unique chain. A proof-of-conception prototype is implemented and tested on a physical network environment. The experimental results verify that the Micorchain is able to offer a partially decentralized, scalable and lightweight distributed ledger protocol for IoT applications.
Proof-of-work blockchains reward each miner for one completed block by an amount that is, in expectation, proportional to the number of hashes the miner contributed to the mining of the block. Is this proportional allocation rule optimal? And in what sense? And what other rules are possible? In particular, what are the desirable properties that any "good" allocation rule should satisfy? To answer these questions, we embark on an axiomatic theory of incentives in proof-of-work blockchains at the time scale of a single block. We consider desirable properties of allocation rules including: symmetry; budget balance (weak or strong); sybil-proofness; and various grades of collusion-proofness. We show that Bitcoin's proportional allocation rule is the unique allocation rule satisfying a certain system of properties, but this does not hold for slightly weaker sets of properties, or when the miners are not risk-neutral. We also point out that a rich class of allocation rules can be approximately implemented in a proof-of-work blockchain.
IoT systems have enabled ubiquitous communication in physical spaces, making them smart Nowadays, there is an emerging concern about evaluating suspicious transactions in smart spaces. Suspicious transactions might have a logical structure, but they are not correct under the present contextual information of smart spaces. This research reviews suspicious transactions in smart spaces and evaluates the characteristics of blockchain technology to manage them. Additionally, this research presents a blockchain-based system model with the novel idea of iContracts (interactive contracts) to enable contextual evaluation through proof-of-provenance to detect suspicious transactions in smart spaces.
Public software repositories such as GitHub make transparent the development history of an open source software system. Source code commits, discussions about new features and bugs, and code reviews are stored and carefully attributed to the appropriate developers. However, sometimes governments may seek to analyze these repositories, to identify citizens who contribute to projects they disapprove of, such as those involving cryptography or social media. While developers who seek anonymity may contribute under assumed identities, their body of public work may be characteristic enough to betray who they really are. The ability to contribute anonymously to public bodies of knowledge is extremely important to the future of technological and intellectual freedoms. Just as in security hacking, the only way to protect vulnerable individuals is by demonstrating the means and strength of available attacks so that those concerned may know of the need and develop the means to protect themselves. \n \nIn this work, we present a method to de-anonymize source code contributors based on the authors' intrinsic programming style. First, we present a partial replication study wherein we attempt to de-anonymize a large number of entries into the Google Code Jam competition. We base our approach on Caliskan-Islam et al. 2015, but with modifications to the feature set and modelling strategy for scalability and feature-selection robustness. We did not achieve 0.98 F1 achieved in this prior work, but managed a still reasonable 0.71 F1 under identical experimental conditions, and a 0.88 F1 given more data from the same set. \n \nSecond, we present an exploratory study focused on de-anonymizing programmers who have contributed to a repository, using other commits from the same repository as training data. We train random-forest classifiers using programmer data collected from 37 medium to large open-source repositories. Given a choice between active developers in a project, we were able to correctly determine authorship of a given function about 75% of the time, without the use of identifying meta-data or comments. We were also able to correctly validate a contributor as the author of a questioned function with 80\\% recall and 65\\% precision. This exploratory study provides empirical support for our approach. \n \nFinally, we present the results of a similar, but more difficult study wherein we attempt de-anonymize a repository in the same manner, but without using the target repository as training data. To do this, we gather as much training data as possible from the repository's contributors through the Github API. We evaluate our technique over 3 repositories: Bitcoin, Ethereum (crypto-currencies) and TrinityCore (a game engine). Our results in this experiment starkly contrast our results in the intra-repository study showing accuracies of 35% for Bitcoin, 22% for Ethereum, and 21% for TrinityCore which had candidate set sizes of 6, 5, and 7 respectively. \n \nOur results indicate that we can do somewhat better than random guessing, even under difficult experimental conditions, but they also indicate some fundamental issues with the state of the art of Code Stylometry. In this work we present our methodology, results, and some comments on past empirical studies, the difficulties we faced, and likely hurdles for future work in the area.
ABSTRACT Financial performance and budgetary realization is one of the most important keys into the progress of an organization. Hhealthy or not can be marked from the financial performance that showed by the financial statements, that’s would be the source of organizational decisions in the future of financial side. The purpose of this research to analysis the finance performance of Bogor city government that measured with regional finance ratio, identifies the factors are affecting finance performance Bogor city ggovernment, formulate the strategies and policies in order to increasing efficiency and effectiveness the finance performance of Bogor city government in managing of the budgetary of regional revenue and expenditure. This research applied descriptive analysis, quantitatively using multiple regression method and analytical hierarchy process. The result makes the point that the finance performance of Bogor city government has unstable yet. This measured by the indicator i.e less fiscal decentralization has given dependency to the central government very high. There have the variables influence between investment, percapita income, local taxes that had a positive and gross regional domestic product (PDRB) has a negative impact also significant influence toward the financial performance. The priority sequences of strategies to improve the efficiency and effectiveness of Bogor Government finance performance with analytical hierarchy process method as follows: (1) increasing the supervision; (2) education and training; (3) communication and commitment to achieve the goals; (4) implementation the incentive and disincentive regulations; (5) intensification and intensification of taxes and local retributionKeywords: Efficiency and Effectiveness, Financial Performance, Bogor City Government, Budgetary of Regional Revenue and ExpenditureABSTRAKKinerja keuangan dan realisasi anggaran merupakan salah satu kunci dalam kemajuan suatu organisasi. Sehat atau tidaknya suatu organisasi dapat dinilai dari kinerja keuangan ditunjukkan oleh laporan keuangan, hal itu yang akan menjadi sumber keputusan organisasi di masa mendatang dari sisi finansial. Tujuan dari penelitian ini adalah menganalisis kinerja keuangan pemerintah Kota Bogor yang diukur dengan rasio keuangan daerah, mengindentifikasi faktor-faktor yang mempengaruhi kinerja keuangan pemerintah Kota Bogor, merumuskan strategi dan kebijkan untuk meningkatkan efisiensi dan efektivitas kinerja keuangan pemerintah Kota Bogor dalam pengelolaan APBD. Penelitian ini menggunakan analisis deskriptif, analisis kuantitatif menggunakan metode regresi linier berganda dan AHP. Hasilnya menunjukkan bahwa kinerja keuangan pemerintah Kota Bogor belum stabil. Hal ini ditunjukkan oleh indikator desentralisasi fiskal kurang mengingat ketergantungan keuangan terhadap pemerintah pusat sangat tinggi. Ada pengaruh antara variabel investasi, pendapatan perkapita, pajak daerah mempunyai pengaruh yang positif dan PDRB mempunyai pengaruh yang negatif signifikan terhadap kinerja keuangan. Urutan prioritas strategi meningkatkan efisiensi dan efektivitas kinerja keuangan pemerintah Kota Bogor dengan metode AHP adalah sebagai berikut: 1. meningkatkan pengawasan, 2. Pendidikan dan pelatihan, 3. komunikasi dan komitmen pencapaian sasaran, 4. penerapan regulasi insentif dan disinsentif, 5.intensifikasi dan ekstensifikasi pajak dan retribusi daerah. Kata Kunci: Efisiensi Dan Efektivitas, Kinerja Keuangan, Pemerintah Kota Bogor, APBD
Forecasting and assessing the risk of heat waves is a crucial public policy stake. Evaluate the probability of heat waves and their severity can be possible by knowing the temperature in continuous time. However, daily extremes (maxima and minima) might be the only available data. The Ornstein-Uhlenbeck process is commonly used to model temperature dynamic. An estimation of the process parameters using only daily observed suprema of temperatures is proposed here. This new approach is based on a least square minimization using the cumulative distribution function of the supremum. Risk measures related to heat waves are then obtained numerically. In order to calculate explicitly those risk measures, it can be useful to have the joint law of the Ornstein-Uhlenbeck process and its supremum. The study is _rst limited to the joint density / distribution of the endpoint and supremum of the Ornstein-Uhlenbeck process. This probability admits a density, solution of the Fokker-Planck equation and explicitly obtained as an expansion involving parabolic cylinder functions. The proof of the density expression relies on a decomposition on a Hilbert basis of the space via a spectral method. We also study the oscillating Ornstein-Uhlenbeck process, which drift parameter is piecewise constant depending on the sign of the process. The Laplace transform of this process hitting time is determined and we also calculate the probability for the process to be positive on a fixed time.
In this work, we present IBFT 2.0 (Istanbul BFT 2.0), which is a Proof-of-Authority (PoA) Byzantine-fault-tolerant (BFT) blockchain consensus protocols that (i) ensures immediate finality, (ii) is robust in an eventually synchronous network model and (iii) features a dynamic validator set. IBFT 2.0, as the name suggests, builds upon the IBFT blockchain consensus protocol retaining all of the original features while addressing the safety and liveness limitations described in one of our previous works. In this paper, we present a high-level description of the IBFT 2.0 protocol and related robustness proof. Formal specification of the protocol and related formal proofs will be subject of a separate body of work. We also envision a separate work that will provide detailed implementation specifications for IBFT 2.0.
Yoon-Chow Yeong, Khairul Shafee Kalid, Savita K. Sugathan
Since the inception of the first cryptocurrency in 2008, cryptocurrency has been receiving global attention from the public, media, merchants and regulators. Although the general sentiment suggested cryptocurrencies which leverage on blockchain technology might eventually replace the paper currency as the mainstream currency, the Malaysian regulators are still unsure that a well-established cryptocurrency ecosystem can come into place anytime soon. Unfortunately, there is a lack of cryptocurrency acceptance study, particularly in Malaysia (developing country context). Hence, this paper aims to propose a research model that integrates cryptocurrency dimension antecedents with Unified Theory of Acceptance and Use of Technology2 (UTAUT2) constructs to examine the factors that influence cryptocurrency acceptance. This study employs a quantitative approach by collecting online survey questionnaire data through the means of cryptocurrency community group on social media. The survey instrument was reviewed by four experts from the field of blockchain and 36 responses have been gathered from individuals who have cryptocurrency knowledge for pilot study. To further evaluate the reliability and validity of the proposed measures, the measurement model was assessed using structural equation modeling (SEM) technique with partial least square approach (PLS). SmartPLS software was used for PLS-SEM analyses. In this paper, the proposed research model contributes a high-level overview of and valuable insights into the potential cryptocurrency acceptance factors to regulatory bodies, practitioners as well as prospective cryptocurrency users. The findings of pilot study confirm that the measurement items and constructs in the proposed model are reliable and valid.
Evan Brinckman, Andrey Kuehlkamp, Jarek Nabrzyski, Ian Taylor
As the public Ethereum network surpasses half a billion transactions and enterprise Blockchain systems becoming highly capable of meeting the demands of global deployments, production Blockchain applications are fast becoming commonplace across a diverse range of business and scientific verticals. In this paper, we reflect on work we have been conducting recently surrounding the ingestion, retrieval and analysis of Blockchain data. We describe the scaling and semantic challenges when extracting Blockchain data in a way that preserves the original metadata of each transaction by cross referencing the Smart Contract interface with the on-chain data. We then discuss a scientific use case in the area of Scientific workflows by describing how we can harvest data from tasks and dependencies in a generic way. We then discuss how crawled public blockchain data can be analyzed using two unsupervised machine learning algorithms, which are designed to identify outlier accounts or smart contracts in the system. We compare and contrast the two machine learning methods and cross correlate with public Websites to illustrate the effectiveness such approaches.
This research work proposes a novel and comprehensive electronic cheque transactions framework. The proposed e-cheque system is free from the various security attacks such as alteration of the e-cheque, double spending of e-cheque, counterfeits e-cheques. The e-cheque generated in the proposed system can be deposited electronically or physically via teller machines. This facility provides greater flexibility to the customers of the banking system. The proposed system also provides space for professional miners to participate in the e-cheque transaction system by performing mining's and earn incentives. As the customer's perspective of security, the proposed system uses digital signature and cryptographic hash in each transaction hence it is a completely secure system. The existing CTS based cheque clearance request requires at least one day to clear a cheque which could extend to two or three days but the proposed system requires only 1.65 seconds for clearing any e-cheque.
Carol Alexander, Jaehyuk Choi, Heungju Park, Sungbin Sohn
Abstract BitMEX is the largest unregulated bitcoin derivatives exchange, listing contracts suitable for leverage trading and hedging. Using minute‐by‐minute data, we examine its price discovery and hedging effectiveness. We find that BitMEX derivatives lead prices on major bitcoin spot exchanges. Bid–ask spreads, interexchange spreads, and relative trading volumes are important determinants of price discovery. Further analysis shows that BitMEX derivatives have positive net spillover effects, are informationally more efficient than bitcoin spot prices, and serve as effective hedges against spot price volatility. Our evidence suggests that regulators prioritize the investigation of the legitimacy of BitMEX and its contracts.
To promote the benefits of the Internet of Things (IoT) in smart communities and smart cities, a real-time data marketplace middleware platform, called the Intelligent IoT Integrator (I3), has been recently proposed. While facilitating the easy exchanges of real-time IoT data streams between device owners and third-party applications through the marketplace, I3 is presently a monolithic, centralized platform for a single community. Although the service oriented architecture (SOA) has been widely adopted in the IoT and cyber-physical systems (CPS), it is difficult for a monolithic architecture to provide scalable, inter-operable and extensible services for large numbers of distributed IoT devices and different application vendors. Traditional security solutions rely on a centralized authority, which can be a performance bottleneck or susceptible to a single point of failure. Inspired by containerized microservices and blockchain technology, this paper proposed a BLockchain-ENabled Secure Microservices for Decentralized Data Marketplaces (BlendSM-DDM). Within a permissioned blockchain network, a microservices based security mechanism is introduced to secure data exchange and payment among participants in the marketplace. BlendSM-DDM is able to offer a decentralized, scalable and auditable data exchanges for the data marketplace.
Searchable symmetric encryption (SSE) allows the data owner to outsource an encrypted database to a remote server in a private manner while maintaining the ability for selectively search. So far, most existing solutions focus on an honest-but-curious server, while security designs against a malicious server have not drawn enough attention. A few recent works have attempted to construct verifiable SSE that enables the data owner to verify the integrity of search results. Nevertheless, these verification mechanisms are highly dependent on specific SSE schemes, and fail to support complex queries. A general verification mechanism is desired that can be applied to all SSE schemes. In this work, instead of concentrating on a central server, we explore the potential of the smart contract, an emerging blockchain-based decentralized technology, and construct decentralized SSE schemes where the data owner can receive correct search results with assurance without worrying about potential wrongdoings of a malicious server. We study both public and private blockchain environments and propose two designs with a trade-off between security and efficiency. To better support practical applications, the multi-user setting of SSE is further investigated where the data owner allows authenticated users to search keywords in shared documents. We implement prototypes of our two designs and present experiments and evaluations to demonstrate the practicability of our decentralized SSE schemes.
Due to rapid developments in technology, the supply chain becomes a bright area of interest among up-and-coming careers in various industries. People with careers in this field oversee such activities as product development, production, information systems, transportation, and day-to-day logistics. But, the rapidly evolving environments of an easy and comfortable life, the demand for product visibility and end-to-end traceability have grown. The existing supply chain is inefficient, unadaptable, intractable and costly as compared to innovative and advanced technology. Blockchain is the emerging and revolutionary technology that impacts the supply chain networks significantly. Therefore, in this paper, the implication of blockchain technology in the supply chain is presented.