Since Bitcoin’s launch in early 2009, the industrial and academic interest in Blockchain and other cryptocurrencies have grown rapidly. Blockchains have been applied in many areas outside of finance such as healthcare, commerce and judiciary already. This technology promotes the creation of a decentralized environment where transactions and data are not under the control of any third-party organization. Blockchain is a fundamentally new technology that could revolutionize the future of transaction-based exchanges. Extensive research is being done in order to implement this technology various sectors. Blockchain technology comes with an edge of inbuilt auditability, trust and transfer of value which also makes it irresistible. \nThis work explores an agent based Blockchain-based Education System through mathematical modeling and simulation tools. The model is constructed to explore how Blockchain technology can be used to verify credit score of students, identify the occurrence and prevention of potential attacks. Along with technical characteristics of Bitcoin and Blockchain; cost, time and behavioural considerations of the system are also made. This is followed by analysing of the number of transactions, size of blockchain, network efficiency, cost analysis of the system along with the network efficiency. The proposed model, based on the blockchain technology shifts the education grading and credit rewarding system from the analog and physical world into a globally efficient, transparent and universal version. The work contributes a foundation for advancing current understanding of blockchain systems, and to further the development of simulation models of blockchains.
Named Data Networking is built with security which requires each named Data object to be digitally signed by its producer. Thus, the NDN project has proposed a key management model on NDN testbed for verification of the Data packet to be immune to distributing poisoned content. However, in practice, this model poses two challenges for verifying fake content: (1) the centralized architecture easily leads to a single point of failure, especially when the root key fails, its difficult to verify the keys across sites due to the lack of trust between them, and (2) excessive overhead of certificate chain traversal when verifying signature. This paper first proposes a blockchain-based key management scheme in NDN to address the problem of lack of mutual trust between sites without trust anchors. Specifically, all site nodes form a permissioned blockchain for storing public key hashes to ensure the authenticity, and the proxy gateway participates in verifying to reduce excessively frequent communication between the router and the blockchain. In addition, the NDN public key content object and the scheme of their storage, verification, and revocation are redesigned. The result of our analysis and evaluation shows that the proposed scheme is capable of supporting less verification numbers and higher verification efficiency.
Thomas Morstyn, Alexander Teytelboym, Malcolm McCulloch
This paper proposes the novel application of matching markets with contracts for electric vehicle smart charging. The flexibility inherent in electric vehicle charging presents the new opportunity for automation and coordination to shape overall demand. Mechanisms that incentivise coordination are a promising approach for integrating the individual preferences and energy requirements of electric vehicle owners. However, these mechanisms require careful design, since they directly influence power system operation. This paper proposes a new market design, allowing owners of electric vehicles and aggregators to competitively negotiate contracts specifying the time and price of charging at discrete power levels. It is shown that the agents' preferences over contracts satisfy the condition of substitutability, establishing the existence of a stable outcome - an agreed set of contracts no group of agents wish to mutually deviate from. A distributed price-adjustment process is then presented for finding stable outcomes, which only requires local agent decisions and agent-to-agent negotiation. An advantage of the proposed market design is that contracts specify discrete charging power levels, rather than requiring continuously controllable charging powers. This makes it suitable for standard charging infrastructure, and could potentially increase efficiency compared with strategies that operate chargers at low power levels.
Aug 1, 2018·2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Blockchains such as those used by the Bitcoin and Ethereum cryptocurrencies provide a global, observable record of all transactions and associated data. Analyzing blockchain data is useful for tasks such as detecting fraudulent activities, studying the use and growth of the system, and understanding its levels of anonymity and traceability. Such analysis is challenging due to the high volume and rapidly changing characteristics of popular blockchains. In particular, online (soft real-time) analysis of blockchains requires methods that adapt organically to changes in the data. This paper describes such a method based on self-organizing maps and reports on experiments using the Bitcoin blockchain data.
Blockchain Technology Applications and Security
Data Stream Mining Techniques
Advanced Steganography and Watermarking Techniques
Alexandra Piedad Cortez Ordoñez, Ana Belén Tulcanaza-Prieto
The new technological advances have brought a revolution on how economic agents interact with society and markets. Nowadays, the use of virtual currencies is more frequent in the financial transactions and bitcoin has been defined as the most important world cryptocurrency due to its high market capitalization and its technological infrastructure. Several studies have been conducted to discuss bitcoin advantages and disadvantages; however, few papers in literature have examined its connection and influence on the stock market. The objective of this paper is precisely cover this gap. Firstly, by providing tools and concepts to understand bitcoin’s dynamic, and then determining its relationship with stock market indexes. In that context, this manuscript examines the definition and function of bitcoin in the global world and its presence in Ecuador. Besides, exploratory and visual analyses are provided using the evolution of bitcoin and other market indexes. Finally, a linear correlation is computed between bitcoin, other cryptocurrencies, stock exchange indexes and commodities. The results in this study, employing visual and statistical analyses, demonstrated that bitcoin has: a strong relationship with other cryptocurrencies; a lineal correlation, not as strong as the previous one, with the main stock market indexes; and no linear correlation with commodities.
With the underlying technology of Bitcoin or other crypto-currencies and its rapid growth nowadays, many places have begun accepting Bitcoin payments in hot debate. It is hardly to deny the emerging success of the creation Blockchain platform behind of Bitcoin in the field of mathematics, finance, banking, and healthcare. The paper aims to create a diagrammatic conceptual model of medical app using Blockchain technology to manage all database of patients and doctors when they have a surgery. The model is built based on the gap of previous models which are mostly using Blockchain in banking and finance sector. Focusing on the development of mission space conceptual models, this paper will continue to propose a simulation space conceptual models in current studies, especially in the context of very few models applied blockchain in healthcare. After creation of this model, an app on smartphone using Bitcoin in payment could be created to facilitate doctors' management of all their patients directly and effectively as well as helping patients have a good comparison of cost, procedure or preparation of pre and post-surgery. Hopefully this paper will contribute to the given field the conceptual model for medical stakeholders including researcher, public health authorities, etc. to participate in the network as Blockchain "miners", to synthesize anonymous data as mining rewards, in return for sustaining and securing the network via Proof of Work.
Abstract In this study, we apply the Bitcoin to estimate the price of the Venezuelan bolivar, due to the unreliability of this currency's official exchange rate. Our approach is based on the triangular no‐arbitrage condition and takes the Bitcoin as an intermediate currency. To verify its validity, in addition to bolivars, six currencies are first considered in the empirical study. We find that trading through the Bitcoin market produces higher transaction costs or requires higher risk compensation than trading through the conventional exchange market. Then, we explore the Venezuelan case. Comparing the estimates of the black market bolivars, which are generated from several popular media sources and the Web site Dolartoday.com, using Bitcoin can produce reliable bolivar exchange rates quickly and easily. To sum up, we verify the feasibility of using the triangular no‐arbitrage condition in foreign exchange markets to estimate exchange rates through the Bitcoin. This is especially useful when capital controls exist such as they do in Venezuela.
The blockchain systems are analyzed under the context of the personal health record system (PHRs) requirements. The transparent property of blockchain may cause the privacy and confidentiality concerns for PHRs. The append-only storage of blockchain can be a barrier for implementing the revocability of consent in PHRs. Moreover, the health care data can be very large exceeding the practical storage capabilities of the current blockchain usages. The most important issues of blockchain include the limited storage, privacy, consent revocation, performance, energy consumption and scalability. A blockchain based secret-data sharing model is proposed by using a proxy re-encryption technique to support the PHRs in this work. Some potential attacks which can attempt on the proposed model and how the model can handle such attempts is also discussed.
With the development of internet of things (IoT) network in recent years, while the centralization data management brings longer delay while has more safety troubles. Moreover, once a single device is attacked, the system crashes. So, blockchain technique which could realize safety distributed data management is introduced. However, the consensus mechanism of blockchain consumes huge computation resources. And the storage of entire ledger also consumes huge storage resources of the blockchain nodes. Due to the limited capacity of IoT devices, the nodes cannot afford the computation resources to reach consensus and caching resources. This paper introduces an architecture of edge computing based blockchain network which makes use of the computation and caching capacity of edge server to help the IoT devices in reaching consensus and storing data.
BACKGROUND & OBJECTIVES: Numerous studies have highlighted the regressive and immiserating impact of out-of-pocket (OOP) health spending in India. However, most of these studies have explored this issue at the national or up to the State level, with an associated risk of overlooking intra-State diversities in the health system and health-seeking behaviour and their implication on the financial burden of healthcare. This study was aimed to address this issue by analyzing district level diversities in inequity, financial burden and impoverishing impact of OOP health spending. METHODS: A household survey of 62,335 individuals from 12,134 households, covering eight districts across three States, namely Gujarat, Haryana and Rajasthan was conducted during 2014-2015. Other than general household characteristics, the survey collected information on household OOP [sum total of expenditure on doctor consultation, drugs, diagnostic tests etc. on inpatient depatment (IPD), outpatient depatment (OPD) or chronic ailments] and household monthly consumption expenditure [sum total of monthly expenditure on food, clothing, education, healthcare (OOP) and others]. Gini index of consumption expenditure, concentration index and Kakwani index (KI) of progressivity of OOP, catastrophic burden (at 20% threshold) and poverty impact (using district-level poverty thresholds) were computed, for these eight districts using the survey data. The concentration curve (of OOP expenditure) and Lorenz curve (of consumption expenditure) for the eight districts were also drawn. RESULTS: The distribution of OOP was found to be regressive in all the districts, with significant inter-district variations in equity parameters within a State (KI ranges from -0.062 to -0.353). Chhota Udepur, the only tribal district within the sample was found to have the most regressive distribution (KI of -0.353) of OOP. Furthermore, the economic burden of OOP was more pronounced among the rural sample (CB of 19.2% and IM of 8.9%) compared to the urban sample (CB of 9.4% and IM of 3.7%). INTERPRETATION & CONCLUSIONS: The results indicate that greater decentralized planning taking into account district-level health financing patterns could be an effective way to tackle inequity and financial vulnerability emerging out of OOP expenses on healthcare.
Capital constraints exist in many supply chains. We examine a low carbon distribution channel that consists of a manufacturer and a retailer, in which the retailer is constrained by capital. The retailer can be financed by bank credit from a competitive bank market. A Stackelberg model is developed to analyze the integrated decision-making process of ordering, financing, and emission reduction. By comparing the decentralized and centralized channels, we obtain that the manufacturer’s green technology investment should be linearly proportional to the retailer’s order quantity in both channels. Thus, a large order quantity leads to increased efforts to reduce emissions. Results further show that the centralized channel in some cases has fewer emissions and can generate more profits for the whole supply chain compared with the decentralized channel. We therefore propose a revenue sharing contract with a function form to coordinate the distribution channel. When the government allocates appropriate quotas to the supply chain, high carbon price can benefit the environment and supply chain efficiency.
Aug 1, 2018·2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech)
The smart community (SC), as an important part of the Internet of energy (IoE), can facilitate integration of distributed renewable energy sources (RES) and electric vehicles (EVs) in the smart grid. However, due to the potential security and privacy issues caused by untrusted and opaque energy markets, it becomes a great challenge to optimally schedule the charging behaviors of EVs with distinct energy consumption preferences in SC. In this paper, we propose a contract based energy blockchain for secure EV charging in SC. Firstly, a permissioned energy blockchain system is introduced to implement secure charging services for EVs with the execution of smart contracts. Secondly, a reputation based delegated Byzantine fault tolerance (DBFT) consensus algorithm is proposed to eficiently achieve the consensus in the permissioned blockchain. Furthermore, based on the contract theory, the optimal contracts are analyzed and designed to satisfy EVs' individual needs from energy sources while maximizing the operator's utility. Finally, numerical results validate the effectiveness and ef?ciency of the proposed scheme through comparison with other conventional schemes.
Sachin M. Kolekar, Rahul P. More, Smita S. Bachal, Anuradha Yenkikar
Blockchain technologies are secure massive power in the last few years. Block chains are distributed ledgers that facilitate parties who do not steady trust each other to maintain a set of ecumenical states. The parties concur on the easiness, standards and histories of the states. As the technology backdrop is enlarge swiftly, it is mutually consequential and arduous to have a rigid grasp of what the foundation technologies have to offer, particularly with difference to their data dealing out capabilities. In this paper, we first survey the state of the art, fixating on secretive block chains. We analyze both in-engenderment and research systems in four dimensions: disseminated ledger, intrusion detection, consortium Blockchain, consensus protocol and perspicacious agreement. We then present BLOCKBENCH, a criterion skeleton for understanding performance of private block chains and public Blockchain. In this chapter we have discussed the circumscriptions of Blockchain.
Aug 1, 2018·2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Paul Sarda, Mohammad Jabed Morshed Chowdhury, Alan Colman, Muhammad Ashad Kabir · 5 authors
Current job recruitment process involves a good number of documentations. It is not uncommon for job applicants to misrepresent, overstate or falsify past employment, specifically work experience, and skills. Where this occurs and the applicant is subsequently appointed, a company may be exposed to significant commercial and legal risk. Companies usually employ third party HR recruitment agencies to verify the authenticity of an applicant's listed work experience. However, verification of applicant's past work experience is both time consuming and costly. Moreover, companies have to rely on the third parties, which may not be trustworthy. Therefore, small and medium size companies usually avoid the verification process. In this research, we demonstrate how blockchain technology can provide cost-effective, and real-time work history verification. The proposed approach also ensures trustworthy and privacy-preserving (work-history) data sharing. Furthermore, we have implemented a prototype to demonstrate how individuals can share and verify work history using Ethereum-based public blockchain.
Ee Hong Aw, Ralucca Gera, Kenneth S. Hicks, Nicholas Koeppen · 5 authors
Due to the anonymous and remote nature of Electronic Commerce (E-commerce), reviews of products and vendors left by previous customers have emerged as an integral part of most online transactions. The reviews may influence the decision of customers buying the product since E-commerce websites/services do not allow customers to validate and inspect products in-store. In this paper, we analyze data from two BITCOIN marketplaces which include transactions between marketplace users and the ratings of those transactions given by those users. In this analysis we create a synthetic network model with similar topological properties as the networks of the interactions of both marketplaces. The results of our analysis show an interesting phenomenon in which user ratings, which range from -10 to 10, converge to a value of approximately two as the number of a user's transactions increase. Finally, we suggest future work on our synthetic model to improve its agreement with the transaction networks in order to better understand how reviews influence user decisions on transactions.
Chelsea Hinds-Charles, Jenelee Adames, Ye Yang, Yusong Shen · 5 authors
As one of the most successful Blockchain systems, Bitcoin evolved over the past 8 years. The collaborative contribution of its online software development community gradually shaped the functionality and performance of Bitcoin. To date, most discussions around Bitcoin are from technologies underlying the product, as well as market applications. There are very few studies on the development and evolution processes of the Bitcoin software. It is important to investigate on such developmental issues, in order to better understand the development methodologies and lessons learnt from such a spearheaded Blockchain system. This paper serves this purpose by examining the issues data extracted from the Bitcoin GitHub repository from 2011 to 2018. It reports the trends of the major development issues from a longitude perspective. The main results include: 1) the average lifespan of an issue in Bitcoin issue repository is approximately 57 days; and 2) the Top-7 issue types including refactoring, tests, doc, RPC.REST.ZMQ, GUI, bugs, and wallet, accounting for 64.3% of all issues; 3) topic modeling techniques are beneficial in mining popularity and evolution of key issue topics and most problematic architecture components. Using data analysis and visualization techniques, this paper suggests the insights for significant development decisions such as better managing issue repository and strategic allocating of bug resolution effort.
James Clay, Alexander Hargrave, Ramalingam Sridhar
We investigate the impact of how a cryptocurrency mining system can affect the power consumption of mobile devices. Specifically we look at CoinHive, a cryptocurrency miner and associated mining pool targeting the Monero (XMR) cryptocurrency. CoinHive distributes a JavaScript-based miner to webpages where visitors run the script and provide computing power to the web host's CoinHive account. Ideally, hosting JavaScript-based cryptocurrency miners provides alternatives to using ad-networks as a source of website revenue. While some users may not oppose an energy for advertisement trade-off, it may be less palatable to mobile users concerned with battery life. Our initial studies have revealed that, at a minimum, running the normally distributed JavaScript-based miner increases the power draw of a Samsung Galaxy S4 by about 5 fold. Under certain circumstances, the power draw can increase to eleven-fold. We illustrate these findings by comparing them with various normal use benchmarks and with a variety of different ad-enabled webpages.
The recent increase in research on financial technology has resulted in transactions receiving considerable research attention. With the increasing importance of bitcoin, many related topics require further clarification. Because bitcoin is a popular financial asset, determining whether the price information is fully circulated among trading platforms has been the focus of many studies in recent years. The method for verifying the efficient market hypothesis relates to whether the price series is a random walk; that is, whether a unit root exists. According to the literature, whether the price of bitcoin satisfies the efficient market hypothesis remains controversial; however, these studies have not considered nonlinear data structures. To deal with the structural change of data, this study employed different unit root tests, namely the Zivot-Andrews unit root test and Kapetanios-Shin unit root test, to investigate bitcoins' relationship to the efficient market hypothesis. If the efficient market hypothesis is validated, the price formed by the bitcoin trading platform is close to a perfectly competitive mechanism, and the information can be quickly and completely reflected in the price, with information of different trading platforms having mutual influence. Therefore, this study applied the threshold vector autoregressive model to explore price information transmission between various trading platforms. The contribution of this research is its exploration of the financial tools derived from the highly developed fields of financial science and technology. This is helpful for providing new methods for completing financial transactions or a platform for speculators to engage in arbitrage.
Andrea Tesei, Luca Di Mauro, M. Falcitelli, Sandro Noto · 5 authors
Intelligent Transport Systems (ITS) show many potential benefits to the way we travel today. The security requirements to be matched in this kind of systems are challenging and they show technical, societal, legal, and economical concerns (e.g. anonymity, accountability, non-repudiation). To address security, standardization bodies (IEEE 1609.2, ETSI) and harmonization efforts (Car2Car Communication Consortium (C2C-CC)) have proposed a Certification Authority-based (CA-based) Vehicular Public Key Infrastructure (VPKI) which still suffers of Single Point of Failure (SPoF) locate in CAs and does not provide transparency in the certificate issuance. We propose IOTA-VPKI, a Distributed Ledger Technology-based (DLT-based) VPKI that improve the state-of-the-art eliminating SPoF with seamless scalability with respect to the users. IOTA-VPKI also guarantees transparency in the issuance of certificates as well as historical proof-of-possession by storing signed and hashed certificates on the IOTA ledger to facilitate verification procedure. The use of IOTA DLT assure also the feasible deploy in Internet of Things (IoT) domain, where the devices involved have limited computational resources. The effectiveness of our DLT-based VPKI will be measured in testbed for EU Horizon 2020-funded AUTOmated driving Progressed by Internet Of Things (AUTOPILOT) project.
With the development of computer and network technology, on-board computers have more stronger capability of computing and network communication. Multiple vehicles can form an Autonomous Vehicular Cloud (AVC) for the certain need to provide cloud computing services for customers. However, the infrastructure of AVC is open completely, how to guarantee the non-repudiation of task execution information is a very important issue during the process of task execution. Blockchain technology is a proven technology with information security and non-repudiation in distributed environments. Smart contract of Ethereum used to design a kind of task scheduling strategy which is suitable for the AVC environment in this paper. The strategy can guarantee the non-repudiation of task execution information. This paper builds the private chain of Ethereum on simulation vehicles node and creates and deploys the smart contract. Experiments show that the task scheduling strategy is very effective.
The existing data sharing models have some issues such as poor transparency of data transactions, data without security assurance and lacking of effective data tracking methods. This paper proposed a brand-new data sharing scheme based on blockchain technology. Firstly, a blockchain double-chain structure about blockchain was introduced, one chain was used to store the original data and another was used to store transaction data generated by transactions. This structure separated the original data storage and data transactions. Secondly, combined with proxy re-encryption technology, safe and reliable data sharing were achieved. Finally, a new design was implemented. The logical structure of data transaction records enables data to be traced. The results of correctness and security analysis showed that this scheme can provide new technical ideas and methods for big data sharing and data trace.
Blockchain is a new trend rising fast from the community and the enterprise world. As an infrastructural technology it is finding its way into a growing number of domains like finance, medical, digital marketplace, pharmaceutical and government agencies. While blockchain technology is primarily thought as the foundation of Bitcoin, it has grown far beyond underpinning the virtual currency. It promises building better trust, transparency, and integrity without a third-party and the risk of censorship. These remarkable advantages do however come at a price. The blockchain ecosystem is riddled with human-centric and economical issues for its participants, leading to unintended consequences in decentralized networks. Gamified software engineering is a growing field that in particular taps into gamification technology, the application of game mechanics in non-game contexts, to address human-related concerns. There are currently no studies around blockchain that have been identified to have a clear view of existing research and solutions for utilizing the gamification in the emerging blockchain systems. As a first step towards filling this gap, this paper discusses and identifies two major human-based problems in the blockchain decentralized applications and development. For those problems, it proposes a preliminary gamified model to provide a basis for expanding future research and applications in this joint domain.
Redha Arifan Juanda, Jondri Jondri, Aniq Atiqi Rohmawati
Abstrak Bitcoin adalah salah satu kurensi elektronik yang bersifat terdesentralisasi dan tidak diatur atau dijamin oleh otoritas pusat. Sebagai sebuah sistem yang masih berusia muda, mengakibatkan harga Bitcoin sangat fluktuatif dan sering kali membuat resah pengguna dan investor Bitcoin. Oleh karena itu, diusulkan sebuah metode atau sistem prediksi harga Bitcoin dengan mempelajari pola dan tingkah laku data time series harga historisnya. Sebelumnya telah dilakukan penelitian yang serupa yaitu prediksi harga Bitcoin dengan menggunakan Support Vector Machines. Teknik yang diusulkan pada penelitian ini yaitu prediksi harga Bitcoin dengan menggunakan salah satu arsitektur Artificial Neural Network (ANN) yaitu Recurrent Neural Network (RNN). Semakin optimal model yang dibangun maka akan semakin tinggi pula akurasi yang dihasilkan. Bobot RNN yang optimal dapat diperoleh dengan algoritma optimasi Backpropagation Through Time (BPTT). Dari proses pelatihan dan pengujian, didapatkan akurasi terbaik sebesar 98.76% pada data latih dan 97.46% pada data uji. Kata kunci : Bitcoin, Recurrent Neural Network, Data Time Series, Prediksi, Backpropagation Through Time Abstract Bitcoin is a decentralized digital currency, as the system works without a central bank or single administrator. As the system is still young, Bitcoin prices are very volatile and often make users and investors worried. Therefore, the author proposed a method or a system of Bitcoin prices prediction by studying the pattern and behavior of time series data. Previously, a similar study has been conducted, the prediction of Bitcoin prices using Support Vector Machines. The technique proposed in this research is Bitcoin prices prediction using one of Artificial Neural Network architecture (ANN) which is Recurrent Neural Network (RNN). The more optimal the model is built the higher the accuracy will be produced. The optimal RNN weight can be obtained with Backpropagation Through Time (BPTT) optimization algorithm. From the training and testing processes, the model archieves the highest accuracy of 98,76% on training data and 97,46% on testing data. Keywords: Bitcoin, Recurrent Neural Network, Time Series Data, Forecasting, Backpropagation Through Time