Lam Duc Nguyen, Anders E. Kalør, Israel Leyva‐Mayorga, Petar Popovski
The data collected from Internet of Things (IoT) devices on various emissions or pollution, can have a significant economic value for the stakeholders. This makes it prone to abuse or tampering and brings forward the need to integrate IoT with a Distributed Ledger Technology (DLT) to collect, store, and protect the IoT data. However, DLT brings an additional overhead to the frugal IoT connectivity and symmetrizes the IoT traffic, thus changing the usual assumption that IoT is uplink-oriented. We have implemented a platform that integrates DLTs with a monitoring system based on narrowband IoT (NB-IoT). We evaluate the performance and discuss the tradeoffs in two use cases: data authorization and real-time monitoring.
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne
The beginning of 2020 has seen the emergence of coronavirus outbreak caused by a novel virus called SARS-CoV-2. The sudden explosion and uncontrolled worldwide spread of COVID-19 show the limitations of existing healthcare systems to timely handle public health emergencies. In such contexts, innovative technologies such as blockchain and Artificial Intelligence (AI) have emerged as promising solutions for fighting coronavirus epidemic. On the one hand, blockchain can combat pandemics by enabling early detection of outbreaks, protecting user privacy, and ensuring reliable medical supply chain during the outbreak tracking. On the other hand, AI provides intelligent solutions for identifying symptoms caused by coronavirus for treatments and supporting drug manufacturing. Motivated by these, in this paper we present an extensive survey on the use of blockchain and AI for combating coronavirus (COVID-19) epidemics based on the rapidly emerging literature. First, we introduce a new conceptual architecture which integrates blockchain and AI specific for COVID-19 fighting. Particularly, we highlight the key solutions that blockchain and AI can provide to combat the COVID-19 outbreak. Then, we survey the latest research efforts on the use of blockchain and AI for COVID-19 fighting in a wide range of applications. The newly emerging projects and use cases enabled by these technologies to deal with coronavirus pandemic are also presented. Finally, we point out challenges and future directions that motivate more research efforts to deal with future coronavirus-like epidemics.
Open access
5 source records
Blockchain Technology Applications and Security
COVID-19 diagnosis using AI
Artificial Intelligence in Healthcare and Education
Blockchain systems have received much attention and promise to revolutionize many services. Yet, despite their popularity, current blockchain systems exist in isolation, that is, they cannot share information. While interoperability is crucial for blockchain to reach widespread adoption, it is difficult to achieve due to differences among existing blockchain technologies. This paper presents a technique to allow blockchain interoperability. The core idea is to provide a primitive operation to developers so that contracts and objects can switch from one blockchain to another, without breaking consistency and violating key blockchain properties. To validate our ideas, we implemented our protocol in two popular blockchain clients that use the Ethereum virtual machine. We discuss how to build applications using the proposed protocol and show examples of applications based on real use cases that can move across blockchains. To analyze the system performance we use a real trace from one of the most popular Ethereum applications and replay it in a multi-blockchain environment.
The world is becoming more interconnected every day. With the high technological evolution and the increasing deployment of it in our society, scenarios based on the Internet of Things (IoT) can be considered a reality nowadays. However, and before some predictions become true (around 75 billion devices are expected to be interconnected in the next few years), many efforts must be carried out in terms of scalability and security. In this study we propose and evaluate a new approach based on the incorporation of Blockchain into current IoT scenarios. The main contributions of this study are as follows: i) an in-depth analysis of the different possibilities for the integration of Blockchain into IoT scenarios, focusing on the limited processing capabilities and storage space of most IoT devices, and the economic cost and performance of current Blockchain technologies; ii) a new method based on a novel module named BIoT Gateway that allows both unidirectional and bidirectional communications with IoT devices on real scenarios, allowing to exchange any kind of data; and iii) the proposed method has been fully implemented and validated on two different real-life IoT scenarios, extracting very interesting findings in terms of economic cost and execution time. The source code of our implementation is publicly available in the Ethereum testnet.
Blockchain technologies provide a platform for a new wave of project management systems, providing managers with a range of characteristics, capabilities, and feature sets to aid their praxis as they engage in increasingly complex processes and projects. This paper presents an explorative case-study in which open-ended interviews are conducted with practicing project managers. The interviews are analysed to understand currently deployed project management tools, technologies, and methods and to contextualise how blockchain based systems may allow for improvments. Five constructs emerge: transparency, control, dynamic status updating, incentives, and trust. Feedback suggests blockchain based alternatives could offer significantly better performance within each of these constructs, and thus should be explored as the technological backbone to the next generation of project management systems.
Blockchain is a new technology for processing complex and disordered information with respect to business and other industrial applications. This work is aimed at studying the consensus algorithm of blockchain to improve the performance of blockchain. Despite their advantages, the proof of stake (POS) algorithm and the practical Byzantine fault tolerance (PBFT) algorithm have high latency, low throughput, and poor scalability. In this paper, a blockchain hybrid consensus algorithm which combines advantages of the POS and PBFT algorithms is proposed, and the algorithm is divided into two stages: sortition and witness. The proposed algorithm reduces the number of consensus nodes to a constant value by verifiable pseudorandom sortition and performs transaction witness between nodes. The algorithm is improved and optimized from three dimensions: throughput, latency, and scalability. The experimental results show that the improved hybrid consensus algorithm is significantly superior to the previous single algorithms for its excellent scalability, high throughput, and low latency.
Blockchain has become very popular as the underlying technology powering Bitcoin. However, the benefits behind this technology further surpass just supporting cryptocurrencies. Blockchain can be defined as a digital ledger that allows to capture transactions conducted among several parties on real-time and serves as a decentralized database where each participant keeps an identical copy of the ledger. The appeal behind blockchain resides on its peer-to-peer network infrastructure along cryptographic capabilities. This combination enables users to conduct transactions without a trusted third-party intermediary. Benefits in accounting are even more promising as blockchain will provide a triple entry accounting system where all transactions are immutable and have been time stamped, recorded on real-time and encrypted The purpose of this paper is to review extant research on this technology and assess the impact of blockchain in the audit profession, including new risks, change in procedures and additional opportunities.
Faisal Jamil, Shabir Ahmad, Naeem Iqbal, Do‐Hyeun Kim
Over the past several years, many healthcare applications have been developed to enhancethe healthcare industry. Recent advancements in information technology and blockchain technologyhave revolutionized electronic healthcare research and industry. The innovation of miniaturizedhealthcare sensors for monitoring patient vital signs has improved and secured the human healthcaresystem. The increase in portable health devices has enhanced the quality of health-monitoringstatus both at an activity/fitness level for self-health tracking and at a medical level, providing moredata to clinicians with potential for earlier diagnosis and guidance of treatment. When sharingpersonal medical information, data security and comfort are essential requirements for interactionwith and collection of electronic medical records. However, it is hard for current systems to meetthese requirements because they have inconsistent security policies and access control structures.The new solutions should be directed towards improving data access, and should be managed bythe government in terms of privacy and security requirements to ensure the reliability of data formedical purposes. Blockchain paves the way for a revolution in the traditional pharmaceuticalindustry and benefits from unique features such as privacy and transparency of data. In this paper,we propose a novel platform for monitoring patient vital signs using smart contracts based onblockchain. The proposed system is designed and developed using hyperledger fabric, which isan enterprise-distributed ledger framework for developing blockchain-based applications. Thisapproach provides several benefits to the patients, such as an extensive, immutable history log, andglobal access to medical information from anywhere at any time. The Libelium e-Health toolkitis used to acquire physiological data. The performance of the designed and developed system isevaluated in terms of transaction per second, transaction latency, and resource utilization usinga standard benchmark tool known as Hyperledger Caliper. It is found that the proposed systemoutperforms the traditional health care system for monitoring patient data.
Abstract The research seeks to contribute to Bitcoin pricing analysis based on the dynamics between variables of attractiveness and the value of the digital currency. Using the error correction model, the relationship between the price of the virtual currency, Bitcoin, and the number of Google searches that used the terms bitcoin , bitcoin crash and crisis between December 2012 and February 2018 is analyzed. The study also applied the same analysis to prices of Bitcoin denominated in different sovereign currencies traded during the same period. The Johansen (J Econ Dyn Control 12:231-254, 1988) test demonstrates that the price and number of searches on Google for the first two terms are cointegrated. This research indicates that there are strong short-term and long-term dynamics among attractiveness factors, suggesting that an increase in worldwide interest in Bitcoin is usually preceded by a price increase. In contrast, an increase in market mistrust over a collapse of the currency, as measured by the term bitcoin crash , is followed by a fall in price. Intense world economic crisis events appear to have a strong impact on interest in the virtual currency. This study demonstrates that during a worldwide crisis Bitcoin becomes an alternative investment, increasing its price. Based on it, bitcoin may be used as a safe haven by the financial market and its intrinsic characteristics might help the investors and governments to find new mechanisms to deal with monetary transactions.
Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bitcoin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason, a web of trust is implemented on the website. The availability of all the historic of the users' interaction data makes this dataset a unique playground for studying reputation dynamics through others' evaluations. We analyze the structure and the dynamics of this web of trust with a multilayer network approach distinguishing the rewarding and the punitive behaviors. We show that the rewarding and the punitive behavior have similar emergent topological properties (apart from the clustering coefficient being higher for the rewarding layer) and that the resultant reputation originates from the complex interaction of the more regular behaviors on the layers. We show that the systems' reputation inequality reaches a high steady value with the network evolution. We characterize the reputation trajectories identifying prototypical behaviors associated to three classes of users: trustworthy, untrusted and controversial. Controversial users are the only ones presenting up and down reputation trends. We focus on these cases for understanding which are the possible factors driving reputation falls and which dynamical patterns characterize these cascades: some users have real oscillating behaviors, other abuse of the trust system doing a few good transactions to gain reputation for cheating the users afterwards, other naturally and slowly die out after a long series of positive exchanges (like disappearing from the system) and finally, some users are hardly beaten by organized trolling attacks.
Sam Blackshear, David L. Dill, Shaz Qadeer, Clark W. Barrett · 7 authors
Smart contracts are programs that implement potentially sophisticated transactions on modern blockchain platforms. In the rapidly evolving blockchain environment, smart contract programming languages must allow users to write expressive programs that manage and transfer assets, yet provide strong protection against sophisticated attacks. Addressing this need, we present flexible and reliable abstractions for programming with digital currency in the Move language [Blackshear et al. 2019]. Move uses novel linear [Girard 1987] resource types with semantics drawing on C++11 [Stroustrup 2013] and Rust [Matsakis and Klock 2014]: when a resource value is assigned to a new memory location, the location previously holding it must be invalidated. In addition, a resource type can only be created or destroyed by procedures inside its declaring module. We present an executable bytecode language with resources and prove that it enjoys resource safety, a conservation property for program values that is analogous to conservation of mass in the physical world.
Roberta Galici, Laura Ordile, Michele Marchesi, Andrea Pinna · 5 authors
We present a novel strategy, based on the Extract, Transform and Load (ETL) process, to collect data from a blockchain, elaborate and make it available for further analysis. The study aims to satisfy the need for increasingly efficient data extraction strategies and effective representation methods for blockchain data. For this reason, we conceived a system to make scalable the process of blockchain data extraction and clustering, and to provide a SQL database which preserves the distinction between transaction and addresses. The proposed system satisfies the need to cluster addresses in entities, and the need to store the extracted data in a conventional database, making possible the data analysis by querying the database. In general, ETL processes allow the automation of the operation of data selection, data collection and data conditioning from a data warehouse, and produce output data in the best format for subsequent processing or for business. We focus on the Bitcoin blockchain transactions, which we organized in a relational database to distinguish between the input section and the output section of each transaction. We describe the implementation of address clustering algorithms specific for the Bitcoin blockchain and the process to collect and transform data and to load them in the database. To balance the input data rate with the elaboration time, we manage blockchain data according to the lambda architecture. To evaluate our process, we first analyzed the performances in terms of scalability, and then we checked its usability by analyzing loaded data. Finally, we present the results of a toy analysis, which provides some findings about blockchain data, focusing on a comparison between the statistics of the last year of transactions, and previous results of historical blockchain data found in the literature. The ETL process we realized to analyze blockchain data is proven to be able to perform a reliable and scalable data acquisition process, whose result makes stored data available for further analysis and business.
Intan Permatasari, Meryam Essaid, Hyeonwoo Kim, Hongtaek Ju
A good archive management system must consider information security aspects, such as availability, confidentiality, and integrity. The Cilegon E-Archive (CEA) system is a centralized system for managing the lifecycle of archives. The existing CEA system has several problems, including a single point of failure, low data availability, and difficulty in proving the originality of files. This paper introduces a prototype for a new CEA system that integrates IPFS and the Ethereum private network. In addition, CEA DApp is developed as an interface for users in interacting with CEA system, and its functionality is managed by a smart contract. The results show that the conducted improvements into the CEA system highly improved the system security in terms of preventing archival forgeries.
The combination of Internet technology and the financial industry makes information more symmetrical, improves the efficiency of payment and settlement in the financial industry, reduces the cost of currency financing, and makes risk management more effective based on big data technologies. Just the improvement of form and means has not changed the nature of finance. With the development boom of financial technology, blockchain technology seems to have become the key to start a new technological revolution. The value transfer of blockchain technology and the absence of credit intermediation, high security, decentralization, and de-monetization are a fundamental disruption of the financial industry.
Eng Chuen Loh, Shuhaida Ismail, Azme Khamis, Aida Mustapha
Bitcoin is the most popular cryptocurrency with the highest market value. It was said to have potential in changing the way of trading in future. However, Bitcoin price prediction is a hard task and difficult for investors to make decision. This is caused by nonlinearity property of the Bitcoin price. Hence, a better forecasting method are essential to minimize the risk from inaccuracy decision. The aim of this paper is to compare two different training algorithms which are Levenberg-Marquardt (LM) backpropagation algorithm and Scaled Conjugate Gradient (SCG) backpropagation algorithm using Feedforward Neural Network (FNN) to forecast the Bitcoin price. After obtaining the forecasting result, forecast accuracy measurement will be carried out to identify the best model to forecast Bitcoin price. The result showed that the performance of Bitcoin price forecasting increased after the application of FNN – LM model. It is proven that Levenberg-Marquardt backpropagation algorithm is better compared to Scaled Conjugate Gradient backpropagation when forecasting Bitcoin price using FNN. The resulting model provides new insights into Bitcoin forecasting using FNN – LM model which directly benefits the investors and economists in lowering the risk of making wrong decision when it comes to invest in Bitcoin. Keywords: Bitcoin Price; Artificial Neural Network; Forecasting
Crypto currency, bitcoins and virtual currencies are topics the scientific community has been discussing for years. The Bank of the Russia has repeatedly warned about high risks of investments in crypto currencies and risks in its turnover. Populations of many countries continue to lose their investments in virtual currencies, which are positioned by their developers as tamper-proof. However, there is still a vacuum in the legal regulation of crypto currencies and the legitimacy of their use as legal payment. The article presents the author’s view on a number of issues arisen in the process of crypto currency, bitcoin, digital and virtual currency use and presents ways to solve them in the context of Russian and world experience.
An increasing number of industries rely on Internet-of-Things devices to track physical resources. Blockchain technology provides primitives to represent these resources as digital assets on a secure distributed ledger. Due to the proliferation of blockchain-based assets, there is an increasing need for a generic mechanism to trade assets between isolated platforms. To date, there is no such mechanism without reliance on a trusted third party. In this work, we address this shortcoming and present XChange. Unlike existing approaches for decentralized asset trading, we decouple trade management and the actual exchange of assets. XChange mediates trade of any digital asset between isolated blockchain platforms while limiting the fraud conducted by adversarial parties. We first describe a generic, five-phase trading protocol that establishes and executes trade between individuals. This protocol accounts full trade specifications on a separate blockchain. We then devise a lightweight system architecture, composed of all required components for a generic asset marketplace. We implement XChange and conduct real-world experimentation. We leverage an existing, lightweight blockchain, TrustChain, to account all orders and full trade specifications. By deploying XChange on multiple low-resource devices, we show that a full trade completes within half a second. To quantify the scalability of our mechanism, we conduct further experiments on our compute cluster. We conclude that the throughput of XChange, in terms of trades per second, scales linearly with the system load. Furthermore, we find that XChange exhibits superior throughput and order fulfil latency compared to related decentralized exchanges, BitShares and Waves.
Blockchain Sharding is a blockchain performance enhancement approach. By splitting a blockchain into several parallel-run committees (shards), it helps increase transaction throughput, reduce computational resources required, and increase reward expectation for participants. Recently, several flexible sharding methods that can tolerate up to $n/2$ Byzantine nodes ($n/2$ security level) have been proposed. However, these methods suffer from three main drawbacks. First, in a non-sharding blockchain, nodes can have different weight (power or stake) to create a consensus, and as such an adversary needs to control half of the overall weight in order to manipulate the system ($p/2$ security level). In blockchain sharding, all nodes carry the same weight. Thus, it is only under the assumption that honest participants create as many nodes as they should that a $n/2$ security level blockchain sharding reaches the $p/2$ security level. Second, when some nodes leave the system, other nodes need to be reassigned, frequently, from shard to shard in order to maintain the security level. This has an adverse effect on system performance. Third, while some $n/2$ approaches can maintain data integrity with up to $n/2$ Byzantine nodes, their systems can halt with a smaller number of Byzantine nodes. In this paper, we present a $p/2$ security level blockchain sharding approach that does not require honest participants to create multiple nodes, requires less node reassignment when some nodes leave the system, and can prevent the system from halting. Our experiments show that our new approach outperforms existing blockchain sharding approaches in terms of security, transaction throughput and flexibility.
Companies trying to build new solutions using blockchain are confronted with a plethora of available concurrent technologies that have many control knobs which require fine-tuning by experts. Exiting studies that build decision models for blockchain adoption or selection lack an automated way to use non-functional requirements to provide recommendations. In this paper, we build a knowledge base for blockchain solutions by analyzing whitepapers and studies, but also our benchmark results performed in a controlled environment. Then, we implement a Multi-Criterion Decision Analysis method to determine the most suitable blockchain solution from companies provided requirements and preferences. Finally, we illustrate our approach by running the decision process on a realistic supply-chain use case. This paper provides a rationale for blockchain deployment choices. While still limited in scope, we plan to include more blockchain alternative and more flexible requirements inputs in future work.
Smart contract (SC) platforms form blocks of transactions into a chain and execute them via user-defined smart contracts. In conventional platforms like Bitcoin and Ethereum, the transactions within a block are executed \emph{sequentially} by the miner and are then validated \emph{sequentially} by the validators to reach consensus about the final state of the block. In order to leverage the advances of multicores, this paper explores the next generation of smart contract platforms that enables concurrent execution of such contracts. Reasoning about the validity of the object states is challenging in concurrent smart contracts. We examine a programming model to support \emph{optimistic} execution of SCTs. We introduce a novel programming language, so-called OV, and a Solidity API to ease programing of optimistic smart contracts. OV language together with static checking will help reasoning about a crucial property of optimistically executed smart contracts -- the validity of object states in trustless systems.
Companies trying to build new solutions using blockchain are confronted with\na plethora of available concurrent technologies that have many control knobs\nwhich require fine-tuning by experts. Exiting studies that build decision\nmodels for blockchain adoption or selection lack an automated way to use\nnon-functional requirements to provide recommendations. In this paper, we build\na knowledge base for blockchain solutions by analyzing whitepapers and studies,\nbut also our benchmark results performed in a controlled environment. Then, we\nimplement a Multi-Criterion Decision Analysis method to determine the most\nsuitable blockchain solution from companies provided requirements and\npreferences. Finally, we illustrate our approach by running the decision\nprocess on a realistic supply-chain use case. This paper provides a rationale\nfor blockchain deployment choices. While still limited in scope, we plan to\ninclude more blockchain alternative and more flexible requirements inputs in\nfuture work.\n
In recent years blockchain technology has become mainstream research topic because of its decentralized, peer to peer transaction and anonymity properties. There are several applications of blockchain which are secure and easy as compare to the current techniques. One of the applications is a smart contract. Smart contracts are lines of code which are stored on a blockchain and automatically executed when the conditions defined by the it (developer) are met. This smart contract with the addition of blockchain technology can do task fast and with high security. In this paper we have developed a smart contract for a generalized notary application on solidity, Ethereum and the application is tested using the truffle suite. Furthermore, applications and their methodology for notary applications are also mentioned.
There is a shared view among practitioners that the blockchain is a revolutionary, decentralized technology that will have a larger impact than the Internet. Firms are increasingly using blockchains for various applications; the most prominent of which to date are digital currencies. In this article, we aim to increase our theoretical understanding of the driving forces behind the success and volatility of digital currencies. We use a detailed dataset of 345 digital currencies for our explorative analysis and identify some of the key factors that can explain their performance. We find that the success and volatility of digital currencies depend on their business type (i.e., whether they relate to a platform business or not) and on their technology type (i.e., whether they are based on their own specialized blockchain technology or on a third-party standardized platform blockchain). Our findings suggest that, paradoxically, to obtain the promised benefits of this decentralized technology, firms need to centralize part of it to retain control over critical strategic dimensions (data and rules for transaction). We discuss the implications of our discovery for other contexts undergoing digital transformation.
The last decade has sparked several valiant efforts in deductive verification of distributed agreement protocols such as consensus and leader election. Oddly, there have been far fewer verification efforts that go beyond the core protocols and target applications that are built on top of agreement protocols. This is unfortunate, as agreement-based distributed services such as data stores, locks, and ledgers are ubiquitous and potentially permit modular, scalable verification approaches that mimic their modular design. We address this need for verification of distributed agreement-based systems through our novel modeling and verification framework, QuickSilver, that is not only modular, but also fully automated. The key enabling feature of QuickSilver is our encoding of abstractions of verified agreement protocols that facilitates modular, decidable, and scalable automated verification. We demonstrate the potential of QuickSilver by modeling and efficiently verifying a series of tricky case studies, adapted from real-world applications, such as a data store, a lock service, a surveillance system, a pathfinding algorithm for mobile robots, and more.