P Bhanupriya, Sabitha Gauni, K Kalimuthu, C. T. Manimegalai
Abstract Blockchain has recently become an essential tool which enables sensitive cloud services without the need for central confidence. For example, several different cryptocurrencies were permitted with public blockchains. Unfortunately, confidential details may be exposed on current public blockchain and smart contracts implemented there. Whilst some continuous work is under way to resolve these insecure knowledge leakage problems using advanced cryptography, they need major improvements on current and common Blockchain technology such as Ethereum and are typically costly in computing. On the other hand, blockchain applications were proposed to allow the data exchange among the pre accepted nodes/participants to be more efficient and privacy-preserving. While private blockchains respond to certain challenges of privacy by allowing only the particular community of participants to view sensitive data, they do not allow public transparency for communications because businesses are accepted by a known number of users also cannot be freely viewed. One natural problem is whether we should use public and private Blockchain networks in order to allow effective, improve privacy and accountable applications in view of these findings? In this work, we try in connection with digital auctions to face this challenge. In specific, we provide a newly designed blockchain architecture combined with private and open blockchains which enables sensitive offers to be opened up on a secluded blockchain so solitary the merchant can study the offers, and none of others. We also use shared blockchains to report the public sale winner and to make transfers responsible. Moreover, we demonstrate how we can promote sincere activity among auction participants by using intelligent contracts on public blockchains. Our detailed analytical findings suggest that it’s more cost effective compared to pure public auction implementations based on blockchain.
Mahdi Mallaki, Babak Majidi, Amirhossein Peyvandi, Ali Movaghar
In the last decade various crypto-currencies opened new doors to a decentralized electronic monetary system. Emergence of new Blockchain platforms, such as Ethereum, introduced new features for the implementation of decentralized software or smart contracts. The applications of blockchain technology for secure and efficient information systems is rapidly increasing. However, due to the limitations of this platform including high computational and storage cost, it is not possible to run sophisticated and computationally expensive software on the blockchain. In this paper, a new framework for execution of smart programs on blockchain called the Smart Program Runner Framework (SPRF) is proposed. The proposed framework works by moving decentralized applications to the off-chain and only storing the hash of the state of the application on-chain. This framework can be implemented by creating a side-chain to an existing blockchain without any modifications. The proposed framework is implemented on Stellar blockchain and has various applications for secure and efficient information systems and can provide the required platform for execution of computationally demanding software on blockchain.
Abstract With the large-scale application of cloud storage systems, lots of attribute-based access control (ABAC) schemes have been introduced to protect data and user security in this insecure environment. ABAC can make data owners control their own data and protect data security and privacy. However, there are two serious privacy leakage problems, namely user attribute privacy and policy privacy, should be solved in the process of constructing ABAC schemes. In this paper, an ABAC scheme supporting privacy protection is constructed, which can solve privacy leakage problems of user attribute privacy and policy privacy in large universe attribute system. Furthermore, a framework is proposed. The framework combines our ABAC scheme, the Ethereum blockchain and blockchain-based storage system. In this framework, the security characteristics of blockchain technology are used to realize decentralization, tamper-resistant and avoiding single point of failure. Besides, the problems of attribute revocation and policy updating are solved by smart contract on the Ethereum blockchain. Finally, we established an initial implementation on Linux and Rinkeby test network, and the experimental results show that our scheme is feasible.
Blockchain data has become a popular subject in studying various aspects of blockchains including the security of underlying mechanisms. However, the main chain block data, usually available from block explorer services, does not serve as a sufficient source of transaction and block dynamics that are only visible from a large-scale event measurement. In this paper, the transaction and block arrival events of the two popular public blockchains, i.e., Bitcoin and Ethereum, are measured to investigate the hidden dynamics of blockchain networks. We share our key findings and security implications including a false universal assumption of previous mining related studies and an invalid transaction propagation problem that can be exploited to launch a Denial-of-Service attack on a network.
With the development of blockchain technology, the data on the blockchain represented by Bitcoin and Ethereum is exploding. Data represents people's activities, indicating that blockchain has been paid more and more attention. However, many problems are hidden behind so much data, such as security and privacy. Analyzing the data can help to find out the problems and propose methods to improve blockchain. Therefore, in order to make the blockchain well applied to various walks of life, data analysis is quite essential. In this paper, we collected the relevant literature in the field of blockchain data analysis, summarized the current analysis methods, and analyzed the research status from four aspects: security, privacy, performance and prediction of price. Finally, we discussed those research work and forecasted the future trend and challenges in this field, providing some reference for related researchers. We thought that applying machine learning technology to blockchain data analysis will become mainstream in the future.
Victoria L. Lemieux, Artemij Voskobojnikov, Meng Kang
Self-sovereign identity (SSI) systems are novel blockchain-based solutions that are said to shift the control of data records from organizations to individuals. Contrary to conventional blockchains, such as Bitcoin or Ethereum, many SSI systems do not capture on ledger the exchange of transactional data between individuals. By not capturing the exchange of transaction data such SSI systems have the advantage of complying with privacy regulations such as the EU’s General Data Protection Regulations, but, at the same time, have the disadvantage of not capturing evidence that an exchange has happened. Such evidence, however, may be needed for audit and accountability purposes. To achieve these objectives and to preserve privacy, we leverage archival principles to introduce a novel concept of a proof registry, which we define as a set of technical components, data structures, and process flows, that assures that authoritative records offering evidence of transactions is captured, stored, and accessible. This solution solves the compliance and accountability problem while preserving the self-sovereignty and privacy of involved parties.
Land Registry is a simple Dapp based on the ethereum blockchain. It can be used as an alternative to the existing approach. Here the land owner registers the land details along with the land value by providing necessary proofs. Only a registrar or government authority who is registered as the superadmin can do the registration process. Lands coming under a particular area (eg. a village) can register to the system only through the superadmin assigned to that area. The smart contract has been written in such a way that the owner has to transfer his full asset to the buyer and no partial transaction of the asset is allowed. Even though the registration process requires a government authority, the entire process is transparent and the transaction happens between the two clients without any intermediaries.
Smart contracts are the artifact of the blockchain that provides immutable and verifiable specifications of physical transactions. Solidity is a domain-specific programming language with the purpose of defining smart contracts. It aims at reducing the transaction costs occasioned by the execution of contracts on the distributed ledgers such as Ethereum. However, Solidity contracts need to adhere to safety and security requirements that require formal verification and certification. This paper proposes a method to meet such requirements by translating Solidity contracts to Event-B models, supporting certification. To that purpose, we define a restrained Solidity subset and a transfer function that translates Solidity contracts to Event-B models. Besides, we have implemented a translator to improve the conversion efficiency. As a case study, we take advantage of Event-B method capabilities to simulate models at different levels of abstraction and to express the properties of a typical smart contract: Honeypot contract. Lastly, we verify the generated proof obligations of the Event-B model with the help of the Rodin platform.
In recent years, the application of distributed computing has become more and more widespread. Volunteer computing has gained people's favor in terms of only requiring low cost to exchange for a large amount of computing power. Volunteer computing is defined as a kind of distributed computing infrastructure with a large number of computers voluntarily provided by the public. The integrated computing and storage resources are collected and processed by a central server. However, for volunteer computing, security issues are of paramount importance due to the computing source provided by the volunteers. The attack on any computer in the volunteer network may have an impact on the whole network. On the other hand, blockchain is a chain storage structure that has been widely used in recent years, and non-tamperability is one of its most important characteristics. Therefore, this research aims to improve the security and credibility of volunteer computing by using blockchain technology. Accordingly, a novel volunteer network is established on the Ethereum test network named Ropsten. Its performance and consumption are evaluated with a neural network used for computing. The results demonstrate that proper security properties of volunteer computing can be guaranteed by the proposed blockchain-based approach, although a comparatively low time cost and commission consumption is required.
Modern mobile applications often produce decentralized data, i.e., a huge amount of privacy-sensitive data distributed over a large number of mobile devices. Techniques for learning models from decentralized data must properly handle two natures of such data, namely privacy and massive engagement. Federated learning (FL) is a promising approach for such a learning task since the technique learns models from data without exposing privacy. However, traditional FL methods assume that the participating mobile devices are honest volunteers. This assumption makes traditional FL methods unsuitable for applications where two kinds of participants are engaged: 1) self-interested participants who, without economical stimulus, are reluctant to contribute their computing resources unconditionally, and 2) malicious participants who send corrupt updates to disrupt the learning process. This paper proposes Refiner, a reliable federated learning system for tackling the challenges introduced by massive engagements of self-interested and malicious participants. Refiner is built upon Ethereum, a public blockchain platform. To engage self-interested participants, we introduce an incentive mechanism which rewards each participant in terms of the amount of its training data and the performance of its local updates. To handle malicious participants, we propose an audit scheme which employs a committee of randomly chosen validators for punishing them with no reward and preclude corrupt updates from the global model. The proposed incentive and audit scheme is implemented with cryptocurrency and smart contract, two primitives offered by Ethereum. This paper demonstrates the main features of Refiner by training a digit classification model on the MNIST dataset.
Ophthalmology has been an early adopter of cutting-edge digital technology such as artificial intelligence (AI) and could be primed to integrate blockchain architecture in the management of AI and big data analytics. Blockchain technology has seen rapid development and maturation over the past few years. Invented in 2008 by Satoshi Nakamoto (a presumed pseudonym for an anonymous inventor/group of inventors), the blockchain ledger, forming the basis of Bitcoin, was the first decentralized cryptocurrency.1 Since then, different blockchain infrastructures, with different consensus frameworks have emerged, such as Ethereum2 and Hyperledger Fabric.3 In essence, blockchain is a decentralized ledger with immutable properties allowing secure verifiable transfer of data in a peer-to-peer fashion, utilizing a common consensus protocol to prevent single points of failure. A variety of use cases have been developed to harness the advantages of blockchain technology, largely in the financial sector and the business world. However, the health care sector, which requires tight control over confidential medical data, is well-poised to take advantage of the unique characteristics of blockchain technology. This could be of particular relevance in the management of big data and AI research, notably in the field of ophthalmology which has an abundance of numerical data and imagery. In this review, we introduce the basic concepts of blockchain technology, discuss its unique advantages and its use case in ophthalmology. BLOCKCHAIN TECHNOLOGY The concept of blockchain technology is built on a framework of an ever-growing list (or “chain”) of transactions, grouped into units called “blocks”, which in turn are linked to their immediate predecessors by a unique cryptographic “hash value”. Generated from specific mathematical algorithms such as the SHA-256 (256-bit Secure Hash Algorithm), hash values are characterized by their deterministic value, as well as pre-image and collision resistance, serving as “fingerprint” of a block and its content. Blockchain platforms depend on “consensus protocols” to approve, record, and validate each transaction. A consensus protocol is a form of rules to reach a common majority agreement on the present state of the ledger within a blockchain network. Once a consensus has been reached, the block containing the log of the data is added into the “chain”, and shared with every stakeholder in the network, known individually as “nodes”. The archetypal example would be a bitcoin transaction. When the transfer of coins is initiated between 2 parties, miners compete for the right to record the transaction by solving a difficult mathematical puzzle, expanding precious energy in the process. The node that solves the puzzle first is recognized for its efforts and given the right to record the transaction, hence reaching a consensus. The common transparency and traceability of each individual cryptoasset transaction prevent duplicative transactions, solving the well-documented “double-spend” problem—an inherent flaw in digital asset schemes where the same single-use digital token is spent more than once. This forms the basis of a hack-resistant, immutable distributed ledger. Current blockchain platforms can be broadly dichotomized into two main groups—permissionless or permitted (Fig. 1). Permissionless blockchain platforms such as Bitcoin and Ethereum provide unrestricted access to the public. Conversely, permitted platforms such as Hyperledger Fabric will retain a central approving authority. Hybrid or consortium-based blockchain platforms are derived from a combination of these two architectures, resulting in partial centralization with participation restricted through the private network. Table 1 provides a summary of the terms and definitions unique to blockchain technology.FIGURE 1: Permissionless blockchain targets at implementing a common platform that can involve anyone with anonymous identity into the network, which often comes with built-in currency and is public, open and fully decentralized; Permitted blockchain engages a few organizations with known identity (forming a consortium) that require collaborative operations to realize specific business logics, which are co-hosted/co-managed by the consortium. TABLE 1 - Summary of Common Terms and Definitions in Blockchain Technology Ledger Book or computer file for recording and totaling transactions Blocks Transactions cumulated and recorded into fixed sized blocks. Each block contains timestamp, a unique hash, the hash of the previous block and transaction data 23 Chain List of blocks linked cryptographically23 Hash Cryptographically generated fixed length string of values, based on random input of transactions/data, that is easily verifiable23 Mining Validating of transactions and recording onto the decentralized ledger24 Byzantine generals problem Computer science description of a situation where involved parties must reach a decision to avoid failure, but some parties are dishonest or malicious25,26 Consensus protocol A form of rules to reach a common majority agreement on the present state of the ledger within a blockchain network23 Fault tolerance Level that allows a system to continue operating normally in the event of failure of some components or nodes27 Nodes Communicating points that may perform different functions on the blockchain platform23 Permissioned Access control layer governed by a central authority23 Permissionless Public access without restriction to participation23 Hybrid/Consortium Blockchain platform governed by multiple organizations23 Immutable Unchangeable ledger23,24 Cryptoasset Digital assets that utilizes cryptography as a medium for transactions24 Smart contracts Automated executions of complex transactions based on computational logic when certain conditions are met24 Asymptotic security Security if and only if the adversary's advantage is a negligible function of the security parameters i.e. a secure scheme that is conditionally proven to be harder than any polynomial for the attacker to break28 Deterministic Same operation performed by different nodes will produce the same result29 Pre-image resistance Computationally infeasible to derive the original transaction data from a given hash function30 Collision resistance Computationally infeasible for two distinct inputs to result in the same hash output23 APPLICATIONS OF BLOCKCHAIN TECHNOLOGY Apart from application in finance, blockchain technology could be highly relevant in other industries such as health care, insurance, and supply chain management4 due to the inherent key advantages: immutable transaction records, decentralized peer-to-peer transaction, costless verification, reduction of incumbent market power, avoidance of single point of failure, and smart contracts – automated executions of complex transactions based on computational logic. Although it has yet to achieve mass-market adoption, blockchain technology has been heavily touted as a potential general-purpose technology, gaining traction across multiple industries such as finance, hedge fund management, and supply chain management.4 Years of reliance on antiquated digital systems have resulted in cumbersome, inefficient and resource-intensive processes. This results in significant resource wastage, and also renders systems susceptible to fraudulent attacks or system-wide failure.5 Financial institutions are therefore innovating with blockchain technology to address these concerns. Another frontrunner in the adoption of blockchain technology is supply chain management.6–8 The complex multi-faceted nature of supply chains places heavy demands on proper record keeping, quality control, and transaction monitoring. Current supply chains rely on centralized intermediation entities with little transparency across the entire chain. The supply chain thus suffers from vulnerability towards malicious modification or human errors and poor accountability. The application of blockchain technologies has the potential to disrupt the industry by effectively eliminating the trust required between involved parties. By transferring the onus of trust onto the algorithm and its immutable record, the issues associated with the need of verifying intermediaries can be eliminated.9 BLOCKCHAIN TECHNOLOGY IN HEALTH CARE In a 2019 technical report by International Telecommunication Union,10 the Telecommunication Standardization Sector identified the health care sector as one of the key sectors that could be a beneficiary of blockchain technology. The devastating COVID-19 pandemic, while unfortunate, has provided a significant impetus to accelerate this process.11 It is important to note that traditional distributed database management system (DDMS) can support the secure transfer of health data through encryption and data masking with the acceptance of several significant flaws: potential single point of failure, subject identification and tampering of data. In comparison, blockchain armed with asymmetric encryption and hash values can surmount these challenges albeit with a measured sacrifice of throughput rate and latency. At this point, adoption of blockchain in health care is still in its infancy with multiple proof of concepts but a limited selection of commercially available health care blockchain platforms. At present, most of these platforms are focused on electronic medical record management, such as patient-controlled electronic medical record (EMR) accessibility and immutable recording of clinical records. One of the most well-known is Medicalchain (Medicalchain SA, London) which is built on the Hyperledger Fabric architecture. Medicalchain's12 primary focus is to assign EMR access-granting rights to the patient, thereby returning control back to the patient. It provides a self-contained incentive system by rewarding data-sharing behavior with its native token (MedToken) which can be utilized in exchange for relevant services. Another example is the national rollout of the e-Estonia health care EMR built on Keyless Signature Infrastructure blockchain technology, allowing for verification of integrity of accessed medical records as well as immutable record of access logs.13 Since its inception in 2016, it has enabled digital permeation with 99% of health data digitized securely and handling up to 1.8 million patient queries every month, made possible through decentralized authenticated sharing of data. Notable examples of data sharing on the e-Estonia platform include physician retrieval of time-critical patient information during emergencies as well as patient monitored access of their medical data.14 Separately, blockchain could potentially be a disrupting technology in the health care supply chain and insurance field. The decentralized nature of blockchain provides a platform for cross-institution and cross-border collaboration, providing transparent check and balance to all stakeholders. This gave rise to initiatives such as Pharmaledger—a European Union blockchain consortium involving 12 global pharmaceutical firms such as Pfizer, Novartis and GSK.15 In the health care insurance field, peer-to-peer transaction of cryptographically-secured sensitive information between stakeholders would remove costly intermediaries and improve efficacy. Fraudulent activities would also be deterred by the algorithm and the immutable log. This could transform the entire patient-customer journey, from verifiable health declaration during policy purchase to transparent and traceable claims process. It is thus becoming apparent that the trust-less verification and immutable audit trail afforded by blockchain is exceedingly crucial for innovative applications in health care. BLOCKCHAIN TECHNOLOGY IN OPHTHALMOLOGY Ophthalmology as a field has been an early adopter of new evolving technologies, in particular the application of AI and deep learning (DL) for the automated analysis of medical images, such as retinal images and optical coherence tomography scans.16–18 DL in medicine (and ophthalmology), an area of active research, is highly reliant on the availability of large high-quality datasets as well as rigorous model validation and testing. However, the management of diverse datasets from different countries and centers for training and testing of algorithms in these studies poses significant challenges. This is attributable to extensive restrictions due to concerns over data security and patient confidentiality, preventing honest transfer of research medical data to support collaborative efforts.19 In addition, proper research community oversight over the multitude of novel AI and DL systems is unattainable due to a lack of transparency regarding model validation and testing. Recognizing these challenges, in a recent study, Tan et al20 proposed a permission blockchain-enabled platform (based on Hyperledger Fabric) to assist with the development and validation of DL algorithms to tackle the global myopia epidemic. They provide proof-of-concept, using this blockchain-enabled platform for secure handling of data transfer, model sharing, and auditable reporting of model validation and testing results across 3 separate sites in 2 countries, in the development of robust DL algorithms for automated detection of myopic macular degeneration and high myopia from retinal images. They suggest that this blockchain-based solution for the management of research datasets and model testing results provides advantages of data integrity and immutability, as well as automation in data consistency and a shared ledger promoting easier collaboration. They also suggest that widespread adoption of this novel method could increase validity and transparency of AI studies in medicine, and may allow health regulators (eg, US Food and Drug Administration) a means of effectively auditing and verifying the diagnostic performance of AI algorithms for regulatory approval. In conjunction, the immutable transaction log replicated across all nodes provides the ideal digital infrastructure to track each iteration of the AI-model training, improving collaborative efficiency and trust. Further applications of blockchain in the health care industry could likewise impact the field of ophthalmology (Table 2). Supply chain transformation is particularly valuable for perishable products21 and would likely play a significant role in health care, where tight monitoring of labile high-value medications is crucial to guarantee safety and efficacy. Scarce or costly products that require highly regulated storage conditions would be ideal candidates, examples which include total parenteral nutrition, mRNA COVID vaccines, intra-vitreal anti-vascular endothelial growth factors (anti-VEGF), blood products or biologics. During the COVID-19 pandemic, Lin et al established a blockchain-based platform to provide virtual clinical service for ophthalmology patients. They proposed a proof-of-concept to verify and efficiently monitor online prescriptions, creating a blockchain-based online pharmacy for prescription renewals and remote drug delivery.22 The significance of this lies in the fact that telemedicine is a highly visual-dependent service, making it particularly well-suited for visual-oriented specialties like ophthalmology. Another potential application of blockchain in health care, which will be highly relevant in ophthalmology, is the use of blockchain technology to monitor and improve patient treatment adherence as well as to automate medication support programs. This would be particularly valuable for high-cost treatment regimes that require considerable patient compliance, such as recurring intra-vitreal anti-VEGF treatments. TABLE 2 - Blockchain Characteristics and Potential Use Case Immutability31–38 AI algorithm training and testing, health care insurance, data transfer, medication distribution supply chain, patient support programme, medical licensing, patient disease monitoring, clinical drug trial Traceability and provenance31,32,34,37,39 Data transfer, medication distribution supply chain, patient support programme, medical licensing De-centralized data security33–37 Patient support programme, health care insurance, patient disease monitoring, data transfer Peer to peer transaction31–35,37 Health care insurance, data transfer, patient support programmes Cost-less verification33,35,37–40 Health care insurance, patient disease monitoring, patient support programmes, medication distribution supply chain, clinical drug trial Smart contracts/De-centralized autonomous organisations33,35,40,41 Medication distribution supply chain, patient support programmes, health care insurance, Anonymity31,32 Data transfer, patient support programme CHALLENGES Although we expect greater innovative and disruptive use cases for blockchain technology in ophthalmology to materialize, implementation and integration could remain a challenge. First, selecting the appropriate blockchain platform will be critical which, under most health care circumstances, will exclude permissionless blockchains. Researchers, clinicians, and hospital administrators will need to be cognizant of the clinical and operational workflow changes required if blockchain is adopted. Second, mindsets deeply rooted in the traditional DDMS will need to be changed. In addition, switching from DDMS to blockchain will entail greater digital automation, integration of application programming interfaces (API) and distributed applications (Dapps), off and on-chain event connection, wholesale conversion to digitized data collection and upgrading of the information technology infrastructure. Third, there are significant costs. Investments will be required for dedicated digital hardware, networking and storage overheads as well as maintenance. Fourth, from a clinician and provider perspective, immutability of the blockchain platform will prevent amendments of erroneous entries whereas latency could be a source of frustration when contrasted against highly efficient traditional client-server databases. Fifth, blockchain relies on a flawless algorithm to create an asymptotic security, hence cryptographic flaws could leave vulnerabilities within the platform. Finally, data security issues need to be addressed. The decentralized peer-to-peer transaction could potentially compromise patient's data if it has not been appropriately anonymized. The sensitive nature of health care data hence demands that the algorithm undergo extensive trials and penetration tests to guarantee that the patient's privacy and confidentiality is upheld. Finally, the democratization of data sharing at the patient-level might not materialize. It is highly possible that the lure of incentives would be nullified by heightened senses towards privacy preservation, hence failing to convince and motivate patients to proactively share their data. Such inertia could be further compounded by a lack of understanding and trust of the reliability of blockchain platforms. It might be more realistic to consider monetization of big data in an institutional level, yet even that faces significant resistance for fear of privacy breaches or the loss of autonomy over valuable data (Supplementary table: https://links.lww.com/APJO/A87). CONCLUSIONS AND FUTURE DIRECTIONS In conclusion, the health care sector faces a pressing need for new digital technologies that allow secure and efficient sharing of data to address the inefficiencies and demands in current systems. There is increasing recognition that blockchain technology could deliver the novel digital platforms that are required to address these requirements. In the field of ophthalmology, blockchain technology can help to monitor data and results integrity, greater research to support AI In addition, and algorithms are likely to further improve the and of blockchain for widespread health care applications care.
Public blockchains have spurred the growing popularity of decentralized transactions and smart contracts, especially on the financial market. However, public blockchains exhibit their limitations on the transaction throughput, storage availability, and compute capacity. To avoid transaction gridlock, public blockchains impose large fees and per-block resource limits, making it difficult to accommodate the ever-growing high transaction demand. Previous research endeavors to improve the scalability and performance of blockchain through various technologies, such as side-chaining, sharding, secured off-chain computation, communication network optimizations, and efficient consensus protocols. However, these approaches have not attained a widespread adoption due to their inability in delivering a cloud-like performance, in terms of the scalability in transaction throughput, storage, and compute capacity. In this work, we determine that the major obstacle to public blockchain scalability is their underlying unstructured P2P networks. We further show that a centralized network can support the deployment of decentralized smart contracts. We propose a novel approach for achieving scalable decentralization: instead of trying to make blockchain scalable, we deliver decentralization to already scalable cloud by using an Ethereum smart contract. We introduce Blockumulus, a framework that can deploy decentralized cloud smart contract environments using a novel technique called overlay consensus. Through experiments, we demonstrate that Blockumulus is scalable in all three dimensions: computation, data storage, and transaction throughput. Besides eliminating the current code execution and storage restrictions, Blockumulus delivers a transaction latency between 2 and 5 seconds under normal load. Moreover, the stress test of our prototype reveals the ability to execute 20,000 simultaneous transactions under 26 seconds, which is on par with the average throughput of worldwide credit card transactions.
With the increasing maturity of encryption algorithms, digital currency emerges as the times require. Blockchain is a highly attractive candidate for developing digital currency. A better understanding of the mechanisms for Blockchain will benefit the comprehensive future development of Blockchain. In the current study, we observed the data and transaction structure of Bitcoin and Ethereum. Therefore, Our study compared the existing structure of Bitcoin and Ethereum and analyzed the reasons for the change of the Blockchain, providing insights for the future development of the Blockchain. The results of this study indicate that he future development of Blockchain will increasingly meet the increasing number of users, lower the threshold for users, meet increasingly cumbersome functional requirements, expand the scope of blockchain applications, and improve security.
Rawya Mars, Amal Abid, Saoussen Cheikhrouhou, Slim Kallel
Ethereum is a blockchain-based platform that pro-vides a global computational infrastructure to run smart contracts. In order to assign a cost to smart contract and transaction execution, the Ethereum Blockchain adopts a gas-based metering approach which is designed to motivate miners to operate the network and protect it against attacks. More precisely, miners receive fees from all transactions included in the mined block in addition to the mining reward. Hence, the higher the gas price in the transactions, the higher the fee paid to the miner will be, resulting in faster selection and execution of higher priced gas transactions. Therefore, an Ethereum transaction sender is exposed to the non-trivial task of having to choose an optimal gas price, as underpaying likely results in a transaction not being picked by miners, whereas overpaying leads to superfluous costs. This paper provides recommendation approach that proposes an appropriate gas price to users. More precisely, it investigates different approaches of forecasting algorithms applied for gas price predictions for the next block in Ethereum Blockchain. The gas price is predicted using the Prophet model and the deep learning models, Long-Short Term Memory (LSTM) and Gated Recurrent Unit (GRU). It also aims to compare these approaches with the most used gas price oracles. An evaluation of the obtained results show that the LSTM and GRU proposed models outperform Prophet model as well as the gas price oracle Geth. In this case, LSTM and GRU provide a low mean squared error (MSE) of 0,008 whereas Geth gives an MSE of 0.016 and Prophet gives an MSE of 0.014.
Ridesharing is a transportation strategy that allows drivers to share their trips with other people which results in less travel expenses. It also minimizes traffic congestions and carbon emissions. Currently, most of the existing ride-sharing services rely on a central third party, like Uber, Ola, Didi which charges high service fees. In this paper, we are using blockchain technology to build a smart ride-sharing platform - CypherCab. All the services from registering as a driver, to using this platform for ridesharing will be written directly to the blockchain distributed ledger. Utilizing the decentralized nature of blockchain, the data stored in the blocks will be stored in a distributed ledger, hence removing the dependency on a central third-party server. Moreover, blockchain enables us to remove intermediaries and allows direct transactions between the driver and passengers. In this paper, we have implemented a prototype using smart contracts in the Ethereum network and Ganache test network.
This study examines the potential of cryptocurrencies such as Bitcoin, Ethereum, ripple, tether, and Bitcoin cash as hedging instruments and a safe haven for the Indonesian capital market, especially during the Covid-19 pandemic era. Now, Indonesia's capital market condition is in turbulence. The benefit of this research is to help the investors make decisions on which cryptocurrencies can be an instrument hedge and safe haven in this Covid-19 pandemic era for Indonesia Stock Exchange (IDX). The data used in this study are data on the closing price of the Composite Stock Price Index (CSPI), bitcoin (BTC), Ethereum (ETH), ripple (XRP), tether (USDT), and bitcoin cash (BCH) from January 3 to June 16, 2020. Data analysis used Generalized AutoregressiveConditional Heteroscedasticity (GARCH) and Quantile Regression (QREG). This study found that Bitcoin, Ethereum, tether, and Bitcoin cash can act as a hedge, but only the ripple cannot act as a hedge. Bitcoin, Ethereum, ripple, tether, and bitcoin cash cannot act as a safe haven when the Indonesian capital market was getting extreme, like during the Covid-19 pandemic era. The roles of Bitcoin, Ethereum, ripple, tether, and bitcoin cash as safe havens will fade when conditions in the Indonesian capital market become more extreme. This research can be used as a reference for investors for their investments by looking top four cryptocurrencies as a hedging instrument. However, in severe conditions such as during the Covid-19 Pandemic, the top five cryptocurrencies cannot be used as a safe haven, as revealed in this study.
In recent years, cryptocurrency or virtual currency is becoming an essential medium of exchange in consumer and domestic trading. Nevertheless, the trading values of cryptocurrency compared to real money are very uncertain and can change dramatically. This article is aimed to assess the uncertainty or volatility of cryptocurrencies, mostly on Bitcoin. In the digital currencies market, Bitcoin is a widely accepted currency. Other digital currencies of the market may influence Bitcoin. For example, Ethereum, Litecoin, Zcash, Monero, Dash and Ripple have a positive impact on Bitcoin. Previous research only focuses on Bitcoin and other markets such as stock markets, energy markets, and exchange rates. However, here we focus on interlinkages and volatility dynamics within cryptocurrency markets by applying some econometrics models. In this article, we have shown that the relationship between Bitcoin and other currencies can be modelled in the ARCH, GARCH, VAR and MGARCH framework. Forecast values of the GARCH (3,3) model are given very close to the original data. VAR stability result shows that the model is stable. Using the CCC, VCC, and DCC of the MGARCH model on daily returns from 1st January 2017 to 15th March 2019, we found significant volatility and strong correlations between the variables.
Jun 30, 2021·International Journal of Contemporary Economics and Administrative Sciences - International Journal of Contemporary Economics and Administrative Sciences
<strong>Abstract </strong> Blockchain technology is becoming more and more important and new usage areas are emerging every day. However, the most fundamental one of these usage areas is cryptocurrencies, which led to the emergence of blockchain technology. Cryptocurrency transfers are made possible with mining. Although there are many cryptocurrencies available today, a lot of them use Ethereum-based blockchain technology. The choice of the most optimal graphics card (GPU; Graphics Processing Unit) in cryptocurrency mining is very important for the efficiency and profitability of the mining operations to be performed. Since this decision problem depends on more than one criterion, it should be handled using Multiple-Criteria Decision-Making Methods (MCDM). Accordingly, the study focused on the mining of Ethereum-based cryptocurrencies and the selection of the optimal GPU to be used in mining with linear BWM-TOPSIS. As a result of the study, a model is presented in which miners can choose the most efficient GPU for them and the optimal GPU as of January 2020 has been determined.
This study explores the bubble behavior in the prices of top five cryptocurrencies (i.e., Bitcoin, Ethereum, Ripple, Stellar, and Tether) using daily data of the closing level at the COVID-19 pandemic, covering the period from January 2, 2020 to January 2, 2021. The testing procedure of the bubble behavior in selected cryptocurrencies prices is investigated by two methodologies. Those covers the test statistics originated by the Supremum Augmented Dickey-Fuller (SADF) (Phillips et al., 2011) and Generalized Supremum Augmented Dickey-Fuller (GSADF) (Phillips et al., 2015) to define several bubble periods. The empirical results emphasize that bubble behavior is not a diverse and stable feature of Bitcoin, Ethereum, Ripple, and Stellar prices, except the Tether prices, which point out the emergence of a potential crisis in the digital assets market through an increasing degree of financial instability.
Blockchain technologies and smart contracts are getting more attention for potential smart grids applications as they are able to decentralize the data management in a secure and transparent way. In this work, a smart contract deployed in a simulated Ethereum blockchain is used to coordinate the decentralized solution of the Economic Dispatch (ED) problem of Distributed Generation (DG) units. The distributed optimization problem is first formulated and solved using the Alternating Directional Method of Multipliers (ADMM) and then a smart contract plays the role of the decentralized coordinator and data aggregator. Results from the combined simulation of the method are provided through a variety of scenarios, that investigate the efficacy and practical applicability of the method.
Xuan Chen, Shujuan Tian, Kien Nguyen, Hiroo Sekiya
With data transparency and immutability, the blockchain can provide trustless and decentralized services for Internet of Things (IoT) applications. However, most blockchain-IoT networks, especially those with a private blockchain, are built on top of an infrastructure-based wireless network (i.e., using Wi-Fi access points or cellular base stations). Hence, they are still under the risk of Single-Point-of-Failure (SPoF) on the network layer, hindering the decentralization merit, for example, when the access points or base stations get failures. This paper presents an Optimized Link State Routing (OLSR) protocol-based solution for that issue in a private blockchain-IoT application. By decentralizing the underlying network with OLSR, the private blockchain network can avoid SPoF and automatically recover after a failure. Single blockchain connections can be extended to multiple ad hoc hops. Services over blockchain become flexible to fit various IoT scenarios. We show the effectiveness of our solution by constructing a private Ethereum blockchain network running on IoT devices (i.e., Raspberry Pi model 4) with environmental data sensing (i.e., Particular Matter (PM)). The IoT devices use OLSR to form an ad hoc network. The environment data are collected and propagated in transactions to a pre-loaded smart contract periodically. We then evaluate the IoT blockchain network’s recovery time when facing a link error. The evaluation results show that OLSR can automatically recover after the failure. We also evaluate the transaction-oriented latency and block-oriented latency, which indicates the blocks have a high transmission quality, while transactions are transferred individually.
At present, the supply chain finance industry has been in a vigorous development trend, but its development is still hindered by the reasons such as information opacity and information asymmetry. This paper mainly studies the application of blockchain technology in supply chain finance for Beibu Gulf region. According to the industry characteristics of supply chain finance, the blockchain technology is integrated with supply chain finance to construct the supply chain finance alliance architecture based on the blockchain technology and the underlying model and composition technology of Ethereum blockchain system applicable to supply chain finance. Considering the actual operation situation of supply chain finance platform blockchain, using the principal-agent model and incentive theory, supply chain finance accounts receivable mode, for example, the design blockchain financial platform service provider with the core enterprises of supply chain between the incentive mechanism, promote blockchain technology and supply chain finance better ground test, solve the current financial supply chain development bottleneck.
Software-defined wide-area network (SD-WAN) is an emerging and advanced networking platform extending software-defined networking (SDN) across multiple networking domains. Because SD-WAN manages the data plane in the networking domains separated by the public Internet, SDWAN provides a distinct environment and challenges from SDN, including greater risks for the security threats injecting control plane communications from attackers residing outside of the SDN domain. We design and build blockchain-coordinating controllers (BCC) to secure control communications of the SD-WAN controller network formed by the distributed controllers spread across multiple domains. BCC provides resiliency against the security threats in the control plane where an attacker compromises controller communications to manipulate the coordination and the operations of the other controllers. More specifically, BCC provides secure control communications even when up to n controllers’ networking credentials are compromised. BCC is also designed for modularity so that it applies generally across the controller implementations. We prototype BCC using Ethereum and smart contract on CloudLab to validate its effectiveness and efficiency. We experiment on geographically separate nodes on CloudLab and show that BCC achieves the distributed consensus at sub-second level for certificate/key distribution and for network-wide control communication synchronization.