Cryptocurrency is a new phenomenon in investment industry in particular and financial world in large. The opportunities and threats come one over another in cryptocurrency debate that left people in perplex state whether to accept or reject the currency. In other view, it also brings advantages and inevitable disadvantages since it is operated online that vulnerable to number of threats and danger. This paper tries to examine maqasid views on this currency relying on SWOT analysis then will be viewed on the mirror of maslahah dan mafsadah as main pillars in maqasid al-syari’ah. As a result, this issue needs to be studied further since the maslahah and mafsadah sometime interchange the roles as particular, general maslahah and its counterparty since the system is always been designed for the benefits, that yet created the negative implication simultaneously. Furthermore, this innovation could be designed followed the desire of designers with dynamics structure in fulfilling the market’s needs.
In this paper, a Blockchain-driven platform for supply chain finance, BCautoSCF (Zhi-lian-che-rong in Chinese), is introduced. It is successfully established as a reliable and efficient financing platform for the auto retail industry. Due to the Blockchain built-in trust mechanism, participants in the supply chain (SC) networks work extensively and transparently to run a reliable, convenient, and traceable business. Likewise, the traditional supply chain finance (SCF), partial automation of SCF workflows with fewer human errors and disruptions was achieved through smart contract in BCautoSCF. Such open and secure features suggest the feasibility of BCautoSCF in SCF. As the first Blockchain-driven SCF application for the auto retail industry in China, our contribution lies in studying these pain points existing in traditional SCF and proposing a novel Blockchain-driven design to reshape the business logic of SCF to develop an efficient and reliable financing platform for small and medium enterprises (SMEs) in the auto retail industry to decrease the cost of financing and speed up the cash flows. Currently, there are over 600 active enterprise users that adopt BCautoSCF to run their financing business. Up to October 2019, the BCautoSCF provides services to 449 online/offline auto retailors, three B2B asset exchange platforms, nine fund providers, and 78 logistic services across 21 provinces in China. There are 3296 financing transactions successfully completed in BCautoSCF, and the amount of financing is ¥566,784,802.18. In the future, we will work towards supporting a full automation of SCF workflow by smart contracts, so that the efficiency of transaction will be further improved.
Nathan Borggren, Hyoung-yoon Kim, Lihan Yao, Gary Koplik
Monero is a popular crypto-currency which focuses on privacy. The blockchain uses cryptographic techniques to obscure transaction values as well as a `ring confidential transaction' which seeks to hide a real transaction among a variable number of spoofed transactions. We have developed training sets of simulated blockchains of 10 and 50 agents, for which we have control over the ground truth and keys, in order to test these claims. We featurize Monero transactions by characterizing the local structure of the public-facing blockchains and use labels obtained from the simulations to perform machine learning. Machine Learning of our features on the simulated blockchain shows that the technique can be used to aide in identifying individuals and groups, although it did not successfully reveal the hidden transaction values. We apply the technique on the real Monero blockchain to identify ShapeShift transactions, a cryptocurrency exchange that has leaked information through their API providing labels for themselves and their users.
A variety of correlations are detected in the Monero blockchain. The joint distribution of the time-since-last-transaction between elements of pairs of RingCTs is enhanced in comparison with the product of the marginal distributions. Similarly there is an enhancement in the joint distribution of the hour timestamps between the same pairs. Lastly, we find another enhancement when the correlation is measured between the hour timestamps of the transaction itself and the elements of the RingCTs. We calculate some adjustments to the probabilities of which input in a RingCT is real, providing an additional heuristic to denoising the Monero blockchain.
Despite the popularity and practical applicability of blockchains, there is very limited work on the theoretical foundation of blockchains: The lack of rigorous theory and analysis behind the curtain of blockchains has severely staggered its broader applications. This paper attempts to lay out a theoretical foundation for a specific type of blockchains---the ones requiring basic authenticity from the participants, also called \textit{permissioned blockchain}. We formulate permissioned blockchain systems and operations into a game-theoretical problem by incorporating constraints implied by the wisdom from distributed computing and Byzantine systems. We show that in a noncooperative blockchain game (NBG), a Nash equilibrium can be efficiently found in a closed-form even though the game involves more than two players. Somewhat surprisingly, the simulation results of the Nash equilibrium implies that the game can reach a stable status regardless of the number of Byzantine nodes and trustworthy players. We then study a harder problem where players are allowed to form coalitions: the coalitional blockchain game (CBG). We show that although the Shapley value for a CBG can be expressed in a more succinct form, its core is empty.
We address the problem of fairness and transparency in online marketplaces selling digital content, where all parties are not actively participating in the trade. We present the design, implementation and evaluation of VADER, a highly scalable solution for multi-party fair digital exchange that combines the trusted execution of blockchains with intelligent protocol design and incentivization schemes. We prototype VADER on Hyperledger Fabric and extensively evaluate our system on a realistic testbed spanning five public cloud datacenters, spread across four continents. Our results demonstrate that VADER adds only minimal overhead of 16% in median case compared to a baseline solution, while significantly outperforming a naive blockchain based solution that adds an overhead of 764%.
Being a decentralized system makes Blockchain a suitable technology solution in many cases. The Smart Energy domain has the potential to benefit from the use of Blockchain, by improving data and transaction management, through applications such as peer-to-peer energy trading, grid enhancement, and electric vehicle support. Many researchers have proposed models and prototypes of blockchain-based applications, which are expected to improve the performance of smart energy systems. In this report, a qualitative literature review was performed to look into a sample of these application proposals and to try to identify the impacts of blockchain technology in Smart Energy. This resulted in the discovery of both positive and negative factors. The beneficial factors include increased security, improved data privacy, data transparency and immutability, removal of third-party control and trust, ubiquitous solution, and greater data accessibility. The list of challenges includes limited scalability and speed, off-chain support requirement, high establishment and maintenance cost, and requiring further practical tests. One of the interesting findings is that the impact of Blockchain technology as to whether it may increase or decrease transaction costs is still unclear. Finally, the paper recommends that a future study may focus on economic feasibility and transaction costs, and ascertain which Smart Energy cases and application designs are more appropriate for Blockchain technology.
Rafael Páez, Manuel Pérez, Gustavo Ramirez Espinosa, Juan Montes · 5 authors
This paper proposes an architecture for biometric electronic identification document (e-ID) system based on Blockchain for citizens identity verification in transactions corresponding to the notary, registration, tax declaration and payment, basic health services and registration of economic activities, among others. To validate the user authentication, a biometric e-ID system is used to avoid spoofing and related attacks. Also, to validate the document a digital certificate is used with the corresponding public and private key for each citizen by using a user’s PIN. The proposed transaction validation process was implemented on a Blockchain system in order to record and verify the transactions made by all citizens registered in the electoral census, which guarantees security, integrity, scalability, traceability, and no-ambiguity. Additionally, a Blockchain network architecture is presented in a distributed and decentralized way including all the nodes of the network, database and government entities such as national register and notary offices. The results of the application of a new consensus algorithm to our Blockchain network are also presented showing mining time, memory and CPU usage when the number of transactions scales up.
Open access
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
This demo abstract introduces a new light-weight programming language koa which is suitable for blockchain system design and implementation. In this abstract, the basic features of koa are introduced including working system (with playground), architecture, and virtual machine operations. Rum-time execution of software implemented by koa will be presented during the session.
In this paper, we develop a new framework called blockchain-based Radio Frequency (RF)-powered backscatter cognitive radio network. In the framework, IoT devices as secondary transmitters transmit their sensing data to a secondary gateway by using the RF-powered backscatter cognitive radio technology. The data collected at the gateway is then sent to a blockchain network for further verification, storage and processing. As such, the framework enables the IoT system to simultaneously optimize the spectrum usage and maximize the energy efficiency. Moreover, the framework ensures that the data collected from the IoT devices is verified, stored and processed in a decentralized but in a trusted manner. To achieve the goal, we formulate a stochastic optimization problem for the gateway under the dynamics of the primary channel, the uncertainty of the IoT devices, and the unpredictability of the blockchain environment. In the problem, the gateway jointly decides (i) the time scheduling, i.e., the energy harvesting time, backscatter time, and transmission time, among the IoT devices, (ii) the blockchain network, and (iii) the transaction fee rate to maximize the network throughput while minimizing the cost. To solve the stochastic optimization problem, we then propose to employ, evaluate, and assess the Deep Reinforcement Learning (DRL) with Dueling Double Deep Q-Networks (D3QN) to derive the optimal policy for the gateway. The simulation results clearly show that the proposed solution outperforms the conventional baseline approaches such as the conventional Q-Learning algorithm and non-learning algorithms in terms of network throughput and convergence speed. Furthermore, the proposed solution guarantees that the data is stored in the blockchain network at a reasonable cost.
zkSNARKS can be described as zero-knowledge: No secret information is revealed by the proof; Succinct: The size of the proof that is generated is small; Non-interactive: no challenge-response protocol; and ARgument of Knowledge: It is computationally intractable for the prover to produce a fake proof.
Investigation of the security of the Ethereum Ropsten test network in connection with the Echosafe application used to record verbal contracts developed by Blocksafe Kft
Open access
Hungarian Social, Economic and Educational Studies
Hard forks. The first tax is levied on the profit made from the receipt of forked coins, and the second tax is levied on the profit made from the disposition of forked coins. At the same time, a concrete proposal is provided for the applicable coin valuation, tax basis, holding period, and tax rate for the two prongs. The proposed framework is closest to the nature of cryptocurrency hard forks and considers various practical concerns, such as the inefficiency of the cryptocurrency market, the indirect possession of forked coins through third-party exchanges, and the fluctuating trading prices of forked coins when determining the valuation, tax basis, and holding period. This proposal not only provides clarity for taxpayers in filing tax returns and fulfilling tax obligations, but it also relieves the potential tax deferral and tax evasion problems that arise after a cryptocurrency hard fork. Practical significance: the main provisions and conclusions of the article can be used in scientific, pedagogical and law enforcement activities when considering the issues related to taxation regime of cryptocurrency hard forks.
In this article, we empirically examine the cryptocurrency market reaction to china prohibiting initial coin offerings, on the 4 September 2007 for the 100 largest cryptocurrencies. The announcement has a significant negative but temporary impact on cryptocurrency returns and liquidity.
Paul B. Romesser, Grace L. Smith, Christopher H. Crane
Locally advanced rectal cancer (LARC) treatment traditionally includes preoperative chemoradiation, radical surgery, and postoperative chemotherapy (1). Although highly effective, this standard leads to substantial rates of long-term morbidity, including permanent colostomy, low anterior resection syndrome, urinary dysfunction, and sexual dysfunction (1–3). Patients with mid- and low rectal cancers who achieve a clinical complete response (cCR) present a dilemma to the thoughtful surgeon because the preoperative discussion must include the very real possibility that the specimen would not contain cancer. Patients’ refusal of radical surgery and surgeons’ desire to balance oncologic outcomes with quality of life (QOL) have led investigators to embark on organ preservation strategies in complete responders. Although the nonoperative management (NOM, also known as watch-and-wait) strategy has been increasingly accepted, radical surgery is still considered the standard, and randomized evidence determining the comparative effectiveness of NOM remains to be established. In this issue of the Journal, Miller and colleagues evaluate other important considerations of effectiveness, specifically the cost-effectiveness and quality-adjusted survival of NOM (4). The NOM strategy was initially introduced by Habr-Gamma and colleagues in 2004 (5). Patients with LARC who achieved a substantial clinical response to chemoradiation were offered NOM if they were agreeable to stringent monthly clinical reassessments (5). The 5-year overall survival and disease-free survival of the 72 patients who underwent NOM were 100% and 92%, respectively (5). Importantly, all of the patients with regrowth of the primary tumor were successfully salvaged with mesorectal excision. Although initially controversial, this pioneering work provided proof of principle that the majority of patients who achieve a cCR to preoperative chemoradiation can be managed without radical surgery. Multiple groups have subsequently reported 70–80% durable local disease control in LARC complete responders on NOM, and close surveillance has led to timely salvage surgery with no clear oncologic disadvantage (6–13). Miller and colleagues developed a decision-analytic Markov model to evaluate cost-effectiveness of this strategy compared with standard radical surgery (4). Importantly, with respect to clinical interpretation and application, this analysis includes only patients who have achieved cCR to neoadjuvant therapy. NOM was found to have incremental cost savings of $28 500 and $32 100 and incremental benefit in quality-adjusted-life years of 0.527 and 0.601 compared with low anterior resection and abdominoperineal resection, respectively. The main cost differences were predominantly driven by the upfront cost of surgery, which was absent or deferred in patients managed with NOM and statistically significantly offset the added cost of enhanced screening. Results were presented from a US payer perspective and validate similar findings demonstrating cost-effectiveness of NOM from a UK payer perspective (14). The model by Miller and colleagues (4) further suggests quality-adjusted survival benefit from NOM, based on population-based QOL and health utility data. This finding highlights the need for ongoing studies of NOM to detail patient-reported QOL measures that encompass pain, symptoms, body image, and sexual function, data that will ultimately be needed to inform individual treatment decision making about NOM for clinically eligible patients. In the setting of unavoidably increasing limits on health-care resources, the authors’ finding of the incremental cost savings of NOM after cCR also suggests that developing therapeutic strategies to optimize and expand cCR rates could substantially affect not only individual patient outcomes but also public health. There is considerable interest in expanding the pool of eligible patients for organ preservation by increasing the cCR. One strategy that appears to be successful is giving the adjuvant chemotherapy component of treatment before surgery, either before chemoradiation (induction) or after completion of chemoradiation (consolidation). This strategy has become known as total neoadjuvant therapy (TNT). The TIMING trial (NCT00335816) showed that delivering increasing number of cycles (zero, two, four, or six cycles) of consolidative FOLFOX in sequential cohorts of patients with LARC increased the pathologic complete response (pCR) rate to 25%, 30%, and 38%, respectively, compared with 18% for chemoradiation alone, suggesting that giving all of the chemotherapy upfront while increasing the time to surgery increases the pCR (15). A recent meta-analysis of 10 comparative studies demonstrated that TNT increased the likelihood of a pCR by 39% (16). An ongoing, randomized phase II trial of TNT compares sequencing 5-Fluorouracil, Leucovorin, and Oxaliplatin before or after chemoradiation, in which patients with LARC who achieve a cCR are offered NOM (NCT02008656) (17). A similar trial has recently been reported with planned surgery showing a slight increase in pCR with consolidation (18). Efforts also continue in earnest to develop selective radiosensitizers that may improve pCR. NRG-GI002 is an ongoing phase II study evaluating sequential experimental arms integrating radiosensitizers into a TNT platform in patients with high-risk LARC. (NCT02921256). Although TNT strategies have resulted in higher response rates, approximately two-thirds of patients with LARC still require radical surgery (19). As efforts continue, better regimens will likely emerge that will improve complete response rates, which will change the proportion of patients eligible for NOM and ultimately increase the acceptance of the NOM approach. Although the results from Miller et al. will not likely persuade nonbelievers, they do provide an important contribution to our understanding of the advantages of a NOM strategy (4). Although the concept of organ preservation for patients with LARC is appealing, prospective randomized cooperative group studies are needed to confirm the oncologic noninferiority of NOM and the applicability of NOM to routine community oncological practice. In Brazil, Cecconello and colleagues are conducting a randomized phase II trial comparing the 3-year disease-free survival of NOM and radical surgery in LARC patients who achieve a cCR after preoperative chemoradiation (NCT02052921) (20). Although this is an important first step, widespread adoption of NOM will likely be limited and the use of NOM will likely remain controversial until randomized phase III data demonstrate noninferiority and improved patient reported outcomes. The feasibility of randomizing patients to radical surgery vs organ preservation will likely be challenging in the United States because of patient preferences either for or against radical surgery. Nevertheless, outcomes data from prospective randomized trials are critical to provide the knowledge needed to harmonize the insights gained from a cost-effectiveness model of NOM with real-world clinical practice. P. B. Romesser is a consultant for EMD Serono for work on radiation sensitizers. The other authors have no disclosures.
Md. Ashraf Uddin, Andrew Stranieri, Iqbal Gondal, Venki Balasubramanian
Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentralized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, careful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer – Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer – Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR processing layer – Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reliable, secure and private communication. The PA executes a lightweight Blockchain consensus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure patient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the processing and storage of RPM data.
Blockchain technology has received significant attention recently, as it offers a reliable decentralized infrastructure for all kinds of business transactions. Software-producing organizations are increasingly considering blockchain technology for inclusion into their software products. Selecting the best fitting blockchain platform requires the assessment of its functionality, adaptability, and compatibility to the existing software product. Novice software developers and architects are not experts in every domain, so they should either consult external experts or acquire knowledge themselves. The decision-making process gets more complicated as the number of decision-makers, alternatives, and criteria increases. Hence, a decision model is required to externalize and organize knowledge regarding the blockchain platform selection context. Recently, we designed a decision support system to use such decision models to support decision-makers with their technology selection problems in software production. In this article, we introduce a decision model for the blockchain platform selection problem. The decision model has been evaluated through three real-world case studies at three software-producing organizations. The case-study participants asserted that the approach provides significantly more insight into the blockchain platform selection process, provides a richer prioritized option list than if they had done their research independently, and reduces the time and cost of the decision-making process.
In this paper, a blockchain-based data sharing and access control system is proposed, for communication between the Internet of Things (IoT) devices. The proposed system is intended to overcome the issues related to trust and authentication for access control in IoT networks. Moreover, the objectives of the system are to achieve trustfulness, authorization, and authentication for data sharing in IoT networks. Multiple smart contracts such as Access Control Contract (ACC), Register Contract (RC), and Judge Contract (JC) are used to provide efficient access control management. Where ACC manages overall access control of the system, and RC is used to authenticate users in the system, JC implements the behavior judging method for detecting misbehavior of a subject (i.e., user). After the misbehavior detection, a penalty is defined for that subject. Several permission levels are set for IoT devices’ users to share services with others. In the end, performance of the proposed system is analyzed by calculating cost consumption rate of smart contracts and their functions. A comparison is made between existing and proposed systems. Results show that the proposed system is efficient in terms of cost. The overall execution cost of the system is 6,900,000 gas units and the transaction cost is 5,200,000 gas units.
Venkata Marella, Bikesh Raj Upreti, Jani Merikivi, Virpi Kristiina Tuunainen
Abstract Contemporary cryptocurrencies lack legal, monetary, and institutional backing that traditional financial services employ. Instead, cryptocurrencies provide trust through technology. Despite the plethora of research in both trust and cryptocurrencies, the underlying attributes of the technologies that drive trust in cryptocurrencies are not well understood. To uncover these attributes, we analyze the corpus of 1.97 million discussion posts related to Bitcoin, the oldest and most widely used cryptocurrency. Based on earlier research, we identified functionality, reliability, and helpfulness as the focal constructs with which to evaluate users’ trust in technology. In our analysis, we discovered 11 different attributes related to three technology constructs that are significant in creating and maintaining users’ trust in Bitcoin. The findings are discussed in detail in the article.
Over the past decade, the blockchain technology and its Bitcoin cryptocurrency have received considerable attention. Bitcoin has experienced significant price swings in daily and long-term valuations. In this paper, we propose a partial differential equation (PDE) model on the bitcoin transaction network for predicting bitcoin price. Through analysis of bitcoin subgraphs or chainlets, the PDE model captures the influence of transaction patterns on bitcoin price over time and combines the effect of all chainlet clusters. In addition, Google Trends Index is incorporated to the PDE model to reflect the effect of bitcoin market sentiment. The experiment shows that the average accuracy of daily bitcoin price prediction is 0.82 for 362 consecutive days in 2017. The results demonstrate the PDE model is capable of predicting bitcoin price. The paper is the first attempt to apply a PDE model to the bitcoin transaction network for predicting bitcoin price.
Marek Laskowski, Michael Zargham, Hjalmar Turesson, Matt Barlin · 6 authors
We present a methodology for evidence based design of cryptoeconomic systems, and elucidate a real-world example of how this methodology was used in the design of a blockchain network. This work provides a rare insight into the application of Data Science and Stochastic Simulation and Modelling to Token Engineering. We demonstrate how the described process has the ability to uncover previously unexpected system level behaviors. Furthermore, it is observed that the process itself creates opportunities for the discovery of new knowledge and business understanding while developing the system from a high level specification to one precise enough to be executed as a computational model. Discovery of performance issues during design time can spare costly emergency interventions that would be necessary if issues instead became apparent in a production network. For this reason, network designers are increasingly adopting evidence-based design practices, such as the one described herein.
Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.
Amid pressing demands to tackle critical sustainable development goals, governments in developing countries face the additional complex task of embracing new digital technologies such as blockchains. This paper takes a conceptual approach and presents a framework that interlinks development, technology, and governments while highlighting the relevance of state capacity and democratic governance in such dynamics. With this in hand, blockchain technology is revisited from the perspective of governments in the Global South, identifying in the process key traits and presenting a new typology. Research gaps regarding the relationship between this technology and both development and developing country government are also identified. A closer look at some on the ground blockchain implementations yields some early evidence on the advantages and risks involved in the process. The paper closes with a discussion of the results within the proposed framework suggesting additional research themes. It also provides some basic guidance for development practitioners interested in enhancing current programs using blockchains as an enabler.
Over the past decade, the blockchain technology and its Bitcoin cryptocurrency have received considerable attention. Bitcoin has experienced significant price swings in daily and long-term valuations. In this paper, we propose a partial differential equation (PDE) model on the bitcoin transaction network for predicting bitcoin price. Through analysis of bitcoin subgraphs or chainlets, the PDE model captures the influence of transaction patterns on bitcoin price over time and combines the effect of all chainlet clusters. In addition, Google Trends Index is incorporated to the PDE model to reflect the effect of bitcoin market sentiment. The experiment shows that the average accuracy of daily bitcoin price prediction is 0.82 for 362 consecutive days in 2017. The results demonstrate the PDE model is capable of predicting bitcoin price. The paper is the first attempt to apply a PDE model to the bitcoin transaction network for predicting bitcoin price.