Rolf van Wegberg, J.J. Oerlemans, Oskar van Deventer
Purpose -This paper aims to shed light into money laundering using bitcoin. Digital payment methods are increasingly used by criminals to launder money obtained through cybercrime. As many forms of cybercrime are motivated by profit, a solid cash-out strategy is required to ensure that crime proceeds end up with the criminals themselves without an incriminating money trail. The authors examine how cybercrime proceeds can be laundered using services that are offered on the Dark Web.
A cycle of elliptic curves is a list of elliptic curves over finite fields such that the number of points on one curve is equal to the size of the field of definition of the next, in a cyclic way. We study cycles of elliptic curves in which every curve is pairing-friendly. These have recently found notable applications in pairing-based cryptography, for instance in improving the scalability of distributed ledger technologies. We construct a new cycle of length 4 consisting of MNT curves, and characterize all the possibilities for cycles consisting of MNT curves. We rule out cycles of length 2 for particular choices of small embedding degrees. We show that long cycles cannot be constructed from families of curves with the same complex multiplication discriminant, and that cycles of composite order elliptic curves cannot exist. We show that there are no cycles consisting of curves from only the Freeman or Barreto--Naehrig families.
The study aims to determine the opinions of school principals on decentralization in education. Phenomenological research design was used in the study. The purposive sampling methods of convenience and criterion samplings were used together. The study group was composed of six volunteer principals. The data were collected through individual face-to-face interviews using a semi-structured form. Descriptive analysis and inductive content analysis were used. In conclusion, from a holistic perspective, most of the participants found the concept of decentralization to be close to full autonomy which is usually perceived as dangerous in terms of the unitary state structure. Therefore, they have more centralized attitudes towards educational processes other than financing and infrastructure support regarding decentralization in education. This is indeed an indication that concerns regarding decentralization in education are high. The participants think that decentralization will not harm our national identity and the national education structure is beneficial.
Alessandro Chiesa, Michael A. Forbes, Tom Gur, Nicholas Spooner
Zero knowledge plays a central role in cryptography and complexity. The seminal work of Ben-Or et al. (STOC 1988) shows that zero knowledge can be achieved unconditionally for any language in NEXP , as long as one is willing to make a suitable physical assumption : if the provers are spatially isolated, then they can be assumed to be playing independent strategies. Quantum mechanics, however, tells us that this assumption is unrealistic, because spatially-isolated provers could share a quantum entangled state and realize a non-local correlated strategy. The MIP * model captures this setting. In this work, we study the following question: Does spatial isolation still suffice to unconditionally achieve zero knowledge even in the presence of quantum entanglement? We answer this question in the affirmative: we prove that every language in NEXP has a 2-prover zero knowledge interactive proof that is sound against entangled provers; that is, NEXP ⊆ ZK-MIP * . Our proof consists of constructing a zero knowledge interactive probabilistically checkable proof with a strong algebraic structure, and then lifting it to the MIP * model. This lifting relies on a new framework that builds on recent advances in low-degree testing against entangled strategies, and clearly separates classical and quantum tools. Our main technical contribution is the development of new algebraic techniques for obtaining unconditional zero knowledge; this includes a zero knowledge variant of the celebrated sumcheck protocol, a key building block in many probabilistic proof systems. A core component of our sumcheck protocol is a new algebraic commitment scheme, whose analysis relies on algebraic complexity theory.
Online portals include an increasing amount of user feedback in form of ratings and reviews. Recent research highlighted the importance of this feedback and confirmed that positive feedback improves product sales figures and thus its success. However, online portals' operators act as central authorities throughout the overall review process. In the worst case, operators can exclude users from submitting reviews, modify existing reviews, and introduce fake reviews by fictional consumers. This paper presents ReviewChain, a decentralized review approach. Our approach avoids central authorities by using blockchain technologies, decentralized apps and storage. Thereby, we enable users to submit and retrieve untampered reviews. We highlight the implementation challenges encountered when realizing our approach on the public Ethereum blockchain. For each implementation challange, we discuss possible design alternatives and their trade-offs regarding costs, security, and trustworthiness. Finally, we analyze which design decision should be chosen to support specific trade-offs and present resulting combinations of decentralized blockchain technologies, also with conventional centralized technologies.
Initial Coin Offerings (ICO) are public offers of new cryptocurrencies in exchange of existing ones, aimed to finance projects in the blockchain development arena. In the last 8 months of 2017, the total amount gathered by ICOs exceeded 4 billion US$, and overcame the venture capital funnelled toward high tech initiatives in the same period. A high percentage of ICOS is managed through Smart Contracts running on Ethereum blockchain, and in particular to ERC-20 Token Standard Contract. In this work we examine 1388 ICOs, published on December 31, 2017 on icobench.com Web site, gathering information relevant to the assessment of their quality and software development management, including data on their development teams. We also study, at the same date, the financial data of 450 ICO tokens available on coinmarketcap.com Web site, among which 355 tokens are managed on Ethereum blochain. We define success criteria for the ICOs, based on the funds actually gathered, and on the behavior of the price of the related tokens, finding the factors that most likely influence the ICO success likeliness.
Initial Coin Offerings (ICO) are public offers of new cryptocurrencies in\nexchange of existing ones, aimed to finance projects in the blockchain\ndevelopment arena. In the last 8 months of 2017, the total amount gathered by\nICOs exceeded 4 billion US$, and overcame the venture capital funnelled toward\nhigh tech initiatives in the same period. A high percentage of ICOS is managed\nthrough Smart Contracts running on Ethereum blockchain, and in particular to\nERC-20 Token Standard Contract. In this work we examine 1388 ICOs, published on\nDecember 31, 2017 on icobench.com Web site, gathering information relevant to\nthe assessment of their quality and software development management, including\ndata on their development teams. We also study, at the same date, the financial\ndata of 450 ICO tokens available on coinmarketcap.com Web site, among which 355\ntokens are managed on Ethereum blochain. We define success criteria for the\nICOs, based on the funds actually gathered, and on the behavior of the price of\nthe related tokens, finding the factors that most likely influence the ICO\nsuccess likeliness.\n
After comparing and contrasting with computer codes running in a central server, this paper notes that smart contracts are not in the legal sense and considers their implications for contract management and dispute prevention. It alerts that the features of are prone to generate disputes which often involve novel legal issues. The paper concludes with a brief comment on the potential use of in dispute resolution.
The cryptocurrency Bitcoin has been prominently featured in the news recently. Its ascension in value has been nothing short of extraordinary. This article briefly explains what Bitcoin is and how it works. The more challenging question is what Bitcoin—this cryptographic breakthrough—really is: currency, like the U.S. dollar, an asset, more like gold, or something else? Further, can this astonishing run-up in value continue or will Bitcoin be added to the long list of so-called "asset bubbles" that eventually burst, causing pain for those that own them?
We design and implement the first private and anonymous decentralized crowdsourcing system ZebraLancer, and overcome two fundamental challenges of decentralizing crowdsourcing, i.e., data leakage and identity breach. First, our outsource-then-prove methodology resolves the tension between the blockchain transparency and the data confidentiality to guarantee the basic utilities/fairness requirements of data crowdsourcing, thus ensuring: (i) a requester will not pay more than what data deserve, according to a policy announced when her task is published via the blockchain; (ii) each worker indeed gets a payment based on the policy, if he submits data to the blockchain; (iii) the above properties are realized not only without a central arbiter, but also without leaking the data to the open blockchain. Second, the transparency of blockchain allows one to infer private information about workers and requesters through their participation history. Simply enabling anonymity is seemingly attempting but will allow malicious workers to submit multiple times to reap rewards. ZebraLancer also overcomes this problem by allowing anonymous requests/submissions without sacrificing accountability. The idea behind is a subtle linkability: if a worker submits twice to a task, anyone can link the submissions, or else he stays anonymous and unlinkable across tasks. To realize this delicate linkability, we put forward a novel cryptographic concept, i.e., the common-prefix-linkable anonymous authentication. We remark the new anonymous authentication scheme might be of independent interest. Finally, we implement our protocol for a common image annotation task and deploy it in a test net of Ethereum. The experiment results show the applicability of our protocol atop the existing real-world blockchain.
By thinking loudly about putting the regulation of cryptocurrencies on the agenda of the G20, governments seem to have managed to keep the Bitcoin bubble from inflating into a systemic risk, so far. In a tongue-in-cheek sense, this behavior of supervisory and regulatory authorities can be described as the distributed ledger technology of financial supervision. It is distributed because it does not have a clear center. The G20 seems to be the common reference point for many actors, but it does not speak itself. It is like a shared code.
Blockchains have recently generated explosive interest from both academia and industry, with many proposed applications. But descriptions of many these proposals are more visionary projections than realizable proposals, and even basic definitions are often missing. We define "blockchain" and "blockchain network", and then discuss two very different, well known classes of blockchain networks: cryptocurrencies and Git repositories. We identify common primitive elements of both and use them to construct a framework for explicitly articulating what characterizes blockchain networks. The framework consists of a set of questions that every blockchain initiative should address at the very outset. It is intended to help one decide whether or not blockchain is an appropriate approach to a particular application, and if it is, to assist in its initial design stage.
Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives.
With the development of marine observation technology and network technology, the volume of marine data growing rapidly. This brings new challenges for data storage and transmission. How to protect data security of marine big data has become an urgent problem. The traditional information security methods' characteristic is centralization. These technologies cannot provide whole process protection, e.g., data storage, data management and application of data. The blockchain technology is a novel technology, which can keep the data security and reliability by using decentralized methodology. It has aroused wide interest in the financial field. In this paper, we describe the concept, characteristics and key technologies of blockchain technology and introduce it into the field of marine data security.
Although the problems identified in the statement have been known for several decades, previous expressions of concern and calls for action have not fostered broad improvements in practice.2 A P value of 0.05 carries a 5% risk of a false positive result (i.e. there is no true difference between treatments). If a trial is meant to provide proof of a genuine treatment difference beyond reasonable doubt, a much smaller P value – say p < 0. 001 – is required.5 We disagree ….that our statement… is erroneous. According to the null hypothesis, P < 0.05 will occur 5% of the time.6 No editorial corrigendum has appeared. A P-value is the area under the curve of a probability distribution defined by a mathematical model. The model, usually presented graphically, describes the expected distribution of a sample statistic around a central measure, the parameter or theoretical ‘true’ value, for example the population mean, μ. Under the central limit theorem, this would be the standard normal distribution of sample means generated by repeat sampling of a population variable of interest. The mean of the sample means would equal the ‘true’ population mean, μ. In medicine, it is rare for us ever to know the true value of the variable of interest. However, we can usefully assign a value in the special case of a difference statistic, for example the difference in mean outcome variables in a placebo-controlled drug trial. In this case, the sampling distribution would represent that of the difference statistic. In this case, if the value we assign μ is zero then the mathematical model becomes the null hypothesis used in NHST. By way of contrast, non-inferiority drug trials require a non-zero value to be assigned. The cumulative AUC of the sampling distribution of a continuous variable is represented by a mathematical function called the cumulative density function. In medical science, most study variables are continuous or, if categorical, are transformed using the logit model. As the P-value is a mathematical integral, that is the cumulative AUC, it cannot take on a precise value as there is no AUC defined by a single point on the curve, for example the P-value ≤ 0.05, but not P = 0.05. While this may seem pedantic, the semantics of statistical inference are influential in thinking and decision-making yet misinterpretation and misuse of terminology are commonplace. Under the null hypothesis, one sample mean that happens to fall within an extreme region of the standard normal distribution may be expected to occur with a low frequency, say P ≤ 0.05 meaning such a sample mean or one more extreme would be expected to occur with a frequency of 5% or less. To be valid, the assumptions of independence and random selection of each sample mean selected from the normal distribution of sample means must be assumed. Another way of stating this is as a conditional probability: . Note: | means ‘given’. It is important to understand that the P-value is a measure conditional on the assumption that the mathematical model describes the distribution of sample means and is not a measure of the probability of the ‘truth’ of the mathematical model. To make this claim would invert the conditional probability statement and commit an error of reasoning called transposing the conditional7 aka the prosecutor's fallacy: . In reasoning from NHST, the commonly used definition of the P-value as ‘a measure of evidence against the null hypothesis’ is potentially misleading in that it seems to legitimise transposing the conditional as if it were a mathematically valid function rather than a matter of intuition. It was the intuitive interpretation that Fisher used in his a posteriori model of NHST.8, 9 His aim was to use the P-value as an aid in deciding which experiments to repeat. If on several repetitions, a consistent extreme P-value for the sample statistic was obtained then that would accumulate evidence for a true experimental effect. If no such effect was present, regression to the mean parameter (μ) would be expected (P ≥ 0.05). In real-life scenarios, many factors inhibit repetition and replication of experiments; however, modelling can give us insight into the precision and reproducibility of extreme P-values10, 11 and hence the intuitive weight we place on the P-value ‘as a measure of evidence against the null hypothesis’. Table 2 is a reproduction.10 It describes the results of simulating repeat experimentation and the probability of producing a P-value ≤ 0.05 under the prescribed conditions of the simulated experiment. It may be surprising to many how poorly reproducible the P-value is as a bright line test (a bright line test is a clearly defined rule or standard, the purpose of which is to produce consistent and predictable results). For example, if in the first experiment P ≤ 0.05 was produced there would be a 50% probability of reproducing P ≤ 0.05 in a repeat experiment; if P ≤ 0.01was produced in the first experiment the probability of producing P ≤ 0.05 in a repeat experiment, would be 73%; and if P ≤ 0.001 was produced in the first experiment the probability of P ≤ 0.05 in a repeat experiment would be 91%. The magnitudes of a number of these first experiment P-values are those commonly used in pharmaceutical trials and other medical analyses. The P-value is also sensitive to sample size. Irrespective of the effect size, with increasing sample size (n) the P-value can be made as small as you wish12 because the standard error is proportional to the inverse of n. If statistical significance is substituted for ‘clinical significance’ even small irrelevant differences may be regarded as worthy of investment. Large sample sizes are often a feature of pharmaceutical trials of secondary and primary prevention interventions such as preventive therapies in atherosclerotic diseases and osteoporosis. The quoted extract from the article on clinical trials mistakenly promotes the P-value as a measure of error and further states that the error rate can legitimately be adjusted depending on the magnitude of the P-value thus providing ‘proof of a genuine treatment difference beyond reasonable doubt’. This erroneous interpretation has arisen from the illusion of coherence resulting from the conflation of the dominant models of hypothesis testing.8, 9 The setting of theoretical type 1 (α) and type 2 (β) error rates in the Neyman and Pearson model envisions the frequency of error ‘in the long run of experience’ (experimental repetition) given randomness and independence of sample means from two juxtaposed probability distributions. A priori two identical populations are imagined except that they differ in mean parameters, null μ0 and alternative μA. This model is valuable in providing a rationality to sample size selection. However, the conflation has resulted in confusion between Fisher's P-value and Neyman's α giving the P-value an apparent legitimacy as an a posteriori ‘sliding’ type 1 error rate. Even if this were logical, decreasing α would increase β, resulting in a decrease in power (1-β). Also the dichotomous approach of pitting null hypothesis against alternative hypothesis carries the risk of blinding the researcher or the consumer to other explanatory hypotheses. For those who think the use of confidence intervals (CI) overcomes the problems described, think again. Although it has greater intuitive value especially with respect to estimating effect size, the CI relies on the same premises as the P-value. For example the CI of juxtaposed probability distributions can be made as large or as small as can be paid for by increasing the sample size such that for any small difference the CI can be made not to overlap. Statistical analyses are very valuable tools for extracting information from data. However, the reliability of the knowledge generated is dependent on many more important factors inter alia, evidential justification of the experimental hypothesis, study design, study conduct and data collection and cleansing, competence in choice of statistical model, valid reasoning, reviewer bias, publication bias and replication. Much of the criticism of medical science centres on its overemphasis on the importance of the P-value, NHST and statistically defined effect sizes. A better understanding of how sound statistical inferences are made and how they influence decision making will be key elements to improving all aspects of healthcare. This is critically important in acknowledgement of individuals as complex adaptive systems with characteristics of emergence, adaptability, non-linearity and unpredictability13 rather than as static population averages. Surveys suggest statistical literacy amongst doctors is low.14, 15 Teaching and assessing knowledge and application of statistical inference, critical appraisal and decision-making skills should be a primary focus of medical schools and specialist colleges. Difficult concepts underpinning statistical inference may be more effectively and efficiently taught using computer simulation whereby the learner can manipulate effect sizes, sample sizes and other statistics in order to see how parameter estimates, P-values and CI change with reproduction and replication.16 This will foster a more in-depth understanding of the limits of statistical inference, making clinicians better able to choose wisely amongst the myriad of investigations and treatment options on offer. Subsequent to article submission and review the author attended the referenced ASA conference.2 A special issue of the ASA journal reporting the conference proceedings is planned for 2018. In the opening addresses, the 400 participants were encouraged to devote their energies to developing proposals and goals to address the long standing yet stubbornly persistent errors in statistical inference described in this article. While concrete proposals are yet to be endorsed by the ASA, many speakers emphasised the need to place greater emphasis on teaching the conceptual framework of the different philosophical approaches to science (mastering the concepts as a priority rather than the mechanics of statistical inference). The need for better understanding of statistical semantics on the part of non-statistician scientists was also highlighted. Further that the best way to achieve understanding would be to develop context-specific learning modules. An aspect of the conference that resonated with the author with respect to prediction in medical science was the idea that science defines degrees of uncertainty (not certainty) apropos caution must be applied to the use of prediction models in medical practice lest they be over-extended.
Urgency of the research.The competitive position of the national economy depends on the power of human capital, the foundation of which is based on the system of secondary education. The reform of the decentralization of budgetary relations allows the local authorities to influence the financial provision of the Concept of the "New Ukrainian School", based on the needs and interests of each region. Target setting. The concept of the "New Ukrainian School" implies that the distribution of financial resources is based on the principle of "money goes after the child." In September 2018 the elementary school moves to a new content of education and financing. Budget decentralization is a powerful tool for creating a new educational environment. Actual scientific researches and issues analysis. Topics of reforming education and the specifics of its financing were investigated by I. Kohut, O. Kuklin, E. Stadnyi, A. Seitosmanov, L. Tsymbal, O. Fasolya, P. Hobzsey, N. Kholyavko and other scholars. Uninvestigated parts of general matters defining. There is an urgent need to research the regional aspects of financing secondary education in the context of budget decentralization. The research objective. To substantiate the conceptual approaches to financing decentralization of secondary education taking into account regional specificity. The statement of basic materials. Modern theoretical and methodological approaches and analytical materials concerning the reform of secondary education are analyzed. The economic and political preconditions of providing educational reform in conditions of decentralization are showed. Conclusions. The constructive implementation of the decentralization reform of the financing of the secondary education system and the implementation of the concept of the "New Ukrainian School", the transfer of significant powers and budgets from state authorities to local has been proved. The tendency to increase financing of education is revealed and specified directions for improving the provision of educational services.
This article studies the emergence of Share&Charge, a German platform that organizes the sharing of charging stations for electric vehicles (EVs) and the billing for the energy transactions. Share&Charge follows a peer-to-peer fashion, enabling direct transactions between charging station owners and EV drivers. On the demand side, the platform, with its interactive map, makes it possible for EV owners to find a charging station in the most suitable location, for instance, at their place of work or where they live. On the offer side, Share&Charge enables station operators (private individuals or companies) to rent their charging stations and eventually to sell the electricity they produce. Charging tariffs within the charging station network are determined by the charging station operators themselves, but the platform provides indicative tariffs. Launched in September 2017, Share&Charge follows other initiatives, such as the French platforms Wattpop and ChargeMap, and the Swedish Elbnb. Share&Charge’s network is already proven to be successful with German citizens. Share&Charge adds certain elements of value at different stages of EV utilization. First, this model allows for a co-financing of charging infrastructures by individuals and businesses in the private sector by sharing the infrastructure costs among EV drivers. Besides the purchase price of EVs, the implementation of charging infrastructures and their financing represent a significant barrier to the rise of e-mobility. Share&Charge helps remove this obstacle without adding a further burden on the governmental budget. In addition, this approach follows the “user pays principle,” which engages in fair and effective financing. Second, the platform increases decentralized production value and facilitates its expansion. It also helps in avoiding grid congestion and energy loss, as well as increasing flexibility within the electricity market. Third, data use enables the optimization of energy demand and supply, and the optimal determination of tariffs, although these remain facultative. Models like Share&Charge could thus positively impact energy policy by tackling several upcoming obstacles associated with the development of EVs and decentralized energy production capacities. However, new forms of network structures (decentralized networks, sharing economy) and new actors (prosumers, platforms, etc.) also raise regulatory challenges. This article presents some of the legal issues associated with the development of models like Share&Charge. In particular, we study the tax framework applicable to this model, assuming that as such, it would be introduced into the Belgian market.
In traditional Chinese medicine, the growth situation of the surface of nails reflects the physiological condition of the human body. Diagnosis by nail can effectively predict and prevent disease. Human nails have a high degree of uniqueness, and it can be used for biometric recognition. In this work, microscope sensor was used to capture the clear image and segment the lunula and nail plate effectively through image preprocessing. Fingernails’ image is managed as the identity authentication. Histogram of oriented gradients and local binary patterns are used to capture the characteristic value. It uses support vector machine and random forest tree for classification. The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. Furthermore, the security and privacy of the Internet of Things is still a challenge. This work uses the highly anonymous blockchain technology to effectively protect data privacy and manage each user’s data through the blockchain, in which any change or manipulation can be recorded and tracked, and the data security is improved. Therefore, this article presents a nail analysis management system with the use of microscopy sensor and blockchain.
Several years after the inception of the most dominant cryptocurrency, bitcoin, the European Central Bank in 2015 indicated the need for establishing legal clarity by relevant authorities through explaining how the current legal framework applies to cryptocurrencies. Three years later, no meaningful step has been taken by any of the European Union (EU) institutions including the parliament. By examining the EU’s legal framework governing payments services, including the Single Euro Payment Area (SEPA) Regulation, the Electronic Money Directive, the Payment Services Directive and the proposed AML/CTF Directive, this article concludes that (a) because the existing payment services laws apply to payments effected in currencies (legal tenders) and cryptocurrencies are not defined as currencies under the EU law or the laws of member states, they do not cover cryptocurrencies. It also argues that it is impossible to design sui generis payments services law for cryptocurrencies without curbing their essential features, especially decentralization. Lastly, the article proposes centralization and the creation of state cryptocurrency as possible solutions moving forward and examines their strengths and challenges.
Since its independence the Republic of Croatia has commenced a thorough reconstruction of its taxation system according to the market economy taxation policy. Essential taxation reforms have brought the system closer to EU systems i.e. it has been being harmonized with taxation systems of developed European countries. The Republic of Croatia has adopted solutions that are used by the majority of European countries. Current tax system of the Republic of Croatia can be viewed through three fiscal levels, but this paper deals with decentralization and revenue, especially tax revenue of local and regional self-government units. The paper will present importance and a way of collecting revenue, especially tax revenue and satisfying public needs in terms of counties, cities and municipalities. The local and central characteristics of the certain types of taxes and the specialities thereof, as well as the applied functional differences are also scrutinized, and a widely accepted opinion of the taxpayers is explained. Taking these into account, the scientific contribution of this paper is that it provides a basis for further research on tax system development.
In this article, the author tracks developments in bitcoin trading and considers regulatory responses. 2017 has witnessed a so-called bitcoin bubble, as entrepreneurs and professional investors rushed into the market to take a bet on the upcoming cryptocurrency age. The price of a bitcoin exceeded $19,300 in December 2017, worth only $0.06 in July 2010. The popularity of bitcoin mining and trading activities has raised legal and regulatory concerns pertaining to anti-money laundering, evasion of forex regulations, the illegal fundraising of start-ups by Initial Coin Offerings (ICOs), as well as a potential financial crisis. Global financial regulators have acted proactively to regulate bitcoin. Most recently, China, once accounting for 90% of bitcoin trading volume, issued an immediate ban of ICOs and ordered the reorganisation of three major bitcoin exchanges: OKCoin, Huobi and BTCC. Over-The-Counter (OTC) transactions have not been affected. Financial authorities in certain countries have been testing state-backed cryptocurrencies.