【Abstract】Bitcoin prices have fluctuated greatly, and news media have warned investors about a possible price bubble, arguing that the fluctuation arises mainly from people's blind pursuit of short-term trends. Despite these increasing concerns, however, only a few studies have addressed them. This article examines the problem using agent-based modeling. In our model, agents are designed to interact with one another in two ways: Price and social interactions. In their price interactions, agents adopt one of three strategies (fundamentalist, momentum trading, and contrarian trading) in investing at each time and adopt a strategy to maximize their expected benefits. In their social interactions, uninvolved agents become involved at various times based on their network properties (word-of-mouth effect). To examine the distinctive properties of Bitcoin from a comparative perspective, two representative currencies (Euro and Turkish lira) and two financial assets (Nasdaq and Nasdaq leverage index) are used in the agent-based model. The results show that the fraction of fundamentalists and price volatility have mutual Granger causal relationships overall. Also, no significant differences are found in the parameters of social interaction. These results are contrary to commonly held beliefs that Bitcoin prices are merely a result of blind pursuit and herding behavior.
【Abstract】Blockchains are currently gaining attention as a newly emerging technology in both academia and industry, capable of impacting a variety of domains beyond cryptocurrencies. Performance modeling can be used to provide us with a deeper understanding of the behavior and dynamics within blockchain peer-to-peer networks. Blockchain system architects can leverage network models to properly tune their system and to reduce design costs significantly. In this article, we focus on the original and well-established Bitcoin blockchain network. In particular, we propose a random graph model for performance modeling and analysis of the inventory-based protocol for block dissemination. This model addresses the impact of key blockchain parameters on the overall performance of Bitcoin. We derive some explicit and closed-form equations for block propagation delay and traffic overhead in the Bitcoin network. We also adapt our model to study the impact of deploying a relay network and investigate the effect of the relay network size on the network performance and decentralization. We implement our model using the popular network simulator OMNet++. We validate the accuracy of our theoretical model and its implementation with our dataset mined from the Bitcoin network. Our results show the tradeoff between the default number of connections per node, network bandwidth, and block size in order to compute the optimal block propagation delay over the network. Additionally, we found that bigger relay networks can jeopardize the decentralization of the Bitcoin network.
【Abstract】In the period of extreme events, this paper aims to study the extreme risk transmission between Bitcoin and crude oil market by using the extreme Granger causality test to test their causal relationship under extreme and non extreme shocks. First, we can obtain different shocks of Bitcoin and crude oil returns based on empirical quantiles. Second, considering the different role that these shocks played in the causality between Bitcoin and crude oil, we conduct our research by testing the causality among different pairwise shocks. Further, given that these relationships may be changed at different time horizons, we also detect them from a frequency-domain perspective. Hence, we not only find the strong evidence of extreme risk transmission between Bitcoin and crude oil but also investigate the time-varying characteristic of this transmission, which may have a great impact on market participants and scholars related to Bitcoin-oil relations.
【Abstract】Blockchain has been applied in many fields to solve the problems of trust, security, efficiency benefiting from its tamper-proof and traceability of data. However, it is still necessary to consider the technical constraints that limit the large-scale application of blockchain: scalability, security, and decentralization cannot be achieved altogether. Consensus algorithm is the core of blockchain, which determines the performance of blockchain system to a certain extent. The existing reviews or surveys mainly focus on processes of consensus algorithms, but fall short in covering the current trends and scenarios, thereby lacking intrinsic understanding of their design philosophy. In this paper, we propose a multi-dimensional tradeoff model and unearth various indicators of different dimensions to guide the construction of consensus algorithms. To summarize the existing efforts, we compare and analyze various classical consensus algorithms, and focus on the design principles of these algorithms under the multi-dimensional tradeoff model. According to different requirements, each algorithm has different tradeoffs. Furthermore, we provide different solutions for blockchain in different dimensions. Finally, we summarize the development trend of consensus design and the key technology prospects of blockchain. This is, to the best of our knowledge, the first survey that accomplishes such goals.
【Abstract】With the continuous development of blockchain technology, Bitcoin as the first cryptocurrency has drawn massive attention from various sectors. Bitcoin on-chain data storage is over 338GB as of September 1, 2021. According to the exponential growth trend of block data, the size of a Bitcoin full node will exceed 500GB in two years. The huge storage problem makes it difficult for general users to store complete Bitcoin data conveniently, which weakens the decentralization capability of Bitcoin network. In this work, we propose an efficient storage scheme (ESS) based on the distribution characteristics of the unspent transaction outputs in Bitcoin network. ESS sets a UTXO-weight for each block. According to UTXO-weight, it dynamically prunes the blocks which have lower query frequency, improving the scalability of the Bitcoin network. When a new block is generated, ESS enables joining nodes to verify most of the transaction inputs instantly. Only a small amount of transaction outputs of older blocks need to be retrieved from the full node for payment verification. Experimental results demonstrated that ESS can reduce the size of a normal node in current Bitcoin network by about 82.14% at a low communication cost.
【Abstract】Central banks and governments all over the world are increasingly exploring digital versions of fiat money, known as retail Central Bank Digital Currencies (CBDCs). Most initiatives rely on Distributed Ledger Technologies and are presented as alternatives to physical cash. Consequently, anonymity-related regulatory questions have naturally started to arise in terms of Anti-Money Laundering and Counter-Terrorist Financing compliance. Against this backdrop, this paper provides a techno-legal taxonomy of approaches to balance privacy and transparency in CBDCs without thwarting accountability, but it also underlines cross-sectoral impacts. The contribution heeds regulation-by-design as its core methodological foundation, with Privacy-Enhancing Technologies as the relevant use case. Thus, it highlights that not only technology aids legal purposes, but also that some regulatory requirements ought to be designed into technology for one to reach agreed-upon results and/or standards.
【Abstract】Recently, network representation learning has been widely used to mine and analyze network characteristics, and it is also applied to blockchain, but most of the embedding methods in blockchain ignore the heterogeneity of network, so it is difficult to accurately describe the characteristics of the transaction. As smart society evolves, Ethereum makes smart contracts reality, while the mine of transaction characteristics appearing on the Ethereum platform is scarce; thus, there is an urgent need to mine Ethereum from contract and transfer. In this article, we propose a heterogeneous network representation learning method to mine implicit information inside Ethereum transactions. Specifically, we construct an Ethereum transaction network by collecting transaction data from normal and phishing Ethereum accounts. Then, we propose a walk strategy that combines timestamps and transaction amounts to represent the information that occurs at the time of a transaction. To mine the types of nodes and edges, we use a heterogeneous network representation learning method to map the transaction network to a low-dimensional space. Finally, we improve the accuracy of the embedding results in the node classification task, which has important implications for Ethereum mining as well as identity recognition.
【Abstract】This study examines the prediction power of market liquidity (the ease with which asset are traded) and funding liquidity (the ease with which traders can obtain funding) on the price volatilities of Bitcoin. We find that both market and funding liquidity shocks forecast future volatility. More importantly, liquidity shocks have a stronger and persistent effect on the longterm trend component of volatility. Exploiting the predictability of liquidity shocks, we propose a risk-managed strategy to manage extremely high volatility and avoid occasional large crashes in cryptocurrency markets. This novel strategy virtually eliminates crashes and improves the Sharpe ratio substantially against the benchmark buy-and-hold strategy. The outperformance is much stronger during the turbulent periods of cryptocurrencies. Hence, this paper provides important insights into cryptocurrency investment and portfolio management combining traditional assets and cryptocurrencies.
【Abstract】Due to the fast-pacing development of technology in the healthcare domain, many problems arise surrounding the security and privacy preservation of medical data. Secure authentication on the Internet of Medical Things (IoMT) is essential. The lack of security in critical and sensitive information of IoMT may lead to high-risk issues in patient privacy. When new data is transmitted from the sensor node, it cannot be assured as authenticated data. Therefore, a blockchain-based system is needed. Such a system allows healthcare providers to access the health records of patients in a more secured authentication-based approach across various network connections. In this paper, a new secure authentication approach using machine learning is proposed. To identify the dynamic time attack detection and authentication in an IoMT environment, this work implements K-Nearest neighbour (KNN) and machine learning using smart contract (KNN-MLSC). It improves security, reduces latency, and maintains health data privacy for both physicians and patients. The accuracy of KNN-MLSC got 0.96 compared with KNN using a smart contract. Also, the results showed that KNN-MLSC has the minimum computation time.
【Abstract】Bitcoin introduced a cryptocurrency as a form of public ledger consequently that turned into a most popular security technology, Blockchain. Its integrated mining technology lies the key security mechanism. The system allows forming a pool mining group to solve a particular job and share their revenues to their CPU usage while one of them successfully mines a block. To mine a block, a cryptographic puzzle should be solved, which requires significant compute resources that cause huge energy consumption. On the other hand, recent statistics show that low computational energy-restricted Internet of Things (IoT) devices are increasing exponentially. Although it has low energy and limited computation power, it is large in quantity when it is integrated. So we focus on a stochastic geometry theory, which resolves the issue of block mining computation via utilizing multiple mobile IoT devices, given that these IoT devices are Computation Capable Nodes (CCNs). To further normalize this issue, we propose an efficient mathematical solution that uses smart coordination of Virtual Network Functions (VNFs) for IoT devices to enable their CPU usage efficiently. At the same time, the work and credit point distribution policy is smartly handled through virtual pool mining. The proposal renders Network Function Virtualization technology to configure VNF, and Service Function Chain technology is utilized to enable the network flow of such VNFs. New algorithms are presented to solve multiple issues like node discovery, computation offloading, and work credit point distribution. Our goal is to minimize energy consumption within the given time constraint. Implementation results show that although virtual functions for block mining require extensive computations in IoT devices, dividing computation work into small fractions called tasks embedded with VNF, and offloading them to nearby CCNs, tend to minimize the cost and energy consumption of individual shared miners. The overall mining process is proved efficient and faster.
【Keywords】Internet of Things; Task analysis; Virtualization; Blockchains; Peer-to-peer computing; Hardware; Business; Internet of Things; network function virtualization; virtual network function; service function chain; blockchain; bitcoin; pool mining
【Abstract】Today's organ donation and transplantation systems pose different requirements and challenges in terms of registration, donor-recipient matching, organ removal, organ delivery, and transplantation with legal, clinical, ethical, and technical constraints. Therefore, an end-to-end organ donation and transplantation system is required to guarantee a fair and efficient process to enhance patient experience and trust. In this paper, we propose a private Ethereum blockchain-based solution to enable organ donation and transplantation management in a manner that is fully decentralized, secure, traceable, auditable, private, and trustworthy. We develop smart contracts and present six algorithms along with their implementation, testing, and validation details. We evaluate the performance of the proposed solution by performing privacy, security, and confidentiality analyses as well as comparing our solution with the existing solutions. We make the smart contract code publicly available on Github.
【Abstract】A smart Ponzi scheme (SPS) is a financial Ponzi scheme that is implemented and deployed in blockchain through smart contract technology. It is built on treachery and lies, by which, the organizers and speculators jointly deceive innocent investors by fostering a belief in obtaining the expected benefits. The occurrence of SPSs is originated from the vulnerability of the supervision mechanism on the blockchain. Although there are many excellent studies, these contributions overemphasized the methods themselves, did not describe the characteristics of the SPS well, and had certain limitations in practice. We made a thorough study on the characteristics of an SPS and brought out the vital features to identify an SPS for an investor. Based on the analysis of the contributions of predecessors, we propose an approach to test whether a contract is an SPS. This approach could deal with two situations, the contracts to be deployed and the long-run contracts respectively. Of the approach, the priori method can be exploited to distinguish whether the contract to be deployed is an SPS for the runner of a blockchain; the posterior method could protect an investor from being trapped in a fraud. At the same time, the posterior method can also be extended to monitor some contracts dynamically to alert users with the probability to be fallen into SPSs.
【Abstract】The decentralization of power generation driven by the rise in the adoption of distributed energy resources paves the way for a new paradigm in grid operations. P2P energy trading is beneficial to the grid as well as the connected peers. A blockchain-based smart contract is well suited to transparently facilitate trades between energy consumers and producers without the services of intermediaries. In this paper, Ethereum-based smart contracts that facilitate double energy auction and spinning reserve trading are developed with Solidity, compiled, and deployed within the Remix IDE. Willing energy sellers/buyers submit offers/bids to a contract that implements the double auction procedure. In order to fulfil energy supply obligations, sellers are also able to purchase spinning reserves via another smart contract. The smart contracts' effectiveness in performing the auction procedure and making payments is confirmed using an energy/reserve market scenario. The proposed scheme encourages further adoption of distributed energy resources and participation in local P2P energy trading.
【Abstract】With the growing popularity of cryptocurrencies, which are an important part of day-to-day transactions over the Internet, the interest in being part of the so-called cryptomining service has attracted the attention of investors who wish to quickly earn profits by computing powerful transactional records towards the blockchain network. Since most users cannot afford the cost of specialized or standardized hardware for mining purposes, new techniques have been developed to make the latter easier, minimizing the computational cost required. Developers of large cryptocurrency houses have made available executable binaries and mainly browser-side scripts in order to authoritatively tap into users' collective resources and effectively complete the calculation of puzzles to complete a proof of work. However, malicious actors have taken advantage of this capability to insert malicious scripts and illegally mine data without the user's knowledge. This cyber-attack, also known as cryptojacking, is stealthy and difficult to analyze, whereby, solutions based on anti-malware extensions, blocklists, JavaScript disabling, among others, are not sufficient for accurate detection, creating a gap in multi-layer security mechanisms. Although in the state-of-the-art there are alternative solutions, mainly using machine learning techniques, one of the important issues to be solved is still the correct characterization of network and host samples, in the face of the increasing escalation of new tampering or obfuscation techniques. This paper develops a method that performs a fingerprinting technique to detect possible malicious sites, which are then characterized by an autoencoding algorithm that preserves the best information of the infection traces, thus, maximizing the classification power by means of a deep dense neural network.
【Abstract】Blockchain supports free and reliable transactions of the production material supply chain (PMSC). However, few scholars have combined the blockchain with supply chain management. Based on blockchain, this paper explores the collaborative management of material supply chain for production and manufacturing job-shops (PMJs). Specifically, a collaborative management model was constructed, and the execution of the smart contract between PMJ and production material supplier (PMS) was explained. Then, the Stackelberg game between PMJ and PMS in the model was analysed, and the calculation method of the total benefit of PMS and PMJ was derived, under the information sharing mode of the blockchain-based PMSC model. Through trust evaluation, the dishonest companies were identified in the PMSC. To ensure the safe and reliable data sharing between the companies in our model, the probability for the dishonest companies to participate in smart contract was reduced, making it less likely for false shared data to appear in the chain. The effectiveness of the proposed blockchain-based model for the collaborative management of PMSC was proved through simulations.
【Abstract】Since the Ethereum virtual machine is Turing complete, Ethereum can implement various complex logics such as mutual calls and nested calls between functions. Therefore, Ethereum has suffered a lot of attacks since its birth, and there are still many attackers active in Ethereum transactions. To this end, we propose a traceability method on Ethereum, using graph analysis to track attackers. We collected complete user transaction data to construct the graph and analyzed data on several harmful attacks, including reentry attacks, short address attacks, DDoS attacks, and Ponzi contracts. Through graph analysis, we found accounts that are strongly associated with these attacks and are still active. We have done a systematic analysis of these accounts to analyze their threats. Finally, we also analyzed the correlation between the information collected through RPC and these accounts and finally found that some accounts can find their IP addresses.
【摘要】车辆到电网（Vehicle-to-grid，V2G）技术是能源互联网中一项高度新兴的技术，用于合理利用可再生能源而被广泛研究。然而，由于V2G网络的集中化管理和通信的开放性，V2G网络存在单点故障、隐私泄露、分布式能源的不平衡调度等问题。针对上述问题，提出了一个基于联盟区块链的本地化的车辆与车辆之间（Vehicle to Vehicle，V2V）的能源交易系统模型。此外，考虑到电动汽车之间价格和电力需求匹配，提出了一种新的二次双重拍卖机制，以匹配交易车辆对和决定最终交易定价，并使交易双方收益相等。通过安全性分析表明，区块链网络提高了V2V能源交易的安全性。最后，基于数值结果表明，提出的二次双重拍卖机制提高了交易双方收益且收益相等，并与传统拍卖方案相比，提高了拍卖成功率。
