面向比特币的区块链扩容:关键技术, 制约因素与衍生问题

比特币是一种利用区块链技术的点对点记账系统.随着比特币的发展,现有的比特币系统架构已经不能满足日益增长的交易需求,亟需扩容以寻求长期发展.比特币是以人为核心的复杂社会经济系统,比特币扩容是涉及多方利益的复杂问题,引起了业界与学术界的广泛关注.本文提出了一个比特币系统扩容问题的研究框架,包括关键技术,制约因素与衍生问题三部分,以深入探讨和研究比特币扩容问题.在该研究框架下,首先介绍链上和链下两类扩容关键技术及发展现状;其次从网络负载和节点瓶颈两方面,总结制约比特币扩容方案的宏观与微观因素;最后,探讨两类衍生问题:从系统安全性的角度,探讨比特币扩容可能引发的安全问题及解决策略;从币值、交易费与矿工收益等方面,阐述比特币扩容涉及的经济问题.     

基于交易网络的公有链用户识别方法

分析与研究公有链交易数据及系统用户行为对于保证公有链应用安全至关重要。比特币作为公有链的代表性应用,是一种基于P2P网络的电子现金系统。比特币交易地址具有匿名特征,无法关联到用户真实信息,这使得比特币溯源非常困难。为识别比特币中交易地址间的关联关系,推断出用户真实信息,提出一种基于交易网络的用户识别方法。对比特币区块数据进行预处理,通过解析比特币区块数据中的脚本信息,将比特币原始交易数据处理为更加直观的数据格式。衡量交易输入与输出地址间的相似程度,根据交易地址关联信息识别出比特币匿名地址对应的所有用户。在实验中应用真实的比特币区块数据,利用可视化方式对用户识别结果进行分析,结果表明该方法不受交易规则的限制,能对比特币匿名地址进行有效识别,且随着比特币区块数量的增加,识别准确率基本稳定于80%。     

可监管的比特币隐私保护混淆服务

随着比特币隐私保护研究的深入,比特币作为一种新型“数字货币”变得更加难以监管。针对该问题,提出了一种可监管的比特币隐私保护混淆方案RBmix。RBmix模型使用公平盲签名算法,并引入可信第三方,具有可监管性、匿名性、可扩展性、比特币兼容性以及抗DoS攻击性。实验结果表明RBmix协议具有良好的扩展性和执行效率。     

基于人工免疫的比特币快捷交易异常检测模型

电子货币交易最重要的问题是双重花费（双花攻击）,比特币预防双花攻击的策略是等待六个确认块（约1 h）,难以适用于快捷支付领域,默认替代策略是等待交易信息传播到卖主的钱包,这无法有效地预防双花攻击。针对比特币快捷交易中双花攻击的检测问题,提出了一种基于人工免疫的比特币快捷交易异常检测模型。在每个传统比特币节点中加入免疫检测模块进行抗原提取,并利用检测器进行异常检测,在威胁控制中心动态演化检测器并分发免疫疫苗以便有效地进行防御。实验结果证明,此检测模型能够有效地检测并预防比特币快捷支付中的双花攻击。     

面向比特币交易网络的拓扑结构可视探索方法

分析比特币交易网络有助于人们理解交易者在比特币交易中的交易模式.比特币交易网络的匿名性和其巨大的规模使得用户很难在分析前对整个交易网络产生大致的认知.提出了一种基于拓扑结构推荐的比特币交易网络可视分析方法.核心思想是为每个节点生成一个向量化表达,在用户交互的基础上,所提算法即可检测一系列相似的结构.案例分析证明了系统能够支持用户对比特币交易中的交易模式进行探索和分析.     

Bitcoin as an alternative investment vehicle

This paper documents time series momentum in Bitcoin returns. The paper finds persistence in returns for one to 8 weeks that partially reverses over longer horizons, consistent with sentiment theories of initial under-reaction and delayed over-reaction. The time series momentum in Bitcoin returns is similar to that of the other asset returns while the time span is much shorter. This may be due to much quicker nature and shorter term memory of Bitcoin investors. A combined portfolio of S&P500 and Bitcoin momentum strategy shows enhanced expected return, skewness, kurtosis and Value at Risk for given levels of portfolio return volatility.     

Incentive Mechanism for Rational Miners in Bitcoin Mining Pool

Information Systems Frontiers - Bitcoin is one of the most popular cryptocurrency in the world. Miners in the Bitcoin network reduce their risks through participating in mining pool. Existing...     

Correlated at the Tail: Implications of Asymmetric Tail-Dependence Across Bitcoin Markets

Computational Economics - This paper is the first to fully characterize the relationship among cross-market Bitcoin prices to provide a complete picture of directional predictability of Bitcoin...     

区块链技术与应用前瞻综述

区块链技术是一种去中心化、去信任化的分布式数据库技术方案。该数据库由参与系统的所有节点集体维护,具有去中心化、不可篡改、透明、安全等特性。区块链技术归功于比特币应用,它作为比特币的底层技术支持,是比特币系统的核心支撑。区块链技术 具有广阔的 发展前景,从关键技术、内容、原理、瓶颈、应用和前景几个方面进行介绍,对相关研究问题进行探讨。     

基于动机分析的区块链数字货币异常交易行为识别方法

当前区块链数字货币被众多恶意交易者利用,导致了"粉尘"注入、"空投"操作、勒索、骗局等一系列异常交易行为.因此,研究区块链数字货币异常交易行为的识别方法对于规范交易行为、保障网络空间安全具有重要意义.在众多区块链数字货币中,比特币市值超过所有区块链数字货币市值和的一半,具有高代表性.比特币系统的用户数量多、交易规模大、...     

Predicting the direction,maximum, minimum and closing prices of daily Bitcoin exchange rate using machine learning techniques

Bitcoin is the most accepted cryptocurrency in the world, which makes it attractive for investors and traders. However, the challenge in predicting the Bitcoin exchange rate is its high volatility. Therefore, the prediction of its behavior is of great importance for financial markets. In this way, recent studies have been carried out on what internal and/or external Bitcoin information is relevant to its prediction. The increased use of machine learning techniques to predict time series and the acceptance of cryptocurrencies as financial instruments motivated the present study to seek more accurate predictions for the Bitcoin exchange rate. In this way, in a first stage of the proposed methodology, different feature selection techniques were evaluated in order to obtain the most relevant attributes for the predictions. In the sequence, it was analyzed the behavior of Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Ensemble algorithms (based on Recurrent Neural Networks and the k-Means clustering method) for price direction predictions. Likewise, the ANN and SVM were employed for regression of the maximum, minimum and closing prices of the Bitcoin. Moreover, the regression results were also used as inputs to try to improve the price direction predictions. The results showed that the selected attributes and the best machine learning model achieved an improvement of more than 10%, in accuracy, for the price direction predictions, with respect to the state-of-the-art papers, using the same period of information. In relation to the maximum, minimum and closing Bitcoin prices regressions, it was possible to obtain Mean Absolute Percentage Errors between 1% and 2%. Based on these results, it was possible to demonstrate the efficacy of the proposed methodology when compared to other studies.     

MicroBTC: Efficient,Flexible and Fair Micropayment for Bitcoin Using Hash Chains

While Bitcoin gains increasing popularity in different payment scenarios, the transaction fees make it difficult to be applied to micropayment. Given the wide applicability of micropayment, it is crucial for all cryptocurrencies including Bitcoin to provide effective support therein. In light of this, a number of low-cost micropayment schemes for Bitcoin have been proposed recently to reduce micropayment costs. Existing schemes, however, suffer from drawbacks such as high computation cost, inflexible payment value, and possibly unfair exchanges. The paper proposes two new micropayment schemes, namely the basic MicroBTC and the advanced MicroBTC, for Bitcoin by integrating the hash chain technique into cryptocurrency transactions. The basic MicroBTC realizes micropayment by exposing hash pre-images on the hash chain one by one, and it can also make arbitrary micropayments by exposing multiple hash pre-images. We further design the advanced MicroBTC to achieve non-interactive refund and efficient hash chain verification. We analyze the complexity and security of the both MicroBTC schemes and implement them using the Bitcoin source code. Extensive experiments were conducted to validate their performance, and the result showed that a micropayment session can be processed within about 18ms for the basic MicroBTC and 9ms for the advanced MicroBTC on a laptop. Both schemes enjoy great efficiency in computation and flexibility in micropayments, and they also achieve fairness for both the payer and the payee.

     

基于机器学习的比特币去匿名化方法研究

比特币是一种去中心化的匿名加密货币,是目前使用最广泛的数字资产之一,具有匿名性、无主权、无地域限制的特点,匿名性的特性也使得比特币被广泛应用于各种犯罪活动。为实现比特币的去匿名化,提出一种联合特征构造方法并构建随机森林与Softmax相结合的分类模型。为更好地区分不同类型比特币的交易行为,引用交易实体的概念,按照联合特征构造方法分别从地址、实体与交易网络结构3个方面在海量的交易数据中构造特征,并将其整合成联合特征向量。实验结果表明,该实体分类模型的类别识别精确率超过0.92,其能够有效提升执法机构对虚拟货币犯罪行为的调查取证能力。     

Difficulty control for blockchain-based consensus systems

Crypto-currencies like Bitcoin have recently attracted a lot of interest. A crucial ingredient into such systems is the “mining” of a Nakamoto blockchain. We model mining as a Poisson process with time-dependent intensity and use this model to derive predictions about block times for various hash-rate scenarios (exponentially rising hash rate being the most important). We also analyse Bitcoin’s method to update the “network difficulty” as a mechanism to keep block times stable. Since it yields systematically too fast blocks for exponential hash-rate growth, we propose a new method to update difficulty. Our proposed method performs much better at ensuring stable average block times over longer periods of time, which we verify both in simulations of artificial growth scenarios and with real-world data. Besides Bitcoin itself, this has practical benefits particularly for systems like Namecoin. It can be used to make name expiration times more predictable, preventing accidental loss of names.     

关于比特币中BWH攻击的一个注记

比特币是当前信息安全应用研究领域的热点问题之一.在比特币所采用的PoW共识协议中,挖矿具有重要作用.在现实生活中,矿工为获得更多的奖励,往往聚集成矿池,以达到在挖矿中获取更高算力进而获取更多区块奖励的目的.针对比特币矿池,Meni Rosenfeld首次提出了一种称为BWH攻击的攻击方式,Loi Luu等人进一步从理论上证明了相对于诚实挖矿,攻击者通过实施BWH攻击可以获得更高的收益.在本文中,我们分析了BWH攻击的理论基础,发现Loi Luu等人关于BWH攻击的理论分析中存在的一个错误,即Loi Luu等人忽略了整体算力改变对系统产生区块所需时间的影响,从而导致其所对比的关于攻击者实施BWH攻击所获得的收益与不实施攻击所获得的收益,实际上是在不同时间长度下的收益对比.显然这种对比缺乏合理性.在相同时间长度下,我们进一步讨论了攻击者实施BWH攻击与不实施攻击所获得的收益对比,得到了与Loi Luu等人完全相反的结论,即相对诚实挖矿来说,攻击者实施BWH攻击反而获得了相对较少的收益.因此攻击者缺乏实施BWH攻击的动机,除非其纯粹出于破坏矿池的目的而采用BWH攻击.     

基于比特币的私有信息检索支付协议

私有信息检索（PIR）是一种密码学工具,使用户能够从远程数据库服务器中获取信息,而不会让服务器知道用户获取了什么信息。PIR方案基本上由两种类型组成,即信息论私有信息检索（Information Theoretic PIR,IT-PIR）和计算性私有信息检索（Computational PIR,C-PIR）。IT-PIR方案要求服务器之间不共谋。一旦服务器共谋,就无法保证用户的隐私。共谋问题一直以来都没有一个比较好的解决办法。比特币和区块链的出现为解决公平和信任的问题提供了一种新方法。在本文中,我们创新地使用区块链来处理IT-PIR中的共谋问题,提出了一种基于比特币的PIR支付协议。在此支付协议中,客户通过比特币交易支付服务费。我们通过比特币脚本控制交易兑现的条件,使得如果服务方相互串通,则使服务方受到利益损失。通过这种方式,该支付协议可以在一定程度上降低共谋的可能性。     

The Effect of Similarity and Dissimilarity on Information Network Formation and Their Implications in Accurate Information Identification

In the context of the Bitcoin market and its virtual investment communities, this paper demonstrates that both similarity and dissimilarity in social media messages’ contents can be associated with high quotation probability among them. This finding advocates new understandings beyond the mainstream conclusion that network connections increase with similarity. It is also found that message networks offer significant implications to distinguish between accurate information and noise. Evidence shows that popular messages frequently quoted by others and redundant messages confirmed from different sources contain more accurate information for Bitcoin market predictions. Theoretical contributions and practical implications are discussed.     

Bitcoin合作式矿区挖矿研究

比特币（Bitcoin）作为一种新型电子货币从创造之初就受到各领域学者的广泛关注,越来越的人投身到挖矿的行列。但是比特币本身的产生机制导致越多人参与,比特币产出的效率就越低。大部分比特币产出都集中在少部分的专业挖矿组织手中,个人参与者回报率极低。为了解决挖矿产出不平衡、回报率低的问题,一种合作式矿区挖矿模型通过有效整合个人参与者的计算能力,按小组形式进行合作挖矿,后将挖矿所得利益在组内重新分配,以提高个人挖矿回报率。     

Two-factor authentication for the Bitcoin protocol

We show how to realize two-factor authentication for a Bitcoin wallet. To do so, we explain how to employ an ECDSA adaption of the two-party signature protocol by MacKenzie and Reiter (Int J Inf Secur 2(3–4):218–239, 2004. doi: 10.1007/s10207-004-0041-0) in the context of Bitcoin and present a prototypic implementation of a Bitcoin wallet that offers both: two-factor authentication and verification over a separate channel. Since we use a smart phone as the second authentication factor, our solution can be used with hardware already available to most users and the user experience is quite similar to the existing online banking authentication methods.     

A survey of Blockchain consensus algorithms:mechanism,design and applications

In 2008,Blockchain was introduced to the world as the underlying technology of the Bitcoin system.After more than a decade of development,various Blockchain sys...