From enfant terrible to problem-solver? Tracing the competing discourse to explain blockchain-related technological diffusion

Since the inception of blockchain-related technologies over a decade ago, investors’ uptake of the technologies has grown rapidly. But even with the advancement in standing from conceptual beginnings to real-world experimentation, mainstream adoption of the technologies in either organizational or individual contexts has yet to eventuate. To resolve this paradox, we examine progression of the technologies’ diffusion instead, and in the process, seek to uncover the underlying dynamics of sentiments at play. Diffusion involves multiple actions by different parties, with social discourses via diverse media playing an essential role. In demonstrating the interplay of support to resistance via media framing and the diffusion of innovation theory, findings from our paper contribute to the technology adoption literature. Understanding resistant behavior toward a new technology area could help resolve potential issues that may arise. This would hopefully lead to better technological implementation outcomes in future.     

Distributed privacy protection strategy for MEC enhanced wireless body area networks

With the rapid development and widespread application of Wireless Body Area Networks (WBANs), the traditional centralized system architecture cannot handle the massive data generated by the edge devices. Meanwhile, in order to ensure the security of physiological privacy data and the identity privacy of patients, this paper presents a privacy protection strategy for Mobile Edge Computing(MEC) enhanced WBANs, which leverages the blockchain-based decentralized MEC paradigm to support efficient transmission of privacy information with low latency, high reliability within a high-demand data security scenario. On this basis, the Merkle tree optimization model is designed to authenticate nodes and to verify the source of physiological data. Furthermore, a hybrid signature algorithm is devised to guarantee the node anonymity with unforgeability, data integrity and reduced delay. The security performance analysis and simulation results show that our proposed strategy not only reduces the delay, but also secures the privacy and transmission of sensitive WBANs data.     

Value drivers of blockchain technology: A case study of blockchain-enabled online community

There is growing recognition that blockchain technology has significant potential to alter how organizations and people work and communicate. However, theoretical guidance concerning how organizations leverage blockchain technology to enhance value creation for users is still limited. Grounded in the socio-technical perspective and leveraging the rich data obtained from case analyses of blockchain-enabled online communities, this paper develops a theoretical model to identify the core value drivers that blockchain enables for online communities. The core value drivers include: a reputation-value system, data ownership mechanisms, and verification & tracking mechanisms. Our findings suggest that these three value drivers enhance value creation of online communities by motivating participation and protecting contributions.     

Blockchain verification and validation: Techniques,challenges, and research directions

As blockchain technology is gaining popularity in industry and society, solutions for Verification and Validation (V&V) of blockchain-based software applications (BC-Apps) have started gaining equal attention. To ensure that BC-Apps are properly developed before deployment, it is paramount to apply systematic V&V to verify their functional and non-functional requirements. While existing research aims at addressing the challenges of engineering BC-Apps by providing testing techniques and tools, blockchain-based software development is still an emerging research discipline, and therefore, best practices and tools for the V&V of BC-Apps are not yet sufficiently developed. In this paper, we provide a comprehensive survey on V&V solutions for BC-Apps. Specifically, using a layered approach, we synthesize V&V tools and techniques addressing different components at various layers of the BC-App stack, as well as across the whole stack. Next, we provide a discussion on the challenges associated with BC-App V&V, and summarize a set of future research directions based on the challenges and gaps identified in existing research work. Our study aims to highlight the importance of BC-App V&V and pave the way for a disciplined, testable, and verifiable BC development.     

A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain

Recently, the applications of Blockchain technology have begun to revolutionise different aspects of supply chain (SC) management. Among others, Blockchain is a platform to execute the smart contracts in the SC as transactions. We develop and test a new model for smart contract design in the SC with multiple logistics service providers and show that this problem can be presented as a multi-processor flexible flow shop scheduling. A distinctive feature of our approach is that the execution of physical operations is modelled inside the start and completion of cyber information services. We name this modelling concept ‘virtual operation’. The constructed model and the developed experimental environment constitute an event-driven dynamic approach to task and service composition when designing the smart contract. Our approach is also of value when considering the contract execution stage. The use of state control variables in our model allows for operations status updates in the Blockchain that in turn, feeds automated information feedbacks, disruption detection and control of contract execution. The latter launches the re-scheduling procedure, comprehensively combining planning and adaptation decisions within a unified methodological framework of dynamic control theory. The modelling complex developed can be used to design and control smart contracts in the SC.     

The novel secure testament methodology for cryptocurrency wallet using mnemonic seed

ABSTRACT

Recently, cryptocurrencies such as Bitcoin, Ethereum, etc, have rapidly been recognized as an asset, often called a digital asset. Comparing to the real assets, it would be handled carefully due to its own characteristics that are completely different. The disadvantage of such digital assets, on the one hand, is that whoever knows the private key of the wallet, they can easily take over that digital asset. On the other hand, if the wallet’s owners are dead without passing credential information to others, that asset will be lost forever. We thus propose the novel secure testament methodology for a digital asset such as Bitcoin to solve the mentioned problems. The mechanism is based on managing the mnemonic seed of the wallet so that an inheritor will obtain the mnemonic seed in a secure way. Two mechanisms of the proposed methodology are implemented. The first is to save the mnemonic seed in a secure repository. Therefore, no one can access to the cryptocurrency wallet while the owner still being alive and does not wish anybody to access. The second is to deliver the mnemonic seed securely to legitimate inheritor when the owner is suspected to be dead or disappeared. Finally, based on our experiment, the results show that the aforementioned problems can be solved. Furthermore, the proposed mechanism can help the owner of the asset to managing the confidentiality of their assets.     

An analysis model for detecting misbehaviors in anonymous cryptocurrency

In online shopping, consumers often rely on information such as sales, reviews or ratings to inform their decision making. Such preferences or user behaviors can be subjected to manipulation. For example, a merchant can artificially inflate product sales by paying a click farm. Specifically, the click farm will recruit a number of non-genuine buyers to purchase the products. After the purchases have been made, the buyers will either refund the product minus the commission or no product exchange actually takes place and these buyers are paid a commission for their role in the activity. Increasingly due to the popularity of cryptocurrency, such as bitcoin, such payment mechanisms are used in such activities. Hence, in this paper, we seek to detect click farm transactions using cryptocurrency. Specifically, we propose three models to capture click farm operations, and based on the models we design three algorithms to detect anonymous click farm transactions. Extensive analysis demonstrates that our model achieves a high accuracy rate in detecting anonymous click farm transactions, without incurring expensive computational costs.     

Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin

This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all bitcoins in existence represent approximately $7 billion, and more than $60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.Using cross-sectional empirical data examining 66 of the most widely used cryptocurrencies, a regression model was estimated that points to three main drivers of cryptocurrency value: the level of competition in the network of producers, the rate of unit production, and the difficulty of algorithm used to “mine” for the cryptocurrency. These amount to relative differences in the cost of production of one digital currency over another at the margin, pointing to differences in relative cost of production – electricity goes in, cryptocurrency comes out. Using that as a starting point, a no-arbitrage situation is established for Bitcoin-like cryptocurrencies followed by the formalization of a cost of production model to determine the fair value of a bitcoin.     

基于形式化方法的区块链系统漏洞检测模型

随着区块链技术在各行各业的广泛应用,区块链系统的架构变得越来越复杂,这也增加了安全问题的数量.目前,在区块链系统中采用了模糊测试、符号执行等传统的漏洞检测方法,但这些技术无法有效检测出未知的漏洞.为了提高区块链系统的安全性,本文提出了基于形式化理论的区块链系统漏洞检测模型VDMBS (Vulnerability Detection Model for Blockchain Systems),该模型综合了系统迁移状态、安全规约和节点间信任关系等多种安全因素,同时提供了基于业务流程执行语言BPEL (Business Process Execution Language)流程的漏洞模型构建方法.最后,本文用NuSMV在基于区块链的电子投票选举系统上验证了所提出的漏洞检测模型的有效性,实验结果表明,与现有的五种形式化测试工具相比,所提出的VDMBS模型能够检测出更多的区块链系统业务逻辑漏洞和智能合约漏洞.