【Abstract】The fast proliferation of digital twin (DT) establishes a direct connection between the physical entity and its deployed digital representation. As markets shift toward mass customization and new service delivery models, the digital representation has become more adaptive and agile by forming digital twin networks (DTNs). The DTN institutes a real-time single source of truth everywhere. However, there are several issues preventing DTNs from further application, including centralized processing, data falsification, privacy leakage, lack of incentive mechanism, and so on. To make DTN better meet the ever changing demands, we propose a novel block-chain-enabled adaptive asynchronous federated learning (FedTwin) paradigm for privacy-preserving and decentralized DTNs. We design Proof-of-Federalism (PoF), which is a tailor-made consensus algorithm for autonomous DTNs. In each DT's local training phase, generative adversarial network enhanced differential privacy is used to protect the privacy of local model parameters, while a modified Isolation Forest is deployed to filter out the falsified DTs. In the global aggregation phase, an improved Markov decision process is leveraged to select optimal DTs to achieve adaptive asynchronous aggregation while providing a rollback mechanism to redact the falsified global models. With this article, we aim to provide insights to forthcoming researchers and readers in this under-explored domain.
【Abstract】The emerging collaborative authentication schemes are capable of outperforming the conventional isolated methods as a benefit of their multi-dimensional data/information gleaned, but they face new challenges in the sixth generation (6G) wireless networks owing to their increased overhead, limited flexibility and autonomy. Moreover, they may also be vulnerable to the privacy leakage of individual entities. These challenges are mainly due to the complex heterogeneous network architecture, owing to the distributed nature of the devices and information involved as well as the diverse security requirements of the 6G-aided vertical systems. As a remedy, we introduce autonomous collaborative authentication for achieving security enhancement through the situation-aware cooperation of different security mechanisms, of heterogeneous security information/context, and of heterogeneous devices and networks. For this purpose, a federated learning-based collaborative authentication scheme capable of privacy-preservation is developed, where cooperative peers observe and locally analyze heterogeneous information of the authenticating device, and afterwards update their authentication models locally. By sharing their authentication models rather than directly sharing the observed authentication information, privacy preservation can be achieved based on the proposed scheme. Moreover, given the time-varying heterogeneous network environment and the wide range of quality-of-service (QoS) requirements, the membership of the group collaborating in support of distributed authentication is updated based on the situation-dependent conditions. To further reduce the communication overhead, a locally collaborative learning process is further developed, where both the updated parameters and observed authentication information are stored and processed locally at the cooperative peers. Finally, a smart contract is designed for achieving collaborative security combined with privacy preservation and for providing accountable services.
【Abstract】The localization process is necessary for intelligent multimedia systems to provide appropriate service, but it is still a significant challenge to provide localization services for devices without active localization ability. The vulnerability of existing localization frameworks is that the incredibility of the information provided can not be verified. This remains the localization process vulnerable to forgery attacks, which can cause false localization results and impact the performance of intelligent multimedia systems. To address this problem, a blockchain-based fingerprint localization scheme is proposed and evaluated in this article. Firstly, A real-time database of verified and temper-proof electromagnetic fingerprints is established by collecting the information from contributors through blockchain. Secondly, a distributed algorithm is designed to obtain a trusted localization based on shared electromagnetic fingerprint information. Lastly, to save on-chain computing resources and defend against spoofing attacks and collusion attacks, an on-chain/off-chain scheme is proposed. The simulations show the practicability and robustness of the proposed scheme. The results are analyzed based on localization accuracy and resistance to malicious activities. It is shown that devices can be located without increasing location errors in malicious environments where 20% of data is uploaded by malicious nodes, and the localization results become more accurate as the decentralized database spontaneously established is expanded.
【Abstract】Aiming at the problems of low decentralization, low motivation for node voting, and malicious behavior of nodes for the traditional DPoS consensus mechanism in the blockchain-based UAV-assisted mobile edge computing environment, this paper proposes an improved DPoS-based consensus mechanism approach. First, the framework of a blockchain-based UAV-assisted mobile edge computing system is given, and the consensus mechanism design problem in this framework is analyzed. Second, a proxy node selection model is established based on the rights and votes obtained by the blockchain nodes, and the proxy nodes are selected to participate in the consensus process of the current cycle. Then, the voting behavior, block generation behavior, and block verification behavior of nodes are classified into positive and malicious behaviors to reward and punish the reputation value of nodes. Finally, a blockchain-based UAV-assisted mobile edge computing experimental environment is built, and the TDPoS algorithm, ADRP algorithm, and RDPoS algorithm are used as benchmark algorithms to experimentally compare with the proposed improved DPoS consensus-based algorithm. The experimental results show that the algorithms in this paper can improve network throughput, reduce block-out delay, and increase the proportion of secure proxy nodes.
【Abstract】In this paper, a novel microgrid (MG) restoration framework is proposed based on Blockchain Technology (BCT). The proposed method consists of a two-stage restoration process. In the first stage, stable Blockchain (BC) links are formulated with the grid-forming Distributed Energy Resources (DERs). In the second stage, load assignment is carried out based on the priority level of the load. The miners run through the consensus mechanism to accommodate the priority-based loads to their corresponding BC links. The consensus mechanism provides the value of an index, known as Combined Stability Measurement (CSM). The BC link, with the higher CSM value, is declared as the winner of the consensus mechanism. Subsequently, the targeted priority load is assigned to that winner BC link. The proposed BCT-based restoration framework is tested with the modified IEEE-33 and IEEE-69 bus test systems using the Ethereum blockchain platform.
【Abstract】Cryptocurrency has gained in popularity in emerging markets, however the knowledge accumulation pertaining to factors contributing to intention to use cryptocurrency has been limited. To address this gap, we meta-analyzed 42 samples from multiple theoretical approaches. Seven common antecedents to intention to use cryptocurrency were assessed, as well as six moderators via meta-regression. A regression model to explain the intention to use cryptocurrency was calculated, and relative importance analysis determined the weight of each variable in predicting cryptocurrency use intention. The findings highlight factors influencing intention to use cryptocurrency in emerging markets and refine theoretical models for future research.
【Abstract】Recently, the automotive industry has been characterized by disruptive innovations, like self-driving cars or hybrid/electric engines. Despite this fact, some operations, such as the trade of second-hand vehicles, still continue to be carried out in the "traditional" way, in which the buyer has to trust the seller about the state of the vehicle. Several studies highlighted that odometer fraud alone could cost around 8.9 billion euros per year. In order to overcome these limitations, which are related to information asymmetries between buyers and sellers, in this work we propose to exploit blockchain technology to store a previous vehicle's history in a transparent way. To further explore blockchain advantages, we also present how a decentralized second-hand vehicle market- enabling also automatic transfers of ownership upon monetary transfers- can be built, leveraging on Non-Fungible Tokens (NFTs). We propose an architecture and a practical implementation of a Decentralized Application (Dapp) and discuss the security of the proposed system, its costs, and future developments.
【Abstract】The proper operation of microgrids depends on Economic Dispatch. It satisfies all requirements while lowering the microgrids' overall operating and generation costs. Since distributed generators constitute a large portion of microgrids, seamless communication between generators is essential. While guaranteeing a reliable microgrid operation, this should be achieved with the fewest losses as possible. The distributed generator technology introduces noise into the system by design. To find the best economic dispatch strategy, noise was considered in this research as a limitation in grid-connected microgrids. The microgrid's performance was improved, and the proposed technique also showed increased resilience. A virtual synchronous generator (VSG) control approach is proposed with a noiseless consensus-based algorithm to improve the power quality of microgrids. Voltage and frequency regulation modules are the foundation of the VSG paradigm. The synchronous generator's second-order equation (hidden-pole configuration) was also used to represent the voltage of the stator and rotor motion. This study compared changes in power, frequency, and voltage for the microgrid by utilizing the described control approach using MATLAB. According to the findings, this method aids in controlling load and noise variations and offers distributed generators an efficient control strategy.
【Abstract】Surmounted environmental concerns and energy challenges have created an augmented awareness among the public and policymakers about alternate energy resources. Using a network approach, this paper aims to investigate the dependence between cryptocur-rencies and the alternative energy market using data from January 1, 2018, to December 23, 2021. For this investigation, first, we build a static dependency network for a given set of variables using partial correlations. Then, we demonstrate within-system connec-tions in a minimum spanning tree (MST) to assess the centrality of all variables. Finally, rolling-window estimations are made to exhibit time variations in both dependency and centrality networks. We find that clean alternative markets (SPGCE, ELEVHC & WILCE) and ETH are net risk transmitters to other markets and system-wide net contributors. We also demonstrate how SPGCE is essential for tying together the various parts of the networks and provide convincing evidence of time-varying within-system dependency. Our thorough examination of the dependency analysis offers significant insights to macroprudential reg-ulators, policymakers, and portfolio managers, enabling them to safeguard the most vul-nerable markets and choose the best legislative and policy measures to protect investors' interests in the face of unforeseen financial and economic conditions.& COPY; 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
【Abstract】Blockchain, an emerging technology benefits the new technological world from its features such as immutability, transparency, and decentralization. The diversity of its domain is from e-commerce, health care, real estate, and enterprise to NFT markets, voting, and digital currency trading. The underlying blockchain features make auditing blockchain applications a challenging task. In this paper, we thoroughly analyze the general challenges faced in blockchain forensics, application-specific challenges, and challenges with respect to public and private blockchains. The aim of this paper is to highlight the challenges faced during the forensics of blockchain-based applications. For this, we took a healthcare system, introduced a contract vulnerability in it, and defined two scenarios for attack depending on that vulnerability. One that allows an attacker to make a malicious transaction directly and the other in which the attacker first gives itself access and then adds malicious transactions. The attacks are generated just to analyze the difficulty level of forensics in blockchain applications. To achieve our goal, we performed log analysis for both scenarios and specified the challenges faced during the analysis. Our experiment shows that due to some blockchain-specific features such as anonymity, identification of malicious entities in the system sometimes becomes a hectic challenge. This research benefits the auditors by highlighting the forensics challenges and auditing issues so they can work on these areas to identify the attackers and illegal data modifications accurately in blockchain applications. Experimental results confirmed that our proposed technique enabled efficient forensics investigation of events inside blockchain-based healthcare applications.
【Abstract】Consent is one of six legal bases for personal data processing mentioned in the General Data Protection Regulation (GDPR). The GDPR is a privacy law giving European Union (EU) citizens authority over personal data. It enforces software systems to collect, analyze, and share only necessary information ('data minimization') following the specific purpose ('consent'). The GDPR defines consent as permission of individuals ('data subjects') to give organizations ('data controllers') processing their personal data. Without a data subject's consent, the data controller processes personal data unlawfully. Therefore, consent management is an essential component of a software system to build data subjects' trust and engagement. However, sharing data can lead to a potential loss of control over personal data, as data are across boundaries between software services. One of the significant risks is caused by a lack of developers' experience in data protection practices. Hence, in this paper, we propose to use blockchain technology to manage data subjects' informed consent for data sharing to build trust, transparency, and traceability to share data across software services. We formalized the semantics of smart contracts to extend the blockchain features to validate the consent authorization and manage the request-response interaction between the services. Furthermore, we used the Event-B method to describe the dynamic behavior of the proposed model and prove its correctness. Finally, we provided a mapping from the formal model to a smart contract class diagram and a prototype called SmartDataTrust implemented with solidity and Python REST API that developers can easily utilize. & COPY; 2023 Elsevier Inc. All rights reserved.
【摘要】智能合约的安全性对于区块链在供应链领域的应用尤为重要。目前，大多数对智能合约的形式化验证工作集中于漏洞检测，对于如何在部署上链前生成安全的智能合约的关注仍然比较少，如何有效规范地将特定领域的属性安全地映射为智能合约代码存在难点。因此，提出在编写合约前基于CPN(Coloured Petri Net)对供应链业务逻辑进行形式化规范并构建双层仿真模型，以图形化界面描述交易状态变化，进行形式化验证和状态分析，从而在建模阶段就减少逻辑漏洞。最后，提供了一种从CPN建模语言到Solidity编写的合约的转换方法，以提高智能合约的安全性和可靠性。
