【Abstract】The new generation of digital intelligence technology enables knowledge creation, dissemination, and application to undergoing parallel changes. Scientific systems face an increasingly uncertain, diverse, and complex environment, making adopting multidisciplinary, interdisciplinary, and transdisciplinary approaches to research issues inevitable. Existing scientific systems follow linear value streams, leading to problems, such as inefficiency, unfairness, and knowledge monopoly. Decentralized science (DeSci) is a new scientific development paradigm based on Web3, Metaverses, and decentralized autonomous organizations and operations (DAOs) technologies, that can solve organizational and management problems in scientific systems through organizing, coordinating, and executing techniques. However, new economic theories and methods are still needed to effectively solve the problem of linear value flow in scientific systems. Metaeconomics based on the parallel intelligence theory, also known as decentralized economics (DeEco), provides a new approach and idea for redesigning the economic system of scientific markets. Thus, this article proposes a research framework and core mechanisms of DeSci MetaMarkets based on parallel economic theory to provide effective and practical methodologies for scientific system governance.
【Abstract】Managing versions of data for building information modeling (BIM) data is critical for design collaboration, especially with multiple disciplines involved where each team has specific data requirements and design pro-cedures. However, existing version control approaches are still inefficient for two limitations: (1) lacking an efficient data structure for managing version dependencies among multi-disciplinary BIM models and (2) risking data manipulation due to a centralized versioning architecture that may lead to reworking, losing design traceability and raising disputes. Blockchain technology is an emerging and promising solution for version management as it provides a decentralized, immutable, and traceable database paradigm. Hence, this paper proposes a blockchain-aided solution for secure and efficient BIM versioning with three major innovations. Firstly, a two-layer container common data environment (TLCCDE) model integrating blockchain and Inter-planetary File System (IPFS) is developed to illustrate an overall logic for BIM versioning in a distributed environment. Secondly, a smart contract swarm (SCS) is developed to automate versioning actions in the TLCCDE. Thirdly, a novel multi-branch structure (MBS) with efficient algorithms is designed to simultaneously manage version change continuity, issue attachment, and dependency compliance. The proposed TLCCDE model is evaluated and validated in design scenarios based on a real-world project. Results show that: (1) the TLCCDE model is workable in BIM versioning; (2) TLCCDE computing performance metrics, including SCS latency and throughput, as well as MBS latency and scalability, are all validated to be practical; and (3) the TLCCDE out-performs existing versioning approaches by augmenting dependency automation and versioning cybersecurity.
【Abstract】A cryptocurrency token airdrop is a novel means of distributing rights over a blockchain project to a community of users and owners for free. The market value of these airdrop giveaways is often upwards of hundreds of millions of dollars. This paper considers why projects might choose this unusual and costly means of token distribution. It considers a selection of high-profile airdrops as case studies between 2014 and 2022. This is the first comprehensive analysis of the rationales and mechanisms of Web3 token airdrops. We find that two primary rationales for airdrops are marketing (to attract new users and to maintain a community) and de-centralisation of ownership and control of a project (building community, providing regulatory protection, and enhancing security). The paper contributes to an understanding of business practice and strategy in the emerging cryptocurrency and blockchain industry.
【Abstract】A large number of modern practices in financial forecasting rely on technical analysis, which involves several heuristics techniques of price charts visual pattern recognition as well as other technical indicators. In this study, we aim to investigate the potential use of those technical information (candlestick information as well as technical indicators) as inputs for machine learning models, especially the state-of-the-art deep learning algorithms, to generate trading signals. To properly address this problem, empirical research is conducted which applies several machine learning methods to 5 years of Bitcoin hourly data from 2017 to 2022. From the result of our study, we confirm the potential of trading strategies using machine learning approaches. We also find that among several machine learning models, deep learning models, specifically the recurrent neural networks, tend to outperform the others in time-series prediction.
【Abstract】Smart contracts are programs deployed on blockchains that run upon meeting predetermined conditions. Once deployed, smart contracts are immutable, thus, defects in the deployed code cannot be fixed. As a consequence, software engineering anti-patterns, such as code cloning, pose a threat to code quality and security if unnoticed before deployment. In this paper, we report on the cloning practices of the Ethereum blockchain platform by analyzing 33,073 smart contracts amounting to over 4MLOC. Prior work reported an unusually high 79.2% of code clones in Ethereum smart contracts. We replicate this study at the conceptual level, i.e., we answer the same research questions by employing different methods. In particular, we analyze clones at the granularity of functions instead of code files, thereby providing a more fine-grained estimate of the clone ratio. Furthermore, we analyze more complex clone types, allowing for a richer analysis of cloning cases. To achieve this finer granularity of cloning analysis, we rely on the NiCad clone detection tool and extend it with support for Solidity, the programming language of the Ethereum platform. Our analysis shows that most findings of the original study hold at the finer granularity of our study as well; but also sheds light on some differences, and contributes new findings. Most notably, we report a 30.13% overall clone ratio, out of which 27.03% are exact duplicates. Our findings motivate improving the reuse mechanisms of Solidity, and in a broader context, of programming languages used for the development of smart contracts. Tool builders and language engineers can use this paper in the design and development of such reuse mechanisms. Business stakeholders can use this paper to better assess the security risks and technical outlooks of blockchain platforms.
【Abstract】This research focuses on addressing the privacy issues in healthcare advancement monitoring with the rapid establishment of the decentralised communication system in the Internet of Medical Things (IoMT). An integrated blockchain homomorphic encryption standard with an in-build supervised learning-based smart contract is designed to improvise personal data prevention. The Internet of Medical Things (IoMT) has advanced in healthcare with the rapid establishment of decentralised communication systems. Distributed ledgers have resource constraints to leverage public, private, and hybrid blockchain transactions to facilitate heterogeneous operations. The authors propose a supervised learning strategy in healthcare to mitigate learning health-related issues, improvise clinical monitoring, and ensure secure communication. The proposed approach handles the vast IoMT data by adopting blockchain for IoMT as (BIoMT) to preserve sensitive clinical information. It incorporates hybrid encryption techniques to improve patient and health records' privacy protection. BIoMT also maintains secured and sustainable supply chain management with a highly confidential decentralised framework using blockchain-based smart contracts, which minimises data loss. Moreover, a framework is designed with a hybrid hashing that integrates a homomorphically encrypted algorithm to support a smart contract for decentralised applicability. The BIoMT approach is tested and compared with the relevant prevention mechanisms. The evaluation shows that the effects observed from the result analysis noted that the proposed method outperforms reliable prevention mechanisms compared to the existing approaches.
【Abstract】A digital twin (DT) is an exact digital replica of a physical world object or asset that aids in managing, controlling, or monitoring the real object. The current systems used for managing DTs are centralized and not easily accessible. Typically, a DT is built by the original equipment manufacturer (OEM) and becomes hard to access and manage once its physical asset is transported or sold to a new owner. Moreover, a physical asset or object is typically comprised of many other physical sub-components. This translates to having one DT comprised of other sub-DTs. In this paper, we show how non-fungible tokens (NFTs) can be used to manage ownership of DTs and to provide proof of delivery (PoD) of their associated physical assets in a decentralized, secure, traceable, and transparent manner. Specifically, we propose, implement, and evaluate a solution to manage DTs and their sub-DTs using NFTs and sub-NFTs. The DTs and their sub-DTs are represented in a hierarchical way, whereby a sub-NFT maps to a sub-DT along with its physical object. We present the system architecture and design, as well as the implementation of algorithms and smart contracts along with thorough testing and validation details. We present the security analysis as well as discuss the generalization aspect of the proposed solution. All developed smart contract codes are made publicly available on GitHub.(c) 2023 Elsevier B.V. All rights reserved.
【Abstract】Since its inception, bitcoin has used the popular consensus protocol proof-of-work (PoW). PoW has a well-known flaw: it distributes all rewards to a single miner (or pool) who inserts a new block. Consequently, the variance of rewards and the mining enterprise risk are extremely high. In 2016, Shi proposed addressing this problem with a theoretical algorithm. We introduce an easily-implemented PoW variant that improves Shi's idea. The network must not find a single nonce but a few to insert a block. This simple change allows for a fairer distribution of rewards and also has the effect of regularizing the insertion time of blocks. This method would facilitate the emergence of small pools or autonomous miners.
【Abstract】A proof of work (PoW) is an important cryptographic construct which enables a party to convince other parties that they have invested some effort in solving a computational task. Arguably, its main impact has been in the setting of cryptocur-rencies such as Bitcoin and its underlying blockchain protocol, which have received significant attention in recent years due to its potential for various applications as well as for solving fundamental distributed computing questions in novel threat mod-els. PoWs enable the linking of blocks in the blockchain data structure, and thus the problem of interest is the feasibility of obtaining a sequence (???chain???) of such proofs. At the same time, the rapid development in quantum computing makes the threats to cryptography more and more concerning. In this work, we examine the hardness of finding such chain of PoWs against quantum strategies. We prove that the chain of PoWs problem reduces to a problem we call multi-solution Bernoulli search, for which we establish its quantum query complexity. Effectively, this is an extension of a threshold direct product theorem to an average-case unstructured search problem. Our proof, adding to active recent efforts, simplifies and generalizes the recording technique due to Zhandry [Crypto 2019]. As an application, we revisit the formal treatment of security of the core of the Bitcoin consensus protocol, called the Bitcoin backbone [Eurocrypt 2015], in a setting where the adversary has quantum capabilities while the honest parties remain classical, and show that the protocol???s security holds under a quantum analogue of the classical ???honest majority??? assumption that we formulate. Our analysis indicates that the security of the Bitcoin backbone protocol is guaranteed provided that the number of adversarial quantum queries is bounded so that each quantum query is worth O(p???1/2) classical ones, where p is the probability of success of a single classical query to the protocol???s underlying hash function. Somewhat surprisingly, the wait time for safe settlement of transactions in the case of quantum adversaries matches (up to a constant) the safe settlement time in the classical case.
【Abstract】The uncertainty decision modeling of control engineering tools to support industrial cyber-physical metaverse smart manufacturing systems (ICPMSMSs) falls under the multicriteria decision-making problem for three reasons: the presence of multiple industry cyber-physical system (ICPS) components, the importance degree of these components, and the variation in data. It is unfortunate that none of the control engineering tools developed to support ICPMSMS have been able to satisfy all ICPS components, despite the tremendous effort expended. Consequently, selecting the best control engineering tool to support ICPMSMS is a challenging task. Although literature reviews have evaluated control engineering tools, informational ambiguity and uncertainty remain open issues. This study extends fuzzy weighted with zero inconsistency (FWZIC) with interval-valued spherical fuzzy rough sets (IvSFRSs) to weight the components of the ICPS. Then, the developed IvSFRS-FWZIC method is integrated with the PROMETHEE II method to uncertain the modeling of control engineering tools. Results of the IvSFRS-FWZIC revealed that cybersecurity was the most influential component, whereas the digital twin component was the least influential. According to PROMETHEE II results, tool_1, tool_3, and tool_2 achieved the first model among the ten tools. Finally, the robustness of the proposed methods is evaluated by conducting sensitivity and comparative analysis.
【Abstract】Heterogeneity in informational inefficiency in a cross-market virtual currency, such as Bitcoin, allows for the extraction of differential gains from a portfolio of investments over time. In this paper, we measure inefficiency in five country/region segmented Bitcoin markets based on dynamic estimation of the fractional integration order of their price series. Results reveal a timevarying and country-specific pattern of inefficiency in the five Bitcoin markets, although the degree of inefficiency in each market has declined over time. Further, we introduce a new decomposition method to disentangle components of the inefficiency degree. Results suggest that the total variation around the convergence benchmark has fallen, whilst the proportion due to the difference between convergence and efficiency has risen from approximately 77% in 2013 to almost 100% in 2020. Besides, evidence of convergence emerges until the outbreak of COVID-19, beyond which the inefficiency degree diverges measurably. We show that Bitcoin markets have become more efficient after the first-wave COVID era and then the nature of market segmentation has played a less important role, levelling the cross-market difference and thus reducing the potential for arbitrage.
【Abstract】With the development of sustainable theory, environmental and resource issues have become one of the major challenges facing human society. As an important part of social economy, enterprises are also an important source of carbon emissions and environmental pollution. With the growth of the digital economy, digital technology has played an important role in improving economic efficiency. Digital transformation can not only enable enterprises to obtain and allocate resources more efficiently and reasonably, but can also provide a powerful driving force for the healthy development of the environment. This can improve the positive role and impact of enterprises on environmental development. Based on the overview of social carbon neutrality and green sustainable development goals, this paper made an in-depth study of digital transformation to help carbon neutrality and green sustainable development. In order to verify its effect, this paper took a medium-sized enterprise as the object, analyzed the growth of its economic and environmental benefits in the process of digital transformation, and compared it with the traditional development strategy. The empirical results showed that in the perspective of the Metaverse, the highest growth rate of environmental benefits of the enterprise would reach 19.6% every month in 2021. From this data, digital transformation based on the perspective of the Metaverse was more able to help carbon neutrality and green sustainable development.
【Abstract】This paper presents a novel collaboration scheme for secure cloud file sharing using blockchain and attribute -based encryption(ABE). Blockchain enables us to implement access control as a smart contract between data owner and users. Each data owner creates its own smart contract where in a data user can request to access a specific file by registering a transaction. In response transaction, the data owner sends the required credential to the user thereby enabling her/him to decrypt the intended file on the cloud storage. This scheme is decentralized, fault tolerant and secured against DoS attacks. The cipher-key, which is used for file encryption, is embedded into a set of coefficients of a polynomial so-called access polynomial. It is attached to the encrypted file on the cloud storage as a metadata. The data user can restore the cipher-key by means of the credential receiving in response transaction and access polynomial. The data owner uses ABE scheme in response transaction to impose her/him access policy to the file as well as preserving user anonymity. This scheme supports fast revocation of the user access by means of updating the access polynomial coefficients and without any communication overhead to non-revoked users. Through formal verification, we show that the scheme is secure in terms of secrecy of credential information and authentication of participants. Finally, the evaluation results show that our scheme is scalable with acceptable performance up to 20,000 users.
【Abstract】Smart contracts have been widely used in the blockchain world these years, and simultaneously vulner-ability detection has gained more and more attention due to the staggering economic losses caused by the attacker. Existing tools that analyze vulnerabilities for smart contracts heavily rely on rules predefined by experts, which are labour-intense and require domain knowledge. Moreover, predefined rules tend to be misconceptions and increase the risk of crafty potential back-doors in the future. Recently, researchers mainly used static and dynamic execution analysis to detect the vulnerabilities of smart contracts and have achieved acceptable results. However, the dynamic method cannot cover all the program inputs and execution paths, which leads to some vulnerabilities that are hard to detect. The static analysis method commonly includes symbolic execution and theorem proving, which requires using constraints to detect vulnerability. These shortcomings show that traditional methods are challenging to apply and expand on a large scale. This paper aims to detect vulnerabilities via the Bug Injection framework and transfer learning techniques. First, we train a Transformer encoder using multi-modality code, which contains source code, intermediate representation, and assembly code. The input code consists separately of Solidity source code, intermediate representation, and assembly code. Specifically, we translate source code into the intermediate representation and decompile the byte code into assembly code by the EVM compiler. Then, we propose a novel entropy embedding technique, which combines token embedding, segment embedding, and positional embedding of the Transformer encoder in our approach. After that, we utilize the Bug Injection framework to automatically generate specific types of buggy code for fine-tuning and evaluating the performance of vulnerability detection. The experimental results show that our proposed approach improves the performance in detecting reentrancy vulnerabilities and timestamp dependence. Moreover, our approach is more flexible and scalable than static and dynamic analysis approaches in detecting smart contract vulnerabilities. Our approach improves the baseline approaches by an average of 11.89% in term of F1 score.(c) 2023 Elsevier Inc. All rights reserved.
【Abstract】In 2022, Thailand's Demand Response (DR) business model was shifting from the Traditional Utility (TU) model to the Load Aggregator (LA) model in accordance with Thailand's smart grid master plan. This research studied the current demand response model and mechanism to draw possible gaps in operations. This research deals with the data system owned by the individual load aggregator. The load aggregators collect meter data and evaluate demand adaptations before sending the results to claim compensation on behalf of their customers. This approach lacks transparency and facilitates distortion of the facts. Hence, this research introduces the data execution by smart contracts and data records on the blockchain that enhance transparent data sharing among multiple parties and maintain data integrity. Moreover, the proposed bidding algorithm allows customers to offer an expected price under the maximum incentive payment determined by the avoided costs of running the peaking power plants. Hence, the bidding helps reflect the DR operation costs on the customer side and control the budget for incentive payments. This study emphasized the smart contracts and decentralized application layer, so the public blockchain is a reasonable network for the test. However, implementation in real cases using the public blockchain requires careful considerations, such as network fees, transaction speeds, and the security of smart contract codes.
【Abstract】This study investigates the diversifier, hedge and safe haven properties of stablecoins against various financial assets including cryptocurrencies such as Bitcoin, Ether, XRP and stock market indices. Using quantile coherency we show that stablecoins included in the study act as weak hedges in normal conditions and weak safe havens when considering moments of market turmoil and there is little evidence to support the existence of any contagion effects between the cryp-tocurrency and stablecoin markets. Aforementioned results are not significantly influenced by the choice of investment horizon. We further evaluate the implications of those results for the question of whether stablecoins are in fact stable.
【Abstract】Regarding the importance of the Internet of Things (IoT) and the Metaverse as two practical emerging technologies to enhance the digitalization of public transportation systems, this article introduces an approach for the improvement of IoT and unmanned electric vehicles in the Metaverse, called the Internet of Unmanned Electric Vehicles (IoUEVs). This research includes two important contributions. The first contribution is the description of a framework for how unmanned electric vehicles can be used in the Metaverse, and the second contribution is the creation of a digital twin for an unmanned electric vehicle. In the digital twin section, which is the focus of this research, we present a digital twin of an electronic differential system (EDS) in which the stability has been improved. Robust fuzzy logic algorithm-based speed controllers are employed in the EDS to independently control the EV wheels driven by high-performance brushless DC (BLDC) electric motors. In this study, the rotor position information of the motors, which is estimated from the low-precision Hall-effect sensors mounted on the motors' shafts, is combined and converted to a set of common switching signals for empowering the EDS of the electric vehicle traction drive system. The proposed digital twin EDS relies on an accurate Hall sensor signals-based synchronizing/locking strategy with a dynamic steering pattern capable of running in severe road conditions with different surface profiles to ensure the EV's stability. Unlike recent EDSs, the proposed digital twinning approach includes a simple practical topology with no need for auxiliary infrastructures, which is able to reduce mechanical losses and stresses and can be adapted to IoUEVs more effectively.
【Keywords】electronic differential system; electric vehicle (EV); digital twin; brushless DC (BLDC) motors; stability control; Internet of Unmanned Electric Vehicles (IoUEVs); Metaverse
【Abstract】Motivated by the relationship between trading intensity and volatility and the attractiveness of duration-based volatility estimators, this paper investigates the ability of price duration to forecast realized volatility of Bitcoin. Using high-frequency transaction data, trading intensity is measured by price duration and incorporated in the class of heterogeneous autoregressive (HAR) models. Results provide compelling evidence that trading intensity improves the forecasting performance of a highly competitive set of HAR models, commonly used in the literature. HAR extensions that incorporate price duration systematically deliver the lowest forecast errors and generate economically significant gains in volatility targeting exercise over multiple horizons. However, results show no evidence in favor of a unique duration-augmented model. The predictive ability of price duration is supported by a number of robustness checks, including alternative estimation windows, bull and bear market states, and alternative thresholds that define price events.
【Abstract】Smart contracts are a set of instructions or programs that are stored on the blockchain network and run when predetermined conditions are met. Ethereum smart contracts are deployed on blockchain networks. Ethereum smart contracts are immutable and are vulnerable to simple coding errors called vulnerabilities. The aim of this paper is to classify Ethereum smart contracts vulnerabilities by feature extraction using machine learning. Pixel values collected from images and trigram feature extraction were used to construct the dataset. This dataset was trained using Multilabel k Nearest Neighbours (MLkNN), Binary Relevance kNN (BRkNN), Random Forest (RF), and Naive Bayes (NB), among other machine learning methods. The Naive Bayes Method outperforms the other models in terms of F1-score among all the algorithms tested. The Naive Bayes model achieves F1-scores of 99.38% and 99.44% using Binary Relevance and Classifier Chain respectively. In terms of F1-score, the Random Forest model attained a substantial degree of performance, with F1-scores of 96.71% and 96.61% using Binary Relevance and Classifier Chain respectively. In comparison, the lazy algorithms MLkNN and BRkNN produced lower F1-scores of 88.19% and 89.71%, respectively. This suggests that using the TriPix dataset outperforms models employed in either opcode characteristics or image-based detection used in other works.
【Abstract】It is known that Bitcoin enables achieving fairness in secure computation by imposing monetary penalties on adversarial parties. This functionality is called secure computation with penalties. Bentov and Kumaresan (2014) [9] introduced the claim-or-refund functionality that can be implemented via Bitcoin. They achieved secure computation with penalties with O(n) rounds and O(n) broadcasts for any function, where n is the number of parties. After that, Kumaresan and Bentov (2014) [8] showed a constant-round protocol. Unfortunately, this protocol requires O (n2) broadcasts. As far as we know, no protocol achieves O (1) rounds and O(n) broadcasts based on Bitcoin. This work accomplishes such efficiency in secure computation with penalties. We first show a protocol in a slightly relaxed setting called secure computation with non-equivalent penalties. This setting is the same as secure computation with penalties except that every honest party receives more than a predetermined amount of compensation, while the previous one requires that every honest party receives the same amount of compensation. Namely, our setting allows the compensations for honest parties to be non-equivalent. Moreover, we present a technique to remove the non-equivalence of our protocol without sacrificing efficiency. We then propose a new ideal functionality called claim-refund-or-give that can be implemented via Bitcoin.(c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons .org /licenses /by /4 .0/).
【Abstract】In this demonstration, we present the working principles and key features of a unique mobile application named LegalHelper. The application is developed to address the existing challenges in terms of reduced interpretability and low perception of the legal documents as commonly faced by the general public. The core software is built up by leveraging the power of cutting-edge technologies such as Blockchain, Computer Vision, and Natural Language Processing. The main components to be demonstrated include Prominent Language Translator, Legal Maxim Library, and Contract Digitizer.
【Abstract】Intelligent transportation systems with Vehicle to Everything (V2X) connectivity can help smart cities solve problems like pedestrian jaywalking, vehicle collision, and traffic congestion. V2X offers seamless connectivity between road infrastructures and driver assistance systems with crowd-sourced data to guide design and feature sets. V2X applications raise security and privacy risks despite their benefits. Risks include data loss, device failure, and environmental damage. The current PKI-based V2X ecosystem requires many pseudonym keys to work successfully. Public Key Infrastructure (PKI) often encounters bottlenecks due to the enormous volume of authorisation, registration, and confirmation requests. When we transit to a means of fully autonomous transport, an enormous amount of data related to vehicle movement will flood the V2X network. A considerable infrastructure setup is needed to validate these messages. Blockchain technology offers distributed ledger technology and a decentralised data processing mechanism. So blockchain can solve the issue of validating the messages in the V2X network. This paper proposes Smartverse, a blockchain technology-based authentication method to validate messages in the V2X ecosystem. We used the Ethereum blockchain platform, Interplanatary File System (IPFS) and developed algorithms to validate the crowd-sourced data in the V2X network. When a user submits data, say vehicle collision, other users in the V2X network validate the data by a voting mechanism. Once the messages are marked valid, other V2X users will receive this message. This paper explains the blockchain-based V2X network architecture and message validation algorithm.
【Abstract】With a spike in usage of Blockchain in various fields like cryptocurrency, smart contracts, etc. due to its decentralized and digitally distributed peerto-peer network featuring elevated speed, efficiency and security. It provides the contract management solutions by consensus mechanism, scalability and reliability on `off-chain' resources. This work focuses on rectifying bugs and cybersecurity attacks e.g. Re-entrancy attacks with utilization of vaults, GHOST protocol, Bitcoin-NG, botnet C&C command, ERLAY protocol, bug prevention tools like Oyente and SolidiFi, and fuzzing tools like ReGuard and Contract-Fuzzer.
【Abstract】Lots of business processes can be benefited of the use of blockchain-based technologies. The distributed nature of the blockhain overcome a part of the reliability issues related to centralised systems. Recently the use of NFTs has been spread to multiple applications. The EIP-721 standard proposal defines the interface of non-fungible tokens (NFTs). This type of token was designed with the aim of creating interchangeable tokens but with the peculiarity of being unique and non-fungible and with the impossibility to be damaged or destroyed. For this reason, the EIP-721 standard has almost limitless applications: it can represent ownership of digital or physical assets, unlock access to certain services, ... In short, it can represent any single object or right that we can transfer between a sender and a receiver. In this paper we present a study on the transferability of the NFTs and its implications in the generation of secure applications. Currently, the NFTs can be transferred with the consent of the owner (by himself or by an authorised party) but the receiver of the token cannot decline the reception of the token, that will be transferred to his wallet. Therefore, we propose in this paper the enhancement of the NFT standard that allows the rejection of reception of tokens, obtaining a kind of token that can be used in a secure way in all kinds of applications that require the selective reception of the tokens.
【Abstract】The growth of the Internet has accelerated the distribution of digital content such as graphics and audio, and its copyright issues have gained attention. One particular industry worth noting, apparel design, has no explicit legal constraints, making piracy even easier. In this paper, we combine the decentralized and tamper-evident features of blockchain to design and implement a federated chain-based copyright management system for apparel design diagrams using the Hyperledger Fabric platform. In this paper, the copyright checking model uses perceptual hash algorithm and difference hash algorithm to calculate the graph similarity of garment effect and garment plan respectively, and calculate the mean value of similarity between them to determine whether they are plagiarized. The design diagrams are stored on IPFS, which makes up for the drawbacks of blockchain's difficulty in scaling and expensive storage space. Simulation experiments show that the blockchain system can maintain a high throughput and the originality checking model proposed in this paper can meet the practical requirements.
【Abstract】Neurofeedback Training (NFT) is an effective way for the participants to self-regulate the Electroencephalography (EEG) activity based on real-time feedback. This procedure has been proven to improve the neurological disorders in mentally ill patients and the psychological behavior of healthy individuals. Despite the considerable success of neurofeedback techniques, it is observed that some subjects fail to learn how to control their brain activities during neurofeedback training. This study is aimed to investigate the EEG learning process in alpha neurofeedback as an early-stage predictor of learners and nonlearners in terms of the enhancement of alpha-band activities. 25 healthy participants have been trained using alpha upregulations. 8 of them were unable to regulate their alpha band within each session. Hence in this work resting state eyes-open EEG is used to predict the learning performance of the NFT participants. Using machine learning. A comparison of three machine learning algorithms; LDA, SVM, and GBM is performed to predict the non-learners based on the absolute alpha power and its Daubechies (level-4) wavelet decompositions eyes-open resting state EEG signals.
【Abstract】This article presents a blockchain-supported evaluation and publishing method for kinematic models. As a modeling tool, OpenSim was chosen. The blockchain facilitates the hiding of the private part of the model, preserving the authors' rights, and, at the same time, the publication of that part to be evaluated. For this evaluation, such excellence criteria are offered that were originally created for supporting corporate activities. The secret part of the model is tokenized by Ethereum-based NFTs (Non-Fungible Tokens). These tokens will provide for copyright issues.
【Abstract】Information related to Covid-19 either it is vaccination status of the country or the active Covid-19 cases both are the confidentialmatters. The privacy is utmost important concern in pandemic situation to secure access of patient vaccine data. Blockchain technique is one of the good techniques that affirm the privacy and data security. The consensus mechanisms in blockchain confirm that data stored in it, is authentic and secured. Proof of Work is one of the consensus algorithms, where miners in the blockchain network solves the puzzle and receive the reward accordingly. The difficulty level of the puzzle decides the security of the data in the network. Hence, this paper proposes blockchain based framework to store the vaccination data of patient by enhancing security using proof of work consensus algorithm. The performance of the proposed framework is measured on different level of difficulties, corresponding to time. The result shows that higher the difficulty level, take more time to solve the puzzle, results in more secure data.
【Abstract】Blockchain Technology is preferred in various applications for its decentralization, integrity and availability features. Much research is going on for blockchain technology's efficient design and utilization. Also, the application of blockchain in the IoT environment is a new area of focus. However, researchers have problems testing various blockchain features on IoT devices. Hence, we developed the Blockchain Platform as a Service (BlockPaaS), which allows users to run various blockchain protocols on the IoT hardware instantly.
【Abstract】With the increasingly stringent regulatory requirements for data security all around the world, advanced privacy preserving data protection strategies and corresponding secure computation protocols are in urgent needs. The traditional methods for original data transaction and processing may conflict with the data regulation and laws. Thus, the object of data transaction nowadays is no longer the original data, but the encapsulated data services, which seal and combine various computing models and protocols that operate on local data. This paper concludes the cryptography based secure computation protocols including proxy re-encryption (PRE), multiparty computation (MPC), and zero-knowledge proof protocol (ZK), then organizes these protocols into smart contract-based layers on blockchain to support verifiable credentials and presentations, authorization-based data re-encryption, and MPC-based data secure computation as well as aggregations with ZK property.
【Abstract】In recent years, blockchain technology in synergy with smart contracts has opened new horizons within almost any field from entertainment to healthcare. However, in order to enable innovative usage scenarios, significant efforts are needed to adapt the existing systems and solutions, so the full potential of blockchain-based tools can be leveraged. In this paper, we propose a model-driven framework which provides automated persistence of domain-specific data within Ethereum blockchain platform, starting from Ecore model instances. Moreover, the corresponding Solidity smart contracts are generated relying on model-to-model and model-to-text transformations using Acceleo. The proposed approach is evaluated on persons-movies dataset inside the Ganache environment. According to the obtained results, our solution successfully automatized the persistence of the evaluated dataset.
【Abstract】Over the past few years, Ethereum has surfaced as a widely adopted standard Blockchain platform that is increasingly being utilized to develop Decentralized Applications (DApps). By introducing Smart Contracts to software developers and programmers, Ethereum has triggered the development of countless Blockchain solutions. Among its main applications, many involve the exchange of valuable financial assets. Simply put, we cannot afford to base our Blockchain solutions or applications on potentially vulnerable smart contracts. This is where the Security Analysis Tools come into picture, for the timely detection of vulnerabilities in the Smart Contracts. Since this is a recent phenomenon, it offers a lot of research opportunities for us to contribute towards improving the existing state of security analysis tools and resolving their shortcomings. Although most of these tools have been evaluated in terms of effectiveness, installation and reliability; the literature largely lacks the technical usability perspective i.e. execution and evaluation. Therefore, based on a selection criteria, we committed our time to 4 such tools for an extensive usability assessment. We designed our usability study in a manner that combined the advantages of multiple evaluation methods. The results were useful not only in terms of comparative analysis, but also as a validation of the need of identified usability improvements.
【Abstract】This paper proposes a protocol for Proof of Assets of a bitcoin exchange using the Zero-Knowledge Succinct Non-Interactive Argument of Knowledge (ZK-SNARK) without revealing either the bitcoin addresses of the exchange or balances associated with those addresses. The proof of assets is a mechanism to prove the total value of bitcoins the exchange has the authority to spend using its private keys. We construct a privacy-preserving ZK-SNARK proof system to prove the knowledge of the private keys corresponding to the bitcoin assets of an exchange. The ZK-SNARK toolchain helps to convert an NP-Statement for proving the knowledge of the private keys (known to the exchange) into a circuit satisfiability problem. In this protocol, the exchange creates a Pedersen commitment to the value of bitcoins associated with each address without revealing the balance. The simulation results show that the proof generation time, size, and verification time are efficient in practice.
【Abstract】With the wide application of the Raft consensus algorithm in blockchain systems, its safety has attracted more and more attention. However, although some researchers have formally verified the safety of the Raft consensus algorithm in most scenarios, there are still some safety problems with Raft consensus algorithm in some special scenarios, and cause problems now and then. For example, as a core part of the Raft consensus algorithm, the Raft leader election algorithm usually faces some safety problems in following scenarios: if the network communication between some nodes is abnormal, the leader node could be unstable or even cannot be elected, or the log entry cannot be updated, etc. In this paper, we model check the safety of the Raft leader election algorithm throughly using Spin. We use Promela language to model the Raft leader election algorithm and use Linear-time Temporal Logic (LTL) formulae to characterize three safety properties including stability, liveness, and uniqueness. The verification results show that the Raft leader election algorithm does not hold stability and liveness when some nodes are faulty and node log entries are inconsistent. For these safety problems, we give the suggestions for improving safety by analyzing counter examples.
【Abstract】Software defined networking (SDN) have the advantages of centralized control, global visibility, and programmability, but these features also bring new security issues, such as Topological Poisoning Attack (TPA), where attackers can attack topology discovery services by stealing host locations or forging link information. Considering the three levels of identity, data package and path, this paper designs a chain authentication defense scheme. The scheme includes authentication mechanism, transaction information storage mechanism, source IP authentication mechanism and smart contract notification mechanism. The received packets are authenticated by digital signature algorithm, and the trusted identity and location information are stored securely. At the same time, an improved block storage structure is designed to avoid data redundancy, and malicious information is processed by smart contract notification and stream rule installation. The experimental results show that the defense scheme designed in this paper can effectively defend against TPA attacks. Compared with the benchmark mechanism, the deployment of this scheme has less impact on controller performance and less impact on the delay of topology discovery in SDN.
【Abstract】This paper proposes a data sharing system among multiple networked robots. The system considers the value and the ownership of shared data in the robot networks based on Ethereum blockchain platform. In this system, the owner robot of important data such as grid maps can receive any rewards from the robots which use the shared data. This study aims to achieve robotic ecosystem including data generation, data sharing and reward compensation to the owners. Since this system is intended to be applied to a large number of robots, the simulation is conducted with multiple robots on Unity and Ethereum private chain. In order to approximate the system configuration in the real world, each robot in the simulator is assumed to be controlled by an independent computer system. Then, a Docker container was built for each robot to control the robots based on ROS platform and connect to the blockchain network and Unity. This paper introduces the whole system configuration integrating the robot network Docker containers, ROS system for navigation tasks, data sharing based on Ethereum and the Unity simulator. In the first simulation, the navigation system of multiple robots was executed. Grid map data of unknown areas is shared in this simulation. The results showed that data sharing and transactions among private Ethereum network participants were achieved as designed.
【Abstract】Auctions are particularly favored as a means of financial transaction for high-value commodities. The Turing-complete script provided by the Ethereum platform facilitates different types of auctions. However, the transparency of Ethereum may lead to threats to the privacy of financial transactions, which is also the biggest obstacle to the practical application of blockchain. This paper proposes an auction contract privacy protection method named TrustAuction, which protects the transaction data privacy and user identity privacy in the auction process through the Trusted Execution Environment(TEE). Specifically, TEE is used to generate new identities for users in the auction process, and the bids submitted by users using the new identities exist are encrypted outside the TEE.
【摘要】[目的/意义]区块链技术被纳入“新基建”范畴后,其产业发展演进快、舆情热度高。本研究将情感因素纳入新兴产业网络舆情热度预测,探究区块链产业关注主题及发展态势。[方法/过程]论文融合情感分析与多元时间序列特征提出舆情热度预测模型,采用BERT-BiLSTM(Bi-directional Long Short-Term Memory, BiLSTM)方法对舆情文本分类并赋值,挖掘情感极性类别的主题,将不同情感倾向的情感值分别取绝对值累加,构建基于情感因素的多元时间序列特征体系,并输入LSTM(Long Short Term Memory, LSTM)模型进行区块链产业舆情热度预测。[结果/结论]BERT-BiLSTM在情感分类任务中准确率为84%,其中消极和中性情感类属文本的成因主要为“对于区块链技术的不信任”和“缺乏区块链相关概念的了解”。在热度预测模型中,模型均方根误差(Root Mean Square Error,RMSE)降低17.67,平均绝对误差(Mean Absolute Error, MAE)降低15.14,决定系数(R-Square,R2)提升11%,模型总体性能良好。