Aiming at the severe challenges of Intelligent Connected Vehicle (ICV) in the field of data security, this paper designs a four-layer ICV data security framework, which covers the whole process from data collection, processing, storage and sharing to privacy protection. In the security framework, three technical methods of blockchain, Zero-Knowledge Proof (ZKP) and Post-Quantum Cryptography (PQC) are integrated. Blockchain is used to provide distributed trust mechanism and tamper-resistant data storage. ZKP is used to protect data privacy and realize data verification without leaking sensitive information. PQC is used to enhance data encryption and authentication mechanism to resist quantum computing attacks. At the same time, the data sharing security strategy is formulated, including initialization and key generation, data transmission preparation, zero-knowledge proof generation and verification, data reception and verification, blockchain recording and consensus, access control and data usage, etc., to ensure the security and privacy protection of data during the sharing process. The simulation experiment data of delay time, throughput and privacy protection intensity in the simulation environment show that the scheme not only enhances data privacy protection and data integrity verification but also improves the system's ability to resist future quantum computing threats and provides a solid guarantee for the data security of intelligent connected vehicles.
The Internet of Behaviors (IoB) is an emerging concept that utilizes devices to collect human behavior and provide intelligent services. Although some research has focused on human behavior analysis and data collection within IoB, the associated security and privacy challenges remain insufficiently explored. This article analyzes the security and privacy risks at different stages of behavioral data generating, uploading, and use while also considering the dynamic characteristics of user activity areas. Then, we propose a blockchain-based distributed IoB data storage and sharing framework, which is categorized into sensing, processing, and management layers based on these stages. To accommodate both identity authentication and behavioral privacy, zero-knowledge proofs are used in the sensing layer to separate the correlation between behavior and identity, which is further extended to a distributed architecture for cross-domain authentication. In the processing layer, an improved consensus protocol is proposed to enhance the decision-making efficiency of distributed IoB by analyzing the geographical and computational capability of the servers. In the management layer, user permission differences and the privacy of access targets are considered. Different types of behavior are modeled as corresponding relationships between keys, and fine-grained secure access is achieved through function secret sharing. Simulation results demonstrate the effectiveness of the proposed framework in multi-scenario IoB, with average consensus and authentication times reduced by 74 percent and 56 percent, respectively.
Data sharing among robots will be an important issue in a future robotic society including many kinds of networked robots. This study proposes a model-sharing system for autonomous mobile robot networks. The model in this study means an action model trained by deep reinforcement learning for mobile robot navigation. The proposed system assumes that the mobile robots in the network can share useful and efficient models among robots. The proposed system uses the Ethereum blockchain as a platform to consider the value and ownership of action models. The owners of the models can receive payments from robots that use the shared models for autonomous navigation. The proposed system finally aims to build a future robotic economic system that includes data generation and accumulation, data sharing, and currency transactions among model owners and user robots. This paper introduces the autonomous navigation method of switching action models according to the navigation environment, the data-sharing system using the Ethereum blockchain, and the flow of autonomous navigation using the proposed system. Simulation results shows that the proposed system can achieve navigation of multiple mobile robots through model and currency transactions among Ethereum network participants.
The core of blockchain technology, as a decentralized distributed ledger technology, lies in how to reach consensus without a centralized institution. Consensus algorithm is the cornerstone of blockchain, which determines the security, performance and decentralization degree of blockchain. This paper starts from the basic concept of blockchain consensus algorithms, analyzes the working principle, advantages and disadvantages, and application scenarios of current mainstream consensus algorithms, and discusses the future development trend of consensus algorithms.
Open access
Blockchain Technology Applications and Security
Cognitive Computing and Networks
Advanced Steganography and Watermarking Techniques
Imran Hussain, Hafiz Ashiq Hussain, Nasim Ullah, Stanislav Mišák
An evolving energy system with a dispersed infrastructure may not be compatible with traditional centralized optimization and management techniques. Blockchain, a peer-to-peer immutable distributed ledger technology, has the potential to significantly contribute to the management of emerging trends of decentralized power networks. However, complex optimization problems associated with the decentralized power grid are poorly integrated into the existing blockchain applications. Here, we suggest Proof of Inherent Intelligence (PoII), a novel prosumer-centric consensus mechanism designed to assist multi-interest party optimization challenges of the distributed power grid. We demonstrate PoII’s operation and performance with comprehensive mathematical modeling of energy pool-market trading and scheduling optimization problems. The efficiency of the proposed framework is evaluated against the existing blockchain applications for peer-to-peer energy transactions in terms of latency, throughput, tolerance against adversaries, vulnerability, and optimization capabilities. A thorough case study of the power grid that includes thermal, wind, and intermittent generation sources is presented to assess the effectiveness of the proposed consensus mechanism. Power demand, reserves, trading, and scheduling scenarios in both the day-ahead and balancing markets are among the peer-to-peer energy transactional elements that are assessed to support the efficacy of the suggested consensus approach.
This paper presents a novel approach to decentralized AI that utilizes blockchain technology to enhance data privacy. By combining federated learning with blockchain's immutable ledger, we create a secure framework that allows multiple parties to collaborate on AI model training without exposing sensitive data. Our findings show that this method not only preserves privacy but also improves model performance through diverse data contributions. This paradigm shift offers significant implications for industries requiring stringent data protection, such as healthcare and finance.
Teaching incentives are important in teaching and training. However, in traditional online teaching and training due to the characteristics of non-disclosure and non-transparency of information, students cannot be encouraged to learn well. In order to provide better incentives can be realized by awarding students with Non Fungible Token (NFT) for their achievements. However, traditional NFT methods do not take into account characteristics such as multi-user co-holding, lifetime holding and non-resale, and interaction based on means such as cryptocurrency wallets raises the threshold for users. In order to allow NFT technology to be better applied to the field of education and training, NFT technology is improved by proposing an NFT incentive mechanism based on the key escrow model, which simultaneously realizes the characteristics of multi-user and soulbounding, and designing a framework of teaching and training system based on NFT incentive. Finally, an experimental analysis is conducted under Ethereum blockchain to validate the rationality and effectiveness of the proposed NFT method, and to evaluate its computation and storage overhead to further prove its usability.
Bruno Ramos-Cruz, Javier Andreu-Pérez, Francisco J. Quesada, Luis Martı́nez
Blockchain technology has become a trusted method for establishing secure and transparent transactions through a distributed, encrypted network. The operation of blockchain is governed by consensus algorithms, among which Proof of Stake (PoS) is popular yet has its drawbacks, notably the potential for centralising power in nodes with larger stakes or higher rewards. Our proposed novel solution, Fuzzychain, leverages fuzzy sets to define stake semantics, introducing a degree of softness in validator selection. This approach mitigates rigid threshold-based decision-making by allowing gradual transitions between stake levels, reducing sharp disparities among validators. By incorporating this enhanced stake evaluation, Fuzzychain promotes a more adaptive and distributed selection process, ensuring a fairer and more inclusive blockchain network. A thorough assessment of a real-time multi-agent blockchain system to examine validator selection and reduce inequality, promoting a more equitable distribution of stakes among validators compared to other consensus mechanisms. This fosters a more inclusive selection process and a more equitably distributed network.
Many are wary of storing and processing data in the cloud because of the prevalence of hostile assaults on mobile and wireless communication networks, which raises serious privacy and security concerns. Using Blockchain as an example, this article investigates the feasibility of developing a trustworthy decentralized authentication system. Utilizing a blockchain technique to enhance the heftiness of multiple data checks and an optimized number of secured features from the bioacoustics signal, in place of traditional biometric features, ensure high security for the bioacoustics signal authentication mechanism. Verified authentication and monitoring of terminal activities are both made possible by it. Then, to provide security at every terminal and edge node, lightweight cryptography (LWC) is created. Lastly, the bastion of the catching approach is the belief-propagation(BP) strategy, which retrains the bioacoustics signal’s attributes. The hit ratio is improved and the delay time is decreased. With a blockchain paradigm for data openness, the investigational setup utilizes bioacoustics signals for authentication instead of standard biometric features, and the efficiency of numerous checks is improved. Both security and privacy are enhanced when this occurs. The association between MFCC and LPCC was 0.9517.
There have been several studies into measuring the level of decentralization in Ethereum through applying various indices to indicate the relative dominance of entities in different domains in the ecosystem. However, these indices do not capture any correlation between those different entities, that could potentially make them the subject of external coercion, or covert collusion. We propose an index that measures the relative dominance of entities based on the application of correlation factors. We posit that this approach produces a more nuanced and accurate index of decentralization.
The lack of authentication and ant forge mechanisms severely compromises the security details of the authorizations issuing the certification. We employ blockchain technology to verify people in a way that is akin to a digital signature with their identity and access authorization, so resolving the issue of certificate forgery. Blockchain technology is an open distributed ledger that ensures that every transaction cannot be altered and holds unquestionable information in a highly secure and encrypted manner. A high standard for the procedure that may guarantee that the data in such a certificate is authentic indicates that the document is authentic and has not been forged, having come from a reliable source. The interplanetary file system uses the content address as the only means of uniquely identifying every file inside a global namespace that includes all computing devices. A bi-dimensional barcode that provides data as black and white dots is called a Quick Response (QR) code. The system consists of black squares that can be photographed by a camera or other image device, arranged in a square framework on a white background.
HKUST Electronic Theses Novel reputation ranking system in Web3 and perpetual futures market models in DeFi by Do Van Thuat thesis 2024 1 online resource (xix, 168 pages) : illustrations (some color) This dissertation examines the evolution of the blockchain…Read more ›
To address the issues of malicious nodes being easily selected as consensus nodes and the problem of untimely processing of malicious nodes in the DPoS consensus algorithm, we propose a Trust-authorized Delegated Proof of Stake (Ta-DPoS) consensus algorithm based on reputation authorization. The Ta-DPoS consensus algorithm uses the PowerTrust model to conduct global reputation evaluation of nodes, enhances the authority and credibility of selected consensus nodes, balances the competition for bookkeeping rights while ensuring a fair selection process, and improves decentralization. At the same time, under a reputation reward and punishment mechanism based on dynamic games, malicious nodes are promptly excluded from the network edge, achieving constraints and incentives for blockchain node behavior. Experimental results show that to some extent, the Ta-DPoS consensus algorithm overcomes security issues that exist in node election and consensus processes and achieves relatively better performance in consensus efficiency, decentralization, and scalability.
Ovidiu Vermesan, Markus Eisenhauer, Martín Serrano, Patrick Guillemin · 12 authors
The Internet of Things (IoT) and the Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, which will bring together hyperconnectivity, edge computing, Distributed Ledger Technologies(DLTs) and Artificial Intelligence (AI). Future IoT applications will apply AI methods, such as machine learning (ML) and neural networks(NNs), to optimize the processing of information, as well as to integrate robotic devices, drones, autonomous vehicles, augmented and virtual reality(AR/VR), and digital assistants. These applications will engender new products, services and experiences that will offer many benefits to businesses, consumers and industries. A more human-centred perspective will allow us to maximise the effects of the next generation of IoT/IIoT technologies and applications as we move towards the integration of intelligent objects With social capabilities that need to address the interactions between autonomous systems and humans in a seamless way.
Blockchain is a distributed ledger technology that has recently gained widespread popularity. Many industries have started to implement blockchain solutions for their application and services. Blockchain provides immutability, privacy, security, and transparency. There is no central authority to validate and verify the transactions, still, every transaction in the Blockchain is considered secure and verified. This is made possible by the use of a consensus algorithm which is a core part of any Blockchain network. Different consensus algorithms exist and the selection of appropriate consensus algorithms can affect the performance of the blockchain. This paper presents a pattern for one of the most commonly used blockchain consensus algorithms, which is the Proof of Stake (PoS) algorithm. This pattern describes its architecture, including its structure and dynamics.
Information extraction and data mining are the important aspects in blockchain technology. Big- data mining tools can perform pattern recognition assignments from thousands to billions of blockchain communications to recognize evil users and fraudulent transactions. The current information extraction algorithms have the limitations of large memory occupation, long running time, high dimensionality, low extraction accuracy, poor convergence precision and slow convergence speed. There is a need to devise newer techniques with the potential of fast and accurate information extraction features in blockchain based systems to support high risk international financial transactions. Thus, in this paper, the automatic extraction algorithm of data mining as a case study of blockchain communications based on QACS (quantum adaption cuckoo search) method is proposed. Principal component analysis (PCA) is used to map the original features of blockchain communications into low-dimensional feature space through linear transformation, and then to replace the original features with fewer absolutely needed features. The features of coding information in information management system are reduced, and the optimal feature subset is obtained. K-means is used to extract the key information in the optimal feature subset. An improved and adaptive Cuckoo search is proposed in this paper where quantum operation is introduced into the original K-means algorithm for automatic extraction of coded information in blockchain communications. The results prove that the proposed QACS method has the potential of automatic extraction of the encoded information with lower execution time, higher extraction accuracy, and faster convergence speed, and is significant for blockchain based systems.
In this article we present the technological foundations on which an ecosystem of semantic data objects can be implemented on the latest Blockchain based systems. As the most important citizens among the semantic data objects are ontologies, the ecosystem is referred to as Ontospace. The foundations can be characterized by their architectural, cryptographic and transactional aspects. The architectural aspect borrows from the latest Layer-2 protocols of the 3rd generation blockchains and from the rules of Linked Data systems creation. The cryptographic aspect represents an original work that attempts to resolve the issue of efficient hashing of the graph data structures. The transactional aspect is concerned with the graph replication consistency, conditions for the direct access to graph data from the blockchain smart-contracts and with linkage between sidechains bearing semantic objects and the main network. The large parts of the work were implemented in the context of the Ontochain project – a part of the Next Generation Internet EU Initiative.
The blockchain identity ecosystem offers the possibility of rejecting the outdated identity system and eliminate the intermediaries. Identity management, through blockchain, can allow individuals to take ownership of their identity by creating a global identity (ID) to serve multiple purposes. For user security and ledger consistency, asymmetric cryptography and distributed consensus algorithms can be implemented. Blockchain technology would be able to save costs and increase efficiency due to its key features such as decentralization, persistence, anonymity and auditability. In addition, the digital identity platform would save citizens' time in accessing or exchanging their personal data and records. Instead of being required to appear physically before the service provider, the user may be provided with a digital ID through his/her personal device, such as a smartphone, through which he/she can share his identity details with the service provider, using distributed ledger technology (DLT).