【Abstract】Since Manufacturing 4.0 faces various challenges, including the risks of data leakage and privacy violation, the struggle to meet the growing demand for personalization, and the limitations in harnessing human creativity, it has become crucial to embark on a transformation toward Manufacturing 5.0. To this end, we propose a DeFACT framework for parallel manufacturing and Manufacturing 5.0, which focuses on safe, efficient and personalized collaborative production. In DeFACT, different enterprises and parallel workers (i.e., digital, robotic and biological workers) are organized, coordinated and scheduled based on decentralized autonomous organizations and operations to promote mutual benefits among members, even in the context of low or zero trust. This contributes to providing customers with higher-quality personalized products and services while ensuring the confidentiality and safeguarding of data. Additionally, various advanced technologies, such as generative artificial intelligence, scenarios engineering, and blockchain, are leveraged to achieve trustworthy and adaptable decision making, user-friendly human-machine interaction, and the federated control and management of parallel workers. Finally, the effectiveness and efficiency of DeFACT are experimentally validated through the design and implementation of three case studies.
【Abstract】In the face of escalating environmental concerns, an expanding consumer base actively seeks authentic and transparent information traceability to reinforce their dedication to sustainable practices. This research aims to examine the impact of consumer preferences for product traceability, environmental sustainability, and brand on the optimal decisions and pricing strategies of firms within heterogeneous smart sustainable supply chains (SSCs). Employing both centralized and decentralized scenarios, the study develops differentiated triopoly models in which the participating players are categorized as boundedly rational, naive, and adaptive. Utilizing a differential game approach, the research analyzes the optimal decisions of entities and the performance of products under various scenarios. Subsequently, a Bertrand triopoly game is employed to scrutinize the pricing strategies of differentiated SSCs. The findings underscore the substantial influence of consumer sustainability and traceability preferences on information transparency for sustainable products, impacting both manufacturers and suppliers, while brand reputation positively shapes decision -making. The study reveals intricate effects of these preferences on the adjustment speed of boundedly rational supply chains, directly influencing market stability.
【Abstract】In the complex and dynamic nature of financial markets where increasingly sophisticated investment strategies are required, deep reinforcement learning (DRL) has proven successful in generating real -time investment strategies, outperforming classical models. Alongside this, statistical arbitrage strategies exploit temporary market inefficiencies to generate returns. In this regard, a novel DRL-based arbitrage method has been developed. This paper presents a unified framework that combines classical statistical arbitrage theory with DRL framework to generate investment strategies. The framework addresses the challenges of identifying similar asset portfolios, extracting signals indicating temporary price deviations, and determining optimal trading rules given market conditions. The proposed methodology involves constructing arbitrage portfolios based on cointegration relationships, removing signals from price series and portfolios, and using a DRL agent to make optimal decisions within a fixed time horizon. The empirical analysis focuses on the cryptocurrency market, known for its volatility and risk. Results demonstrate that DRL agents can generate strategies with positive returns in out-of-sample periods 79.52% to 112.82% with no transaction cost, outperforming market benchmark Bitcoin 32.51% return, the best performing over the period Litecoin with 57.11% return and the worst performing Solana with a 35.70% loss. Moreover, these strategies effectively reduce risk, achieving higher risk-adjusted returns on individual assets. The strategies maintain positive returns when considering transaction costs, with the DRL agent outperforming the standard arbitrage strategy. The best-performing strategy is based on a Deep Q-Network (DQN) agent with a return of 18.39%, annualized volatility of 12.22%, and an annualized Sharpe ratio of 2.43. At the same time, Bitcoin holds an annualized volatility of 44.13% and a Sharpe ratio of 1.08. Their randomness and coherence are studied to verify the robustness of the agents' decisions. The actions generated by the agents are not random but based on well-founded policies, which align with the obtained results.
【Abstract】This study explores the perceptions of tourists regarding the use of artificial intelligence (AI) devices in the hotel industry. Adopting the artificially intelligent device use acceptance (AIDUA) framework, this research uncovered the factors that influence tourists' attitudes towards AI devices and their willingness/unwillingness to use them. This study also demonstrated the moderating impact of Industry 4.0. The strong associations among social influence, hedonic motivation, anthropomorphism, performance expectancy, effort expectancy, users' emotions towards AI device usage, and their willingness/unwillingness to accept AI devices are explored. Furthermore, Industry 4.0 was of utmost importance in strengthening the relations among research constructs.
【Abstract】Around 196 countries committed to become part of United Nation's Framework Convention on Climate Change (UNFCC) through Paris Agreement and pledged to achieve carbon neutrality goals by 2050. The organizations have recognised the importance of digital technologies for achieving sustainable goals. To accelerate the transition to low-carbon energy systems, to best of author's knowledge, this is the first attempt which addresses issues of BCT for decarbonization in logistics sector in developing economy using theories like TOE (technological, organizational and environmental) and IRT (Innovation resistance theory). A comprehensive literature review was undertaken using PRISMA to recognise the barriers linked to the blockchain technology adoption for reducing carbon emissions. To prioritize these barriers, inputs from ten experts belonging to different industry verticals and academics were taken. Ordinal Priority approach (OPA) is used to prioritise them. Further, the cause-and-effect relationship among the listed barriers is established using Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique. A real-life case illustration on Indian logistics company has been considered and the barrier intensity index is computed using Graph Theory Matrix approach (GTMA) for the case company. The results suggest that 'Organizational Barriers' are the most crucial category of barriers followed by 'Environmental Barriers'. The results also show that the organizational barriers and environmental barriers belong to the cause group whereas technical and risk barriers are the part of the effect group. Based on the findings of GTMA, it has been observed that the overall barrier intensity index for the case company lies close to the centre of the worst and best theoretical values. The intensity index value will help case company to position themselves properly to formulate new strategies for secured and carbon neutral operations. Researchers and supply chain practitioners can devise new strategies and policies for achieving net zero goals by understanding the interplay between blockchain technology, organizational policies, and environmental outcomes. This research work can contribute to provide distinct perspective to look upon the BCT adoption issues in developing countries and can assist logistics industry stakeholders to plan and design new integrated BCT systems with carbon reduction initiatives.
【Abstract】Small and medium enterprises (SMEs) contribute to strengthening the global market by creating new jobs. Interactions among these companies may indeed be facilitated via e-commerce platforms. However, e-commerce activities seem to be a virtual face-to-face transactions, highly digital, and mutable. E-commerce based SMEs are frequently exposed to virtuous risks and competitive intensity. Blockchain is a digital database with the features of truthfulness, assurance, accountability, and intractability. It is made up of decentralized data storage, a consensus algorithm, and smart contracts. As a result, integrating e-commerce platforms and blockchain networks to help SMEs overcome their security difficulties. Conventional e-commerce platforms and storage depends on authorized intermediary networks or distributed cloud storage. Still, the failure of a single device is a danger, and third parties access, and data storage systems might be subject to data theft attacks. This paper presents a proof-of-authority (PoA) based consensus mechanism for e-commerce platforms in SMEs to address security issues in the network. This manuscript initially developed an energy-efficient PoA based consensus mechanism supported by e-commerce platforms for SMEs. We construct a comprehensive PoA consensus model based on pseudorandom number generator (PRNG) and accumulated validators number (AVN) for adding a new block in the conceptual framework. Finally, we demonstrate the security performance of the proposed consensus mechanism to help SMEs solve finance and trading issues. To evaluate the energy performance of the proposed model, we did a CPU utilization analysis and compared it with existing consensus protocols.
【Abstract】Currently, data security and privacy protection are becoming more and more important. Access control is a method of authorization for users through predefined policies. Token-based access control (TBAC) enhances the manageability of authorization through the token. However, traditional access control policies lack the ability to dynamically adjust based on user access behavior. Incorporating user reputation evaluation into access control can provide valuable feedback to enhance system security and flexibility. As a result, this paper proposes a blockchain-empowered TBAC system and introduces a user reputation evaluation module to provide feedback on access control. The TBAC system divides the access control process into three stages: policy upload, token request, and resource request. The user reputation evaluation module evaluates the user's token reputation and resource reputation for the token request and resource request stages of the TBAC system. The proposed system is implemented using the Hyperledger Fabric blockchain. The TBAC system is evaluated to prove that it has high processing performance. The user reputation evaluation model is proved to be more conservative and sensitive by comparative study with other methods. In addition, the security analysis shows that the TBAC system has a certain anti-attack ability and can maintain stable operation under the Distributed Denial of Service (DDoS) attack environment.
【Abstract】With the rising adoption of blockchain technology due to its decentralized, secure, and transparent features, ensuring its resilience against network threats, especially Distributed Denial of Service (DDoS) attacks, is crucial. This research addresses the vulnerability of blockchain systems to DDoS assaults, which undermine their core decentralized characteristics, posing threats to their security and reliability. We have devised a novel adaptive integration technique for the detection and identification of varied DDoS attacks. To ensure the robustness and validity of our approach, a dataset amalgamating multiple DDoS attacks was derived from the CIC-DDoS2019 dataset. Using this, our methodology was applied to detect DDoS threats and further classify them into seven unique attack subcategories. To cope with the broad spectrum of DDoS attack variations, a holistic framework has been pro posed that seamlessly integrates five machine learning models: Gate Recurrent Unit (GRU), Convolutional Neural Networks (CNN), Long-Short Term Memory (LSTM), Deep Neural Networks (DNN), and Support Vector Machine (SVM). The innovative aspect of our framework is the introduction of a dynamic weight adjustment mechanism, enhancing the system's adaptability. Experimental results substantiate the superiority of our ensemble method in comparison to singular models across various evaluation metrics. The framework displayed remarkable accuracy, with rates reaching 99.71% for detection and 87.62% for classification tasks. By developing a comprehensive and adaptive methodology, this study paves the way for strengthening the defense mechanisms of blockchain systems against DDoS attacks. The ensemble approach, combined with the dynamic weight adjustment, offers promise in ensuring blockchain's enduring security and trustworthiness
【Abstract】Over the last few decades, technology has been improving dramatically and consequently transformed the standard of living and socio-economic conditions. The entire process will revolutionize when the next advanced technologies will be fully functional. Advanced technologies like the metaverse, Web 3.0, and others necessitate high computing power, invincible security, and ultra-fast internet. Despite increasing demand, traditional computing methods have limitations and are not capable of satisfying the requirements. To solve these tribulations, quantum computing is shining a light of hope. This survey aims to analyze the methodology, constraints, and potential of integrating quantum computing with the metaverse. We begin with an overview of quantum computing and related terms. We then investigate the feasibility of applying quantum-enabled technologies to enhance the metaverse. Furthermore, this survey also considers middleware for seamless conversion between traditional and quantum computing with the metaverse. In the subsequent phase of this survey, our objective is to discern and delineate the prospective application domains for the quantum-enabled metaverse. In essence, the difficulties of integrating quantum computing with the metaverse, present research approaches, and open research issues with consequences for additional in-depth investigations are highlighted.
【Abstract】Distributed energy generation disrupts traditional energy markets by blurring the line between producers and consumers and enabling the emerging prosumers to trade energy in per-to-peer transactions. Blockchain technology automates peer-to-peer energy trades in a distributed database architecture that achieves security and cost-effectiveness using cryptographic hashing and consensus-based verification. Before its deployment, an energy blockchain trading application needs to be tested in a virtual environment that is analogous to the real-world setting to ensure correct implementation and identify potential obstacles and opportunities. This study suggests executing such a testing within a framework that integrates a Geographic Information System (GIS) environment with an Agent-Based Modeling (ABM) simulation platform. The application of this testing framework to a case study of solar Photovoltaic (PV) energy trade among household peers in in Doha, Qatar, shows how the integration of the GIS environment offers a detailed analysis of transactions in local housing community markets. The ABM simulation reveals that population density, energy market prices, and household proximity significantly influence residential PV energy trading in Qatar. The ensuing simulation environment provides a decision-support platform for designing and implementing decentralized trading systems based on blockchain technology, and high-performance computing can enhance model performance for scalable energy blockchain analysis in Qatar and beyond.
【Keywords】Spatial temporal access; social simulation; power grid; artificial intelligence; solar energy; blockchain technology; agent based modelling; energy marketplace
【Abstract】Blockchain makes heavy use of cryptographic hashing to achieve integrity and consensus in a peer-to-peer network, but hashing causes some inefficiencies. For example, blockchain stores data with their hash digest as a key in the database, so the blockchain always reads and writes data in a random order. This can affect blockchain performance, especially for account-based blockchains such as Ethereum, which must maintain a huge, hash-based data structure for accounts, called the state trie. Also, Proof-of-Work (PoW) consensus algorithm requires the miners to find a nonce that makes the block hash lower than a difficulty threshold, but ASICs with parallel hashing have made PoW use a large dataset such as the Ethash DAG for memory-hardness and ASIC-resistance. Unfortunately, verification of the nonce is not easy for many light clients, which cannot deal with the overhead caused by the dataset. This paper proposes a novel PoW mining algorithm named Trie-Hashimoto to address these issues. Trie-Hashimoto adds a nonce field in a state trie node. It then makes the miners find a nonce of every newly-created trie node for a new block such that each node has a hash digest whose prefix is equal to the block number. This can accelerate the database performance by storing the trie nodes in a sequential order. The way for Trie-Hashimoto to achieve memory-hardness is also different. It uses the block headers that any client must maintain, obviating a separate dataset. Furthermore, it allows partial verification using a few Merkle proofs of accounts, so that a client with minimal resources or even a smart contract in another interoperable blockchain can verify a block with a high probability. Finally, Trie-Hashimoto discourages big mining pools by increasing the network overhead among the miners. Our experiment on the Geth client with 500K blocks and 100M accounts shows that Trie-Hashimoto improves the transaction execution time tangibly, reducing the full synchronization time by half. It also shows that Trie-Hashimoto has enough memory-hardness as Ethash. Lastly, a Trie-Hashimoto mining pool should exchange messages highly frequently, proportional to the total number of miners.
【Abstract】This paper presents MindTheDApp, a toolchain designed specifically for the structural analysis of Ethereum-based Decentralized Applications (DApps), with a distinct focus on a complex network-driven approach. Unlike existing tools, our toolchain combines the power of ANTLR4 and Abstract Syntax Tree (AST) traversal techniques to transform the architecture and interactions within smart contracts into a specialized bipartite graph. This enables advanced network analytics to highlight operational efficiencies within the DApp's architecture. The bipartite graph generated by the proposed tool comprises two sets of nodes: one representing smart contracts, interfaces, and libraries, and the other including functions, events, and modifiers. Edges in the graph connect functions to smart contracts they interact with, offering a granular view of interdependencies and execution flow within the DApp. This network-centric approach allows researchers and practitioners to apply complex network theory in understanding the robustness, adaptability, and intricacies of decentralized systems. Our work contributes to the enhancement of security in smart contracts by allowing the visualisation of the network, and it provides a deep understanding of the architecture and operational logic within DApps. Given the growing importance of smart contracts in the blockchain ecosystem and the emerging application of complex network theory in technology, our toolchain offers a timely contribution to both academic research and practical applications in the field of blockchain technology.
【Abstract】This paper investigates the connectedness among eighteen cryptocurrency assets including NFT, DeFi, gold -backed cryptocurrencies, and traditional cryptocurrencies. We also compute the Optimal hedge ratio for each pair of (gold -backed) cryptocurrency-NFT/DeFi and assess their hedge effectiveness. To this end, we use a combination of econometric methods. Our sample period goes from 01/11/2021 to 21/02/2023, making the empirical analysis insightful and interesting as it includes the Covid-19 health crisis and the Russia-Ukraine war. Our empirical findings highlight the dissimilarities between different cryptocurrencies in terms of connectedness with NFT/DeFi assets. They also reflect the diversification benefits generated by the inclusion of gold -backed cryptocurrencies into NFT/DeFi portfolios, in particular in times of unprecedented events. These findings could be useful for crypto-investors who search to diversify their portfolios.
【Abstract】As a critical raw material for the textile industry, cotton lint provides various types of cotton yarns, fabrics and finished products. However, due to the complexity of the supply chain and its many links, information records are often missing, inaccurate or lagging, resulting in low transparency and traceability. In the traditional cotton lint supply chain, the data of each link are stored in isolation; due to the lack of an effective sharing mechanism and the formation of "information silos", complete traceability is challenging to achieve. In addition, the completeness and authenticity of documents such as lint quality reports and certificates of origin must be rapidly strengthened. Otherwise, quality problems may arise. To solve the above problems, this study proposes a cotton lint supply chain traceability system based on blockchain and non-fungible tokens (NFTs), covering the whole cotton lint production process from harvesting to selling. We use an NFT as an asset token to digitise seed cotton, cotton lint and quality inspection reports and allow participants to store and manage these assets on the blockchain. The system design includes architecture diagrams, sequence diagrams and Ethernet smart contract development based on the ERC721 standard. In addition, the integration of Interplanetary File System (IPFS) technology solves the problem of storing large files on the chain and ensures that the data are permanently preserved and cannot be tampered with. We provide a diagram of the interactions between the system components and the four core algorithms' design, testing and verification process. We present an in-depth analysis of the solution regarding the transaction costs and smart contract security. We confirm the solution's security, reliability and applicability through a cost evaluation and security analysis.
【Abstract】The rapid development of blockchain transactions highlights the importance of privacy protection (including anonymity and confidentiality) and underscores the necessity for auditability. Some schemes, such as PGC and Miniledger, support privacy protection and auditability. However, they only offer incomplete privacy protection (i.e., supporting anonymity or confidentiality exclusively). In response to these issues, we propose a scheme that achieves partial anonymity, confidentiality, auditability, and traceability. By integrating a variant of Pedersen commitments and randomizable signatures, we achieve partial anonymity for users and the auditability of transactions, thereby protecting user privacy under audit conditions. Based on the twisted ElGamal encryption algorithm and specially constructed zero-knowledge proofs, we achieve confidentiality of transaction amounts under legal and regulatory conditions. System test results indicate that this scheme effectively meets the above requirements. The feasibility of this scheme is confirmed through system testing, comparative analysis, and security analysis.
【Abstract】Since the emergence of blockchain, how to improve its transaction throughput and reduce transaction latency has always been an important issue. Hostuff has introduced a pipeline mechanism and combined it with a chain structure to improve the performance of blockchain networks. HCA has introduced a revoting mechanism on the basis of Hostuff, further reducing transaction latency, but it has also brought some problems. In HCA, if the leader is malicious, it would be possible to continuously call on the replica nodes to revote, which can lead to network congestion. This paper employs the global perfect coin technology to guarantee that every replica can obtain a globally consistent and the freshest candidate proposal during the Revote phase, thereby improving the robustness of the HCA protocol. The performance improvement of RHCA in attack scenarios has been verified through experiments.
【Abstract】In order to make the image copyright protection system can resist network attacks, and to solve the problems of unknown copyright owner, difficulty in data integrity verification and unauthorized redistribution, a digital image copyright protection method based on blockchain and zero trust mechanism was proposed. Firstly, after the copyright owner signs with the elliptic curve digital signature algorithm (ECDSA), the signature and copyright information are encrypted with the elliptic curve cryptography (ECC) algorithm, and the ciphertext and the generated image hashing are uploaded to the blockchain; Then, the smart contract is called to authenticate the copyright owner, the similarity of the hash value is used to detect the infringement of the verified image, the MD5 key generated by the image hashing value is used to encrypt the detected image, the ciphertext and encrypted image are uploaded to the interplanetary file system (IPFS), and the corresponding storage address is returned to the blockchain. Consumers can download ciphertext and encrypted images in IPFS as needed after completing asset evaluation and paying when calling the dual-smart contract to initiate copyright transaction. Experimental results show that the proposed method can not only authenticate the identity, but also realize double encryption of the image and copyright information. It can prevent the unauthorized use and redistribution of digital content, and improve the overall security of the image copyright protection system.
【Abstract】In addition to providing mobility, plug-in hybrid electric vehicles (PHEVs) provide a two-sided energy exchange opportunity which makes them highly flexible distributed energy storage systems for the future of energy systems. This paper analyzes PHEVs' performance from the perspective of urban traffic and energy using a decentralized multichannel blockchain network based on the hyperledger model. This network using a layered design and local management of energy sources can significantly contribute to urban management and optimal use of its infrastructures. Then, dynamic modelling of PHEVs in this network is performed, and their data is added to the network to evaluate the network performance compared with the current centralized networks. The results indicated that the proposed blockchain network could simultaneously optimize PHEVs' performance, urban traffic management, and energy systems. Furthermore, by utilizing smart contracts, it can consider and optimize multiple challenges, such as congestion in the electricity network, urban traffic, and limited fuel, simultaneously. Therefore, it gives a strong tool to study the impact of mass deployment of PHEVs and their value and role in the sustainable cities and communities of the future while helping to support the global efforts toward affordable and clean energy for all. This study presents a decentralized multichannel blockchain network based on the hyperledger model to improve vehicle performance, as well as illustrate the interaction and impressibility of the three fields using smart tools provided by the network. image
【Abstract】PurposeBlockchain technology has brought about significant transformation among organizations worldwide. This study aimed to explore the effects of organizational and technological factors on blockchain technology adoption (BTA) and financial performance (FP) in Pakistan.Design/methodology/approachThis is a co-relational study which used the cross-sectional data. We gathered the data from the managers of Pakistan's small and medium-sized enterprises (SMEs), which functioned their industries with blockchain technology. We applied convenience sampling to identify the respondents. Finally, we based this study's findings on 274 valid cases.FindingsWe used structural equation modeling (SEM) in this study, to exert a positive and significant impact on organizational factors such as organizational innovativeness (OI), organizational learning capability (OLC), top management support (TMS) and organizational work climate (OWC) on BTA. In addition, the technological factors, such as complexity (CTY), technology readiness (TR), compatibility (CBTY) and technology capability (TC), have a positive and significant effect on BTA. Finally, this study's findings show that BTA positively and significantly impacts FP.Practical implicationsThis study's findings will help policymakers and planners to design policies to adopt other blockchain technologies to improve SMEs' operations. Moreover, this study's findings will inspire policymakers and planners to actively seek new ideas, knowledge and skills through acquiring new knowledge to assist with their IT-related decisions.Originality/valueThis study empirically confirms the role of organizational and technology factors toward BTA and FP among Pakistan's SME managers.
【Abstract】Blockchain technology, marked as a disruptive force across various sectors, including seaport logistics, faces challenges and obstacles that impede its effective adoption. We aim to empirically identify the significant barriers impeding blockchain adoption in the seaport industry and elucidate the interconnected relationships between these impediments. Utilizing the Fuzzy Decision Making Trial and Evaluation Laboratory Analysis (Fuzzy DEMATEL) technique, we quantify the cause-and-effect relationships between various barriers to blockchain adoption. Structured interviews involving 18 experts were conducted, collecting both qualitative interview data and quantitative data. The nature of ports and the maritime industry did not seem to be accurately reflected in the literature about blockchain adoption, presenting several new findings in this study. Four primary obstacles were identified: 1) Lack of management support and commitment. 2) Issues in supply chain collaboration, communication and coordination. 3) Resistance from and lack of involvement of external stakeholders. 4) The high cost. Furthermore, cost was reaffirmed as a significant factor influencing blockchain adoption. We enhance existing literature by revealing the interdependencies among identified barriers and offers insights for policymakers and industry practitioners. We aim to foster successful blockchain integration in the seaport industry, improving its sustainability performance. During this research, it has been acknowledged by the business sector that the effective employment of business process re engineering (BPR) and the strategic implementation of blockchain technology are crucial strategies to surmount the obstacles that have impeded the extensive integration of blockchain within port operations.
【Abstract】Is there a momentum effect in cryptocurrency anomalies? To answer this, we analyze data from over 3900 coins spanning the years 2014 to 2022 and replicate 34 anomalies in the cross-section of cryptocurrency returns. We document a discernible pattern in factor premia: past winners consistently outperform losers. The effect persists across subperiods, withstands various methodological approaches, and its magnitude parallels that of its stock market counterpart. However, the autocorrelation in factor returns is not widespread and primarily stems from size and volatility anomalies. Additionally, unlike in stocks, cryptocurrency factor momentum originates from price momentum, which subsequently transfers to the factor level.
【Abstract】With the growing adoption of cloud-based technologies, maintaining the privacy and security of cloud data has become a pressing issue. Privacy-preserving encryption schemes are a promising approach for achieving cloud data security, but they require careful design and implementation to be effective. The integrated approach to cloud data security that we suggest in this work uses CogniGate: the orchestrated permissions protocol, index trees, blockchain key management, and unique Opacus encryption. Opacus encryption is a novel homomorphic encryption scheme that enables computation on encrypted data, making it a powerful tool for cloud data security. CogniGate Protocol enables more flexibility and control over access to cloud data by allowing for fine-grained limitations on access depending on user parameters. Index trees provide an efficient data structure for storing and retrieving encrypted data, while blockchain key management ensures the secure and decentralized storage of encryption keys. Performance evaluation focuses on key aspects, including computation cost for the data owner, computation cost for data sharers, the average time cost of index construction, query consumption for data providers, and time cost in key generation. The results highlight that the integrated approach safeguards cloud data while preserving privacy, maintaining usability, and demonstrating high performance. In addition, we explore the role of differential privacy in our integrated approach, showing how it can be used to further enhance privacy protection without compromising performance. We also discuss the key management challenges associated with our approach and propose a novel blockchain-based key management system that leverages smart contracts and consensus mechanisms to ensure the secure and decentralized storage of encryption keys.
【Abstract】The rapid evolution of the IoT has paved the way for new opportunities in smart city domains, including e-health, smart homes, and precision agriculture. However, this proliferation of services demands effective SLAs between customers and service providers, especially for critical services. Difficulties arise in maintaining the integrity of such agreements, especially in vulnerable wireless environments. This study proposes a novel SLA management model that uses an SDN-Enabled WSN consisting of wireless nodes to interact with smart contracts in a straightforward manner. The proposed model ensures the persistence of network metrics and SLA provisions through smart contracts, eliminating the need for intermediaries to audit payment and compensation procedures. The reliability and verifiability of the data prevents doubts from the contracting parties. To meet the high-performance requirements of the blockchain in the proposed model, low-cost algorithms have been developed for implementing blockchain technology in wireless sensor networks with low-energy and low-capacity nodes. Furthermore, a cryptographic signature control code is generated by wireless nodes using the in-memory private key and the dynamic random key from the smart contract at runtime to prevent tampering with data transmitted over the network. This control code enables the verification of end-to-end data signatures. The efficient generation of dynamic keys at runtime is ensured by the flexible and high-performance infrastructure of the SDN architecture.
【Abstract】Peer-to-peer (P2P) technology has gained popularity as a way to enhance system performance. Nodes in a P2P network work to-gether by providing network resources to one another. In this study, we examine the use of P2P technology for video streaming and develop a dis-tributed incentive mechanism to prevent free-riding. Our proposed solu-tion combines WebTorrent and the Solana blockchain and can be accessed through a web browser. To incentivize uploads, some of the received video chunks are encrypted using AES. Smart contracts on the blockchain are used for third-party verification of uploads and for managing access to the video content. Experimental results on a test network showed that our sys-tem can encrypt and decrypt chunks in about 1/40th the time it takes using WebRTC, without affecting the quality of video streaming. Smart contracts were also found to quickly verify uploads in about 860 milliseconds. The paper also explores how to effectively reward virtual points for uploads.
