In this study,we examine the connectedness between the NASDAQ artificial intelligence index and sectoral cryptocurrency indices.Empirical analyses were conducted via the quantile‒quantile methodology and cross-multiqu...In this study,we examine the connectedness between the NASDAQ artificial intelligence index and sectoral cryptocurrency indices.Empirical analyses were conducted via the quantile‒quantile methodology and cross-multiquantilogram tests across 15 cryptocurrency sectors from June 1,2021,to May 28,2024.The results show that dynamic total spillovers primarily occur in extremely low and high quantiles,corresponding to the left and right tails of the return distributions.Net directional spillovers indicate the dominance of the AI sector over the cryptocurrency market,which intensifies during significant crashes or booms.The most substantial effect of AI is observed in the DeFi,NFT,and Smart Contracts sectors,highlighting the prominence of financial operation-based blockchain applications in their interaction with artificial intelligence.The cross-multiquantilogram results also suggest that developments in artificial intelligence dominate the cryptocurrency market and have high predictability in its price movements.On the basis of our findings,we recommend using the AI market as an early indicator for the cryptocurrency market and advise against combining these two asset groups in the same portfolio to maintain diversification benefits.展开更多
The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and ...The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.展开更多
Practical byzantine fault tolerance(PBFT)can reduce energy consumption and achieve high throughput compared with the traditional PoW algorithm,which is more suitable for a strongly consistent consortium blockchain.How...Practical byzantine fault tolerance(PBFT)can reduce energy consumption and achieve high throughput compared with the traditional PoW algorithm,which is more suitable for a strongly consistent consortium blockchain.However,due to the frequent communication among nodes,PBFT cannot realize scalability in large-scale networks.Existing PBFTbased algorithms still ignore performance and security.Therefore,we propose a secure and efficient practical byzantine fault tolerance based on double layers and multi copies(DM-PBFT).We design a reputation evaluation and node scheduling method for DMPBFT.And then we propose an adaptive node scheduling strategy based on the derived threshold values after analyzing the system communication complexity and security.Combining the above research,a node dynamic adjustment mechanism is proposed to freeze or adjust the node operation status according to the system environment.Simulation experiments show that the proposed mechanism can improve efficiency and increase the system’s throughput.展开更多
With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security ...As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.展开更多
The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from com...The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.展开更多
In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic q...In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.展开更多
The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)...The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)and artificial intelligence(AI)techniques,have become standard practice.The need for Federated Learning(FL)for ML model training in ORAN environments is heightened by the modularised structure of the ORAN architecture and the shortcomings of conventional ML techniques.However,the traditional plaintext model update sharing of FL in multi-BS contexts is susceptible to privacy violations such as deep-leakage gradient assaults and inference.Therefore,this research presents a novel blockchain-assisted improved cryptographic privacy-preserving federated learning(BICPPFL)model,with the help of ORAN,to safely carry out federated learning and protect privacy.This model improves on the conventional masking technique for sharing model parameters by adding new characteristics.These features include the choice of distributed aggregators,validation for final model aggregation,and individual validation for BSs.To manage the security and privacy of FL processes,a combined homomorphic proxy-reencryption(HPReE)and lattice-cryptographic method(HPReEL)has been used.The upgraded delegated proof of stake(Up-DPoS)consensus protocol,which will provide quick validation of model exchanges and protect against malicious attacks,is employed for effective consensus across blockchain nodes.Without sacrificing performance metrics,the BICPPFL model strengthens privacy and adds security layers while facilitating the transfer of sensitive data across several BSs.The framework is deployed on top of a Hyperledger Fabric blockchain to evaluate its effectiveness.The experimental findings prove the reliability and privacy-preserving capability of the BICPPFL model.展开更多
Blockchain technology is increasingly popular and has been widely applied in many industrial fields,due to its unique properties of decentralization,immutability,and traceability.Blockchain systems in different fields...Blockchain technology is increasingly popular and has been widely applied in many industrial fields,due to its unique properties of decentralization,immutability,and traceability.Blockchain systems in different fields vary,with different block structures,consensus mechanisms and access permission models.These differences make it hard for different blockchain systems to interoperate with each other,which isolates them.Cross-chain technologies have been developed to solve this isolation problem in order to improve the interoperability of blockchains.Although some surveys on cross-chain technologies can be found,they are unable to keep up with the latest research progress due to their extremely fast pace of development.Moreover,the literature misses general criteria to evaluate the quality of cross-chain technologies.In this paper,a comprehensive literature review of cross-chain technologies is conducted by employing a comprehensive set of evaluation criteria.The preliminaries on blockchain interoperability are first presented.Then,a set of evaluation criteria is proposed in terms of security,privacy,performance,and functionality.The latest cutting-edge works are reviewed based on the proposed taxonomy of cross-chain technologies and their performance is evaluated against our proposed criteria.Finally,some open issues and future directions of cross-chain research are pointed out.展开更多
Taxation,the primary source of fiscal revenue,has profound implications in guiding resource allocation,promoting economic growth,adjusting social wealth distribution,and enhancing cultural influence.The development of...Taxation,the primary source of fiscal revenue,has profound implications in guiding resource allocation,promoting economic growth,adjusting social wealth distribution,and enhancing cultural influence.The development of e-taxation provides a enhanced security for taxation,but it still faces the risk of inefficiency and tax data leakage.As a decentralized ledger,blockchain provides an effective solution for protecting tax data and avoiding tax-related errors and fraud.The introduction of blockchain into e-taxation protocols can ensure the public verification of taxes.However,balancing taxpayer identity privacy with regulation remains a challenge.In this paper,we propose a blockchain-based anonymous and regulatory e-taxation protocol.This protocol ensures the supervision and tracking of malicious taxpayers while maintaining honest taxpayer identity privacy,reduces the storage needs for public key certificates in the public key infrastructure,and enables selfcertification of taxpayers’public keys and addresses.We formalize the security model of unforgeability for transactions,anonymity for honest taxpayers,and traceability for malicious taxpayers.Security analysis shows that the proposed protocol satisfies unforgeability,anonymity,and traceability.The experimental results of time consumption show that the protocol is feasible in practical applications.展开更多
The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver ...The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver operational improvements, the heightened interconnectivity introduces significant cybersecurity challenges, particularly within military logistics, where mission-critical operations and life-safety concerns are paramount. This paper examines these unique cybersecurity requirements, focusing on advanced persistent threats, supply chain poisoning, and data breaches that could compromise sensitive operations. The study proposes a hybrid cybersecurity framework tailored to military logistics, integrating resilience, redundancy, and cross-jurisdictional security measures. Real-world applicability is validated through simulations, offering strategies for securing supply chains while balancing security, efficiency, and flexibility.展开更多
Within the framework of the 2030 Agenda and to achieve the Sustainable Development Goals(SDGs),science,technology and innovation play an even more central role.Building on this foundation,the primary objective of this...Within the framework of the 2030 Agenda and to achieve the Sustainable Development Goals(SDGs),science,technology and innovation play an even more central role.Building on this foundation,the primary objective of this paper is to explore the potential applications of blockchain in supporting the achievement of these sustainability goals.Starting from a review of the relevant literature on this topic,the main fields in which blockchain can contribute to sustainable development will be identified.The main blockchain applications will then be analyzed and categorized according to these SDGs.This research will then critically present the main blockchain-based projects that emerged in the first stage of the study and were implemented by the United Nations.The main objectives and benefits of each project will be analyzed.This is where the originality of this paper lies.To the best of the author’s knowledge,this is one of the first attempts to present a comprehensive overview of the United Nations’projects related to SDGs 1,2,5,7,9,13,and 16.This paper,which bridges the gap between innovation management and the sustainability field,will contribute to the increasingly current debate on sustainability issues and be beneficial to scholars,practitioners,and policymakers alike.展开更多
With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become ...With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.展开更多
With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the...With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the existing data sharing schemes have been difficult to meet the growing demand for data sharing,this paper aims at exploring a secure,efficient and privacy-protecting data sharing scheme under web3.0 applications.Specifically,this paper adopts interplanetary file system(IPFS)technology to realize the storage of large data files to solve the problem of blockchain storage capacity limitation,and utilizes ciphertext policy attribute-based encryption(CP-ABE)and proxy re-encryption(PRE)technology to realize secure multi-party sharing and finegrained access control of data.This paper provides the detailed algorithm design and implementation of data sharing phases and processes,and analyzes the algorithms from the perspectives of security,privacy protection,and performance.展开更多
Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signatu...Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signature,adaptor signature can bind the release of a complete digital signature with the exchange of a secret value.Existing constructions of adaptor signatures are mainly based on Schnorr or ECDSA signature algorithms,which suffer low signing efficiency and long signature length.In this paper,to address these issues,we propose a new construction of adaptor signature using randomized EdDSA,which has Schnorr-like structure with higher signing efficiency and shorter signature length.We prove the required security properties,including unforgeability,witness extractability and pre-signature adaptability,of the new adaptor signature scheme in the random oracle model.We conduct a comparative analysis with an ECDSA-based adaptor signature scheme to demonstrate the effectiveness and feasibility of our new proposal.展开更多
As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by...As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.展开更多
Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a...Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a bottleneck to the widespread adoption of UCAN in 6G.In this paper,we propose Overlap Shard,a blockchain framework based on a novel reputation voting(RV)scheme,to dynamically manage the APs in UCAN.AP nodes in UCAN are distributed across multiple shards based on the RV scheme.That is,nodes with good reputation(virtuous behavior)are likely to be selected in the overlap shard.The RV mechanism ensures the security of UCAN because most APs adopt virtuous behaviors.Furthermore,to improve the efficiency of the Overlap Shard,we reduce cross-shard transactions by introducing core nodes.Specifically,a few nodes are overlapped in different shards,which can directly process the transactions in two shards instead of crossshard transactions.This greatly increases the speed of transactions between shards and thus the throughput of the overlap shard.The experiments show that the throughput of the overlap shard is about 2.5 times that of the non-sharded blockchain.展开更多
The accelerated advancement of the Internet of Things(IoT)has generated substantial data,including sensitive and private information.Consequently,it is imperative to guarantee the security of data sharing.While facili...The accelerated advancement of the Internet of Things(IoT)has generated substantial data,including sensitive and private information.Consequently,it is imperative to guarantee the security of data sharing.While facilitating fine-grained access control,Ciphertext Policy Attribute-Based Encryption(CP-ABE)can effectively ensure the confidentiality of shared data.Nevertheless,the conventional centralized CP-ABE scheme is plagued by the issues of keymisuse,key escrow,and large computation,which will result in security risks.This paper suggests a lightweight IoT data security sharing scheme that integrates blockchain technology and CP-ABE to address the abovementioned issues.The integrity and traceability of shared data are guaranteed by the use of blockchain technology to store and verify access transactions.The encryption and decryption operations of the CP-ABE algorithm have been implemented using elliptic curve scalarmultiplication to accommodate lightweight IoT devices,as opposed to themore arithmetic bilinear pairing found in the traditional CP-ABE algorithm.Additionally,a portion of the computation is delegated to the edge nodes to alleviate the computational burden on users.A distributed key management method is proposed to address the issues of key escrow andmisuse.Thismethod employs the edge blockchain to facilitate the storage and distribution of attribute private keys.Meanwhile,data security sharing is enhanced by combining off-chain and on-chain ciphertext storage.The security and performance analysis indicates that the proposed scheme is more efficient and secure.展开更多
To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional...To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional blockchains limit their application in large-scale FL tasks,and the synchronous traditional FL will also reduce the training efficiency.To address these issues,in this paper,we propose a Directed Acyclic Graph(DAG)blockchain-enabled generalized Federated Dropout(FD)learning strategy,which could improve the efficiency of FL while ensuring the model generalization.Specifically,the DAG maintained by multiple edge servers will guarantee the security and traceability of the data,and the Reputation-based Tips Selection Algorithm(RTSA)is proposed to reduce the blockchain consensus delay.Second,the semi-asynchronous training among Intelligent Devices(IDs)is adopted to improve the training efficiency,and a reputation-based FD technology is proposed to prevent overfitting of the model.In addition,a Hybrid Optimal Resource Allocation(HORA)algorithm is introduced to minimize the network delay.Finally,simulation results demonstrate the effectiveness and superiority of the proposed algorithms.展开更多
As an effective strategy to address urban traffic congestion,traffic flow prediction has gained attention from Federated-Learning(FL)researchers due FL’s ability to preserving data privacy.However,existing methods fa...As an effective strategy to address urban traffic congestion,traffic flow prediction has gained attention from Federated-Learning(FL)researchers due FL’s ability to preserving data privacy.However,existing methods face challenges:some are too simplistic to capture complex traffic patterns effectively,and others are overly complex,leading to excessive communication overhead between cloud and edge devices.Moreover,the problem of single point failure limits their robustness and reliability in real-world applications.To tackle these challenges,this paper proposes a new method,CMBA-FL,a Communication-Mitigated and Blockchain-Assisted Federated Learning model.First,CMBA-FL improves the client model’s ability to capture temporal traffic patterns by employing the Encoder-Decoder framework for each edge device.Second,to reduce the communication overhead during federated learning,we introduce a verification method based on parameter update consistency,avoiding unnecessary parameter updates.Third,to mitigate the risk of a single point of failure,we integrate consensus mechanisms from blockchain technology.To validate the effectiveness of CMBA-FL,we assess its performance on two widely used traffic datasets.Our experimental results show that CMBA-FL reduces prediction error by 11.46%,significantly lowers communication overhead,and improves security.展开更多
文摘In this study,we examine the connectedness between the NASDAQ artificial intelligence index and sectoral cryptocurrency indices.Empirical analyses were conducted via the quantile‒quantile methodology and cross-multiquantilogram tests across 15 cryptocurrency sectors from June 1,2021,to May 28,2024.The results show that dynamic total spillovers primarily occur in extremely low and high quantiles,corresponding to the left and right tails of the return distributions.Net directional spillovers indicate the dominance of the AI sector over the cryptocurrency market,which intensifies during significant crashes or booms.The most substantial effect of AI is observed in the DeFi,NFT,and Smart Contracts sectors,highlighting the prominence of financial operation-based blockchain applications in their interaction with artificial intelligence.The cross-multiquantilogram results also suggest that developments in artificial intelligence dominate the cryptocurrency market and have high predictability in its price movements.On the basis of our findings,we recommend using the AI market as an early indicator for the cryptocurrency market and advise against combining these two asset groups in the same portfolio to maintain diversification benefits.
文摘The Internet of Things(IoT)has gained substantial attention in both academic research and real-world applications.The proliferation of interconnected devices across various domains promises to deliver intelligent and advanced services.However,this rapid expansion also heightens the vulnerability of the IoT ecosystem to security threats.Consequently,innovative solutions capable of effectively mitigating risks while accommodating the unique constraints of IoT environments are urgently needed.Recently,the convergence of Blockchain technology and IoT has introduced a decentralized and robust framework for securing data and interactions,commonly referred to as the Internet of Blockchained Things(IoBT).Extensive research efforts have been devoted to adapting Blockchain technology to meet the specific requirements of IoT deployments.Within this context,consensus algorithms play a critical role in assessing the feasibility of integrating Blockchain into IoT ecosystems.The adoption of efficient and lightweight consensus mechanisms for block validation has become increasingly essential.This paper presents a comprehensive examination of lightweight,constraint-aware consensus algorithms tailored for IoBT.The study categorizes these consensus mechanisms based on their core operations,the security of the block validation process,the incorporation of AI techniques,and the specific applications they are designed to support.
基金supported in part by Beijing Natural Science Foundation(L244010,251038)National Natural Science Foundation of China(92467203,62372050,62502041)+2 种基金CCF-Huawei Populus Grove Fund(TC202418)Fellowship of China National Postdoctoral Program for Innovative Talents(BX20240045)China Postdoctoral Science Foundation General Program(2025M773481).
文摘Practical byzantine fault tolerance(PBFT)can reduce energy consumption and achieve high throughput compared with the traditional PoW algorithm,which is more suitable for a strongly consistent consortium blockchain.However,due to the frequent communication among nodes,PBFT cannot realize scalability in large-scale networks.Existing PBFTbased algorithms still ignore performance and security.Therefore,we propose a secure and efficient practical byzantine fault tolerance based on double layers and multi copies(DM-PBFT).We design a reputation evaluation and node scheduling method for DMPBFT.And then we propose an adaptive node scheduling strategy based on the derived threshold values after analyzing the system communication complexity and security.Combining the above research,a node dynamic adjustment mechanism is proposed to freeze or adjust the node operation status according to the system environment.Simulation experiments show that the proposed mechanism can improve efficiency and increase the system’s throughput.
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
基金supported by the Key Project of Joint Fund of the National Natural Science Foundation of China“Research on Key Technologies and Demonstration Applications for Trusted and Secure Data Circulation and Trading”(U24A20241)the National Natural Science Foundation of China“Research on Trusted Theories and Key Technologies of Data Security Trading Based on Blockchain”(62202118)+4 种基金the Major Scientific and Technological Special Project of Guizhou Province([2024]014)Scientific and Technological Research Projects from the Guizhou Education Department(Qian jiao ji[2023]003)the Hundred-Level Innovative Talent Project of the Guizhou Provincial Science and Technology Department(Qiankehe Platform Talent-GCC[2023]018)the Major Project of Guizhou Province“Research and Application of Key Technologies for Trusted Large Models Oriented to Public Big Data”(Qiankehe Major Project[2024]003)the Guizhou Province Computational Power Network Security Protection Science and Technology Innovation Talent Team(Qiankehe Talent CXTD[2025]029).
文摘As blockchain technology rapidly evolves,smart contracts have seen widespread adoption in financial transactions and beyond.However,the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems.Although numerous detection techniques have been proposed,existing methods suffer from significant limitations,such as class imbalance and insufficient modeling of transaction-related semantic features.To address these challenges,this paper proposes an oversampling-based detection framework for Ponzi smart contracts.We enhance the Adaptive Synthetic Sampling(ADASYN)algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions.This enhancement facilitates the generation of high-quality minority class samples and effectively mitigates class imbalance.In addition,we design a Contract Transaction Graph(CTG)construction algorithm to preserve key transactional semantics through feature extraction from contract code.A graph neural network(GNN)is then applied for classification.This study employs a publicly available dataset from the XBlock platform,consisting of 318 verified Ponzi contracts and 6498 benign contracts.Sourced from real Ethereum deployments,the dataset reflects diverse application scenarios and captures the varied characteristics of Ponzi schemes.Experimental results demonstrate that our approach achieves an accuracy of 96%,a recall of 92%,and an F1-score of 94%in detecting Ponzi contracts,outperforming state-of-the-art methods.
基金supported by the National Natural Science Foundation of China(Grant No.61762071,Grant No.61163025).
文摘The Internet of Vehicles(IoV)operates in highly dynamic and open network environments and faces serious challenges in secure and real-time authentication and consensus mechanisms.Existing methods often suffer from complex certificate management,inefficient consensus protocols,and poor resilience in high-frequency communication,resulting in high latency,poor scalability,and unstable network performance.To address these issues,this paper proposes a secure and efficient distributed authentication scheme for IoV with reputation-driven consensus and SM9.First,this paper proposes a decentralized authentication architecture that utilizes the certificate-free feature of SM9,enabling lightweight authentication and key negotiation,thereby reducing the complexity of key management.To ensure the traceability and global consistency of authentication data,this scheme also integrates blockchain technology,applying its inherent invariance.Then,this paper introduces a reputation-driven dynamic node grouping mechanism that transparently evaluates and groups’node behavior using smart contracts to enhance network stability.Furthermore,a new RBSFT(Reputation-Based SM9 Friendly-Tolerant)consensus mechanism is proposed for the first time to enhance consensus efficiency by optimizing the PBFT algorithm.RBSFT aims to write authentication information into the blockchain ledger to achieve multi-level optimization of trust management and decision-making efficiency,thereby significantly improving the responsiveness and robustness in high-frequency IoV scenarios.Experimental results show that it excels in authentication,communication efficiency,and computational cost control,making it a feasible solution for achieving IoV security and real-time performance.
基金supported in part by the National Natural Science Foundation of China under Grant 62262073in part by the Yunnan Provincial Ten Thousand People Program for Young Top Talents under Grant YNWR-QNBJ-2019-237in part by the Yunnan Provincial Major Science and Technology Special Program under Grant 202402AD080002.
文摘In the age of big data,ensuring data privacy while enabling efficient encrypted data retrieval has become a critical challenge.Traditional searchable encryption schemes face difficulties in handling complex semantic queries.Additionally,they typically rely on honest but curious cloud servers,which introduces the risk of repudiation.Furthermore,the combined operations of search and verification increase system load,thereby reducing performance.Traditional verification mechanisms,which rely on complex hash constructions,suffer from low verification efficiency.To address these challenges,this paper proposes a blockchain-based contextual semantic-aware ciphertext retrieval scheme with efficient verification.Building on existing single and multi-keyword search methods,the scheme uses vector models to semantically train the dataset,enabling it to retain semantic information and achieve context-aware encrypted retrieval,significantly improving search accuracy.Additionally,a blockchain-based updatable master-slave chain storage model is designed,where the master chain stores encrypted keyword indexes and the slave chain stores verification information generated by zero-knowledge proofs,thus balancing system load while improving search and verification efficiency.Finally,an improved non-interactive zero-knowledge proof mechanism is introduced,reducing the computational complexity of verification and ensuring efficient validation of search results.Experimental results demonstrate that the proposed scheme offers stronger security,balanced overhead,and higher search verification efficiency.
文摘The next-generation RAN,known as Open Radio Access Network(ORAN),allows for several advantages,including cost-effectiveness,network flexibility,and interoperability.Now ORAN applications,utilising machine learning(ML)and artificial intelligence(AI)techniques,have become standard practice.The need for Federated Learning(FL)for ML model training in ORAN environments is heightened by the modularised structure of the ORAN architecture and the shortcomings of conventional ML techniques.However,the traditional plaintext model update sharing of FL in multi-BS contexts is susceptible to privacy violations such as deep-leakage gradient assaults and inference.Therefore,this research presents a novel blockchain-assisted improved cryptographic privacy-preserving federated learning(BICPPFL)model,with the help of ORAN,to safely carry out federated learning and protect privacy.This model improves on the conventional masking technique for sharing model parameters by adding new characteristics.These features include the choice of distributed aggregators,validation for final model aggregation,and individual validation for BSs.To manage the security and privacy of FL processes,a combined homomorphic proxy-reencryption(HPReE)and lattice-cryptographic method(HPReEL)has been used.The upgraded delegated proof of stake(Up-DPoS)consensus protocol,which will provide quick validation of model exchanges and protect against malicious attacks,is employed for effective consensus across blockchain nodes.Without sacrificing performance metrics,the BICPPFL model strengthens privacy and adds security layers while facilitating the transfer of sensitive data across several BSs.The framework is deployed on top of a Hyperledger Fabric blockchain to evaluate its effectiveness.The experimental findings prove the reliability and privacy-preserving capability of the BICPPFL model.
基金supported in part by the National Natural Science Foundation of China under Grant 62072351in part by the Key Research Project of Shaanxi Natural Science Foundation under Grant 2023-JCZD-35in part by the open research project of ZheJiang Lab under grant 2021PD0AB01。
文摘Blockchain technology is increasingly popular and has been widely applied in many industrial fields,due to its unique properties of decentralization,immutability,and traceability.Blockchain systems in different fields vary,with different block structures,consensus mechanisms and access permission models.These differences make it hard for different blockchain systems to interoperate with each other,which isolates them.Cross-chain technologies have been developed to solve this isolation problem in order to improve the interoperability of blockchains.Although some surveys on cross-chain technologies can be found,they are unable to keep up with the latest research progress due to their extremely fast pace of development.Moreover,the literature misses general criteria to evaluate the quality of cross-chain technologies.In this paper,a comprehensive literature review of cross-chain technologies is conducted by employing a comprehensive set of evaluation criteria.The preliminaries on blockchain interoperability are first presented.Then,a set of evaluation criteria is proposed in terms of security,privacy,performance,and functionality.The latest cutting-edge works are reviewed based on the proposed taxonomy of cross-chain technologies and their performance is evaluated against our proposed criteria.Finally,some open issues and future directions of cross-chain research are pointed out.
文摘Taxation,the primary source of fiscal revenue,has profound implications in guiding resource allocation,promoting economic growth,adjusting social wealth distribution,and enhancing cultural influence.The development of e-taxation provides a enhanced security for taxation,but it still faces the risk of inefficiency and tax data leakage.As a decentralized ledger,blockchain provides an effective solution for protecting tax data and avoiding tax-related errors and fraud.The introduction of blockchain into e-taxation protocols can ensure the public verification of taxes.However,balancing taxpayer identity privacy with regulation remains a challenge.In this paper,we propose a blockchain-based anonymous and regulatory e-taxation protocol.This protocol ensures the supervision and tracking of malicious taxpayers while maintaining honest taxpayer identity privacy,reduces the storage needs for public key certificates in the public key infrastructure,and enables selfcertification of taxpayers’public keys and addresses.We formalize the security model of unforgeability for transactions,anonymity for honest taxpayers,and traceability for malicious taxpayers.Security analysis shows that the proposed protocol satisfies unforgeability,anonymity,and traceability.The experimental results of time consumption show that the protocol is feasible in practical applications.
文摘The concept of Supply Chain 4.0 represents a transformative phase in supply chain management through advanced digital technologies like IoT, AI, blockchain, and cyber-physical systems. While these innovations deliver operational improvements, the heightened interconnectivity introduces significant cybersecurity challenges, particularly within military logistics, where mission-critical operations and life-safety concerns are paramount. This paper examines these unique cybersecurity requirements, focusing on advanced persistent threats, supply chain poisoning, and data breaches that could compromise sensitive operations. The study proposes a hybrid cybersecurity framework tailored to military logistics, integrating resilience, redundancy, and cross-jurisdictional security measures. Real-world applicability is validated through simulations, offering strategies for securing supply chains while balancing security, efficiency, and flexibility.
文摘Within the framework of the 2030 Agenda and to achieve the Sustainable Development Goals(SDGs),science,technology and innovation play an even more central role.Building on this foundation,the primary objective of this paper is to explore the potential applications of blockchain in supporting the achievement of these sustainability goals.Starting from a review of the relevant literature on this topic,the main fields in which blockchain can contribute to sustainable development will be identified.The main blockchain applications will then be analyzed and categorized according to these SDGs.This research will then critically present the main blockchain-based projects that emerged in the first stage of the study and were implemented by the United Nations.The main objectives and benefits of each project will be analyzed.This is where the originality of this paper lies.To the best of the author’s knowledge,this is one of the first attempts to present a comprehensive overview of the United Nations’projects related to SDGs 1,2,5,7,9,13,and 16.This paper,which bridges the gap between innovation management and the sustainability field,will contribute to the increasingly current debate on sustainability issues and be beneficial to scholars,practitioners,and policymakers alike.
基金supported by the National Natural Science Foundation of China(Grant No.62102449)the Central Plains Talent Program under Grant No.224200510003.
文摘With the increasing popularity of blockchain applications, the security of data sources on the blockchain is gradually receiving attention. Providing reliable data for the blockchain safely and efficiently has become a research hotspot, and the security of the oracle responsible for providing reliable data has attracted much attention. The most widely used centralized oracles in blockchain, such as Provable and Town Crier, all rely on a single oracle to obtain data, which suffers from a single point of failure and limits the large-scale development of blockchain. To this end, the distributed oracle scheme is put forward, but the existing distributed oracle schemes such as Chainlink and Augur generally have low execution efficiency and high communication overhead, which leads to their poor applicability. To solve the above problems, this paper proposes a trusted distributed oracle scheme based on a share recovery threshold signature. First, a data verification method of distributed oracles is designed based on threshold signature. By aggregating the signatures of oracles, data from different data sources can be mutually verified, leading to a more efficient data verification and aggregation process. Then, a credibility-based cluster head election algorithm is designed, which reduces the communication overhead by clarifying the function distribution and building a hierarchical structure. Considering the good performance of the BLS threshold signature in large-scale applications, this paper combines it with distributed oracle technology and proposes a BLS threshold signature algorithm that supports share recovery in distributed oracles. The share recovery mechanism enables the proposed scheme to solve the key loss issue, and the setting of the threshold value enables the proposed scheme to complete signature aggregation with only a threshold number of oracles, making the scheme more robust. Finally, experimental results indicate that, by using the threshold signature technology and the cluster head election algorithm, our scheme effectively improves the execution efficiency of oracles and solves the problem of a single point of failure, leading to higher scalability and robustness.
基金supported by the National Natural Science Foundation of China(Grant No.U24B20146)the National Key Research and Development Plan in China(Grant No.2020YFB1005500)Beijing Natural Science Foundation Project(No.M21034).
文摘With the rapid development of web3.0 applications,the volume of data sharing is increasing,the inefficiency of big data file sharing and the problem of data privacy leakage are becoming more and more prominent,and the existing data sharing schemes have been difficult to meet the growing demand for data sharing,this paper aims at exploring a secure,efficient and privacy-protecting data sharing scheme under web3.0 applications.Specifically,this paper adopts interplanetary file system(IPFS)technology to realize the storage of large data files to solve the problem of blockchain storage capacity limitation,and utilizes ciphertext policy attribute-based encryption(CP-ABE)and proxy re-encryption(PRE)technology to realize secure multi-party sharing and finegrained access control of data.This paper provides the detailed algorithm design and implementation of data sharing phases and processes,and analyzes the algorithms from the perspectives of security,privacy protection,and performance.
基金supported by the National Key R&D Program of China(2022YFB2701500)the National Natural Science Foundation of China(62272385,62311540156)+2 种基金Shaanxi Distinguished Youth Project(2022JC-47)the Key Research and Development Program of Shaanxi(2021ZDLGY06-04)Major Program of Shandong Provincial Natural Science Foundation for the Fundamental Research(ZR2022ZD03).
文摘Adaptor signature,a new primitive that alleviates the scalability issue of blockchain to some extent,has been widely adopted in the off-chain payment channel and atomic swap.As an extension of standard digital signature,adaptor signature can bind the release of a complete digital signature with the exchange of a secret value.Existing constructions of adaptor signatures are mainly based on Schnorr or ECDSA signature algorithms,which suffer low signing efficiency and long signature length.In this paper,to address these issues,we propose a new construction of adaptor signature using randomized EdDSA,which has Schnorr-like structure with higher signing efficiency and shorter signature length.We prove the required security properties,including unforgeability,witness extractability and pre-signature adaptability,of the new adaptor signature scheme in the random oracle model.We conduct a comparative analysis with an ECDSA-based adaptor signature scheme to demonstrate the effectiveness and feasibility of our new proposal.
文摘As AI systems scale, the limitations of cloud-based architectures, including latency, bandwidth, and privacy concerns, demand decentralized alternatives. Federated learning (FL) and Edge AI provide a paradigm shift by combining privacy preserving training with efficient, on device computation. This paper introduces a cutting-edge FL-edge integration framework, achieving a 10% to 15% increase in model accuracy and reducing communication costs by 25% in heterogeneous environments. Blockchain based secure aggregation ensures robust and tamper-proof model updates, while exploratory quantum AI techniques enhance computational efficiency. By addressing key challenges such as device variability and non-IID data, this work sets the stage for the next generation of adaptive, privacy-first AI systems, with applications in IoT, healthcare, and autonomous systems.
基金supported by the National Natural Science Foundation of China(NSFC)under Grant 61931005.
文摘Blockchain-based user-centric access network(UCAN)fails in dynamic access point(AP)management,as it lacks an incentive mechanism to promote virtuous behavior.Furthermore,the low throughput of the blockchain has been a bottleneck to the widespread adoption of UCAN in 6G.In this paper,we propose Overlap Shard,a blockchain framework based on a novel reputation voting(RV)scheme,to dynamically manage the APs in UCAN.AP nodes in UCAN are distributed across multiple shards based on the RV scheme.That is,nodes with good reputation(virtuous behavior)are likely to be selected in the overlap shard.The RV mechanism ensures the security of UCAN because most APs adopt virtuous behaviors.Furthermore,to improve the efficiency of the Overlap Shard,we reduce cross-shard transactions by introducing core nodes.Specifically,a few nodes are overlapped in different shards,which can directly process the transactions in two shards instead of crossshard transactions.This greatly increases the speed of transactions between shards and thus the throughput of the overlap shard.The experiments show that the throughput of the overlap shard is about 2.5 times that of the non-sharded blockchain.
文摘The accelerated advancement of the Internet of Things(IoT)has generated substantial data,including sensitive and private information.Consequently,it is imperative to guarantee the security of data sharing.While facilitating fine-grained access control,Ciphertext Policy Attribute-Based Encryption(CP-ABE)can effectively ensure the confidentiality of shared data.Nevertheless,the conventional centralized CP-ABE scheme is plagued by the issues of keymisuse,key escrow,and large computation,which will result in security risks.This paper suggests a lightweight IoT data security sharing scheme that integrates blockchain technology and CP-ABE to address the abovementioned issues.The integrity and traceability of shared data are guaranteed by the use of blockchain technology to store and verify access transactions.The encryption and decryption operations of the CP-ABE algorithm have been implemented using elliptic curve scalarmultiplication to accommodate lightweight IoT devices,as opposed to themore arithmetic bilinear pairing found in the traditional CP-ABE algorithm.Additionally,a portion of the computation is delegated to the edge nodes to alleviate the computational burden on users.A distributed key management method is proposed to address the issues of key escrow andmisuse.Thismethod employs the edge blockchain to facilitate the storage and distribution of attribute private keys.Meanwhile,data security sharing is enhanced by combining off-chain and on-chain ciphertext storage.The security and performance analysis indicates that the proposed scheme is more efficient and secure.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB1714100in part by the National Natural Science Foundation of China(NSFC)under Grant 62371082 and 62001076in part by the Natural Science Foundation of Chongqing under Grant CSTB2023NSCQ-MSX0726 and cstc2020jcyjmsxmX0878.
文摘To protect user privacy and data security,the integration of Federated Learning(FL)and blockchain has become an emerging research hotspot.However,the limited throughput and high communication complexity of traditional blockchains limit their application in large-scale FL tasks,and the synchronous traditional FL will also reduce the training efficiency.To address these issues,in this paper,we propose a Directed Acyclic Graph(DAG)blockchain-enabled generalized Federated Dropout(FD)learning strategy,which could improve the efficiency of FL while ensuring the model generalization.Specifically,the DAG maintained by multiple edge servers will guarantee the security and traceability of the data,and the Reputation-based Tips Selection Algorithm(RTSA)is proposed to reduce the blockchain consensus delay.Second,the semi-asynchronous training among Intelligent Devices(IDs)is adopted to improve the training efficiency,and a reputation-based FD technology is proposed to prevent overfitting of the model.In addition,a Hybrid Optimal Resource Allocation(HORA)algorithm is introduced to minimize the network delay.Finally,simulation results demonstrate the effectiveness and superiority of the proposed algorithms.
基金supported by the National Natural Science Foundation of China under Grant No.U20A20182.
文摘As an effective strategy to address urban traffic congestion,traffic flow prediction has gained attention from Federated-Learning(FL)researchers due FL’s ability to preserving data privacy.However,existing methods face challenges:some are too simplistic to capture complex traffic patterns effectively,and others are overly complex,leading to excessive communication overhead between cloud and edge devices.Moreover,the problem of single point failure limits their robustness and reliability in real-world applications.To tackle these challenges,this paper proposes a new method,CMBA-FL,a Communication-Mitigated and Blockchain-Assisted Federated Learning model.First,CMBA-FL improves the client model’s ability to capture temporal traffic patterns by employing the Encoder-Decoder framework for each edge device.Second,to reduce the communication overhead during federated learning,we introduce a verification method based on parameter update consistency,avoiding unnecessary parameter updates.Third,to mitigate the risk of a single point of failure,we integrate consensus mechanisms from blockchain technology.To validate the effectiveness of CMBA-FL,we assess its performance on two widely used traffic datasets.Our experimental results show that CMBA-FL reduces prediction error by 11.46%,significantly lowers communication overhead,and improves security.
