【影响因子】11.072
【主题类别】
--
【Abstract】This study provides circular economy principles in natural resource management (NRM) in Vietnam when merging financial sustainability. Prior studies have neglected NRM in terms of utilizing circular economy principles (CEP) with the support of financial sustainability (FS). The main goal is to improve CEP in NRM utilizing the FS. This study employs the novel hybrid method to explore the multi-hierarchical NRM structure, address the interrelationships among CE and NRM attributes, and identify the attributes for improvement with the support of FS. This study proposes 85 criteria across 13 aspects base on the natural resource-based view. The results reveal a valid set of 20 criteria spanning six aspects. The aspects comprise operational digitalization, Fintech application and environmental strategy. The practical criteria include digital ecosystem collaborations, automation and robotics operations, compliance with environmental standards and laws, blockchain adoption, and data security. The FS is indicated as the decisive perspective for improving the CEP in NRM.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Natural resource management; Financial sustainability; Circular economy; Operation digitalization; Fuzzy decision-making trial and evaluation; laboratory
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】9.498
【主题类别】
--
【Abstract】The increasing adoption of electric vehicles (EVs) and the corresponding surge in lithium-ion battery (LIB) production have intensified the focus on sustainable end-of-life (EOL) management strategies (i.e., reuse, repurpose, remanufacture, and recycle). This paper presents a systematic literature review of the entire remanufacturing process of LIBs, aiming to offer a cohesive perspective on the approach that reduces the environmental impact of LIB waste by prolonging their lifecycle for reuse in their original EV applications. It reveals major issues from EOL collection to renewed batteries, clustering results into six research streams, and proposes a research agenda to develop integrative, data-driven models that incorporate technical, economic, and environmental considerations. Key findings highlight the need for standardised, non-damaging joining techniques, enhanced safety protocols for disassembly, and scalable cathode re-functionalisation methods. Recommendations include leveraging advanced technologies such as AI, machine learning, IoT, and blockchain to optimise remanufacturing processes and enhance supply chain transparency and efficiency. This comprehensive review aims to foster the development of sustainable remanufacturing practices, contributing to the circular economy and supporting the growth of the EV industry.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Remanufacturing; Electric vehicle; Lithium-ion batteries; Automotive; Sustainability
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】8.263
【主题类别】
--
【Abstract】This paper introduces a novel Privacy-Preserving Verifiable Federated Learning (PPVFL) scheme that integrates blockchain technology and homomorphic encryption to address critical challenges in decentralized machine learning. The proposed scheme ensures data privacy, integrity, verifiability, robust security, and efficiency in collaborative learning environments, particularly insensitive domains such as healthcare. By leveraging blockchain's decentralized, immutable ledger and homomorphic encryption's capability to perform computations on encrypted data, the model maintains the confidentiality of sensitive information throughout the learning process. The inclusion of Byzantine fault tolerance and Elliptic Curve Digital Signature Algorithm (ECDSA) further enhances the system's security against malicious attacks and data tampering, while the optimization of computational processes ensures efficient model training and communication. The novelty of this work lies in the seamless integration of blockchain and homomorphic encryption within a federated learning framework, specifically tailored for post-quantum cryptography, a combination that has not been extensively explored in prior research. This research represents a significant advancement insecure and efficient federated learning, offering a promising solution for industries that prioritize data privacy, security, and trust in collaborative machine learning. The effectiveness, security, and efficiency of the PPVFL scheme were validated using the Glaucoma dataset. The proposed method outperformed baseline federated learning algorithms, achieving a Dice coefficient of 0.918 and a Hausdorff distance of 4.05 on Severe Glaucoma (SG) cases, compared to 0.905 and 5.27, respectively, with traditional FedAvg. Moreover, the integration of blockchain and homomorphic encryption ensured that data privacy was upheld without compromising model performance, while efficient computation and communication processes minimized latency and resource consumption. This study contributes a robust, privacy-preserving, secure, efficient, and verifiable federated learning framework that addresses the pressing need for secure and scalable data management in distributed machine learning environments.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Federated learning; Blockchain; Homomorphic encryption; Consensus algorithm; Fault tolerance
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Son, Jaemin Ryu, Doojin
【影响因子】8.235
【主题类别】
--
【Abstract】We analyze the competitive dynamics between a decentralized financial system, called a protocol for loanable funds (PLF), and a centralized financial system. A PLF primarily differs from traditional banks in terms of its purpose and its decentralized ledger. While traditional banks pursue profit maximization, the PLF with a decentralized ledger system liquidates borrowing demand in line with the supply of deposits. We provide a theoretical framework that incorporates the differences among the lending markets to outline their competitive dynamics and suggest an optimal design for the PLF's consensus algorithm. The traditional bank incurs a cost to secure market power that depends on its degree of heterogeneity from the PLF. Our results suggest channels through which monetary policy influences the interest rates of PLFs.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain trilemma; Centralized finance; Decentralized finance; Financial stability; Protocol for loanable funds
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-B
【影响因子】7.862
【主题类别】
--
【Abstract】The field of construction informatics is fragmented and lacks clarity in understanding the interconnection of different data management strategies. This makes it challenging to address industry-specific data management issues. Using a critical interpretive synthesis, this study reviews and integrates both present and emerging data management approaches in construction informatics. The review is meant to be comprehensive, encompassing technologies and concepts such as Open Schema, Information Container, Common Data Environments, Linked Data, as well as cutting-edge Web3 technologies such as blockchain and decentralized data protocols. The different approaches are identified and classified into five categories and mapped into a two-dimensional framework that considers data storage and data processing modes. The systematic categorization provides a simple, but comprehensive understanding of data management strategies in construction informatics. Moreover, the framework allows to identify the state of the art and trends of data management approaches, providing guidance for future research perspectives, especially in the intersection with Web3 technologies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Construction informatics; Data management approaches; Web3; BIM; Linked data; Blockchain
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】7.574
【主题类别】
--
【Abstract】Undoubtedly, blockchain technology has emerged as one of the most fascinating advancements in recent decades. Its rapid development has attracted a diverse range of experts from various fields. Over the past five years, numerous blockchains have been launched, hosting a multitude of applications with varying objectives. However, a key limitation of blockchain-based services and applications is their isolation within their respective host blockchains, preventing them from recording or accessing data from other blockchains. This limitation has spurred developers to explore solutions for connecting different blockchains without relying on centralized intermediaries. This new wave of projects, officially called Layer 3 projects (L3) initiatives, has introduced innovative concepts like cross-chain transactions, multi-chain frameworks, hyper-chains, and more. This study provides an overview of these significant concepts and L3 projects while categorizing them into interoperability and scalability solutions. We then discuss opportunities, challenges, and future horizons of L3 solutions and present a SWOT (Strengths-Weaknesses-Opportunities-Threats) analysis of the two groups of L3 solutions and all other proposals. As an important part, we introduce the concept of Universal decentralized finance (DeFi) as one the most exciting applications of L3s which decreases transaction costs, enhances the security of crowdfunding, and provides many improvements in distributed lending-borrowing processes. The final part of this study maps the blockchain's triangle problem on L3s and identifies current challenges from the L3's perspective. Ultimately, the future directions of L3 for both academic and industry sectors are discussed.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Chainlink; Fantom sonic; Interoperability; Scalability; Universal deFi
【发表时间】2025
【收录时间】2024-11-18
【文献类型】
CCF-A
【影响因子】7.231
【主题类别】
--
【Abstract】The requirements for large amounts of data have promoted the rapid emergence of an industry for trading data. However, the current one-to-one trading constraints in the existing data trading schemes lead to low security and low efficiency. To tackle the challenges, a novel one-to-many distributed data trading scheme is proposed based on blockchain, which enables a data seller to sell one piece of data to multiple data buyers simultaneously, saving storage resources and computing resources significantly. Firstly, some new smart contracts are devised for two decentralized applications. Then, attribute-based searchable encryption technology is proposed to establish a data circulation scheme that realizes end-to-end encryption of data and ensures data security and highly efficient access. Finally, an inspection mechanism based on zero-knowledge proof and a pricing strategy based on the Stackelberg game are designed to guarantee fairness in trading and maximize revenue. The experiment results show that, in comparison to one-to-one trading, the high efficiency of this data trading scheme gradually emerges as the number of buyers (n) is greater than 2, and the run time is less than 1/10 of the former when n =35. Furthermore, the pricing strategy can enable buyers and sellers to obtain more revenue when n>4 .
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Data security; Security; Pricing; Encryption; Inspection; Servers; Protection; Data privacy; Nickel; Data trading; blockchain; zero-knowledge proof; Stackelberg game; attribute-based encryption
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-B
【影响因子】5.859
【主题类别】
--
【Abstract】The current high-fidelity generation and high-precision detection of DeepFake images are at an arms race. We believe that producing DeepFakes that are highly realistic and "detection evasive" can serve the ultimate goal of improving future generation DeepFake detection capabilities. In this paper, we propose a simple yet powerful pipeline to reduce the artifact patterns of fake images without hurting image quality by performing implicit spatial-domain notch filtering. We first demonstrate that frequency-domain notch filtering, although famously shown to be effective in removing periodic noise in the spatial domain, is infeasible for our task at hand due to the manual designs required for the notch filters. We, therefore, resort to a learning-based approach to reproduce the notch filtering effects, but solely in the spatial domain. We adopt a combination of adding overwhelming spatial noise for breaking the periodic noise pattern and deep image filtering to reconstruct the noise-free fake images, and we name our method DeepNotch. Deep image filtering provides a specialized filter for each pixel in the noisy image, producing filtered images with high fidelity compared to their DeepFake counterparts. Moreover, we also use the semantic information of the image to generate an adversarial guidance map to add noise intelligently. Our large-scale evaluation on 3 representative DeepFake detection methods (tested on 16 types of DeepFakes) has demonstrated that our technique significantly reduces the accuracy of these 3 fake image detection methods, 36.79% on average and up to 97.02% in the best case.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Deepfakes; Filtering; Notch filters; Image synthesis; Frequency-domain analysis; Fingerprint recognition; Detectors; DeepFake; DeepFake evasion; DeepFake detection
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-B
【影响因子】5.493
【主题类别】
--
【Abstract】Malicious attacks and the introduction of illegal data put blockchains at risk, and blockchain governance is gaining increasing attention. The redactable blockchain technology has become a mainstream solution for blockchain governance. However, a low completion rate for redaction tasks limits current redactable blockchain technologies, primarily due to the absence of an effective incentive mechanism for participants. This gap underscores the urgent need for designing and implementing robust incentive mechanisms in redactable blockchains. Incentive mechanisms can motivate and guide entities to participate and perform desired behaviors through awards and punishments. This paper proposes Concordit, the first deployable credit- based incentive mechanism for redactable blockchains. Its purpose is to encourage submitters to submit legal redaction requests, modifiers to perform legal redaction operations, and verifiers to maintain the behavior consistent with the consensus algorithm. In the context of permissioned blockchains, Concordit utilizes a credit value system for awards and punishments. Additionally, we use a game theory-based mechanism to analyze and model participants' behavior utilities in the redactable blockchain. Meanwhile, we evaluate the credibility of nodes by combining their static initial credit values and dynamic behavior-related credit values. This system prioritizes high-credibility nodes as participants, thereby enhancing the completion rate for redaction tasks. Finally, the implementation and performance evaluation of our Concordit incentive mechanism demonstrate its effectiveness and practicality.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Incentive mechanism; Credit value; Blockchain governance; Redactable blockchain; Game theory analysis
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Roy, Utsa Ghosh, Nirnay
【影响因子】4.960
【主题类别】
--
【Abstract】The Internet of Things (IoT) paradigm has widespread applications across many fields in which private and sensitive user or environmental data are sensed and shared. Most present-day IoT applications depend on centralized cloud servers for authentication and access control. Validating the identity of a user and determining the legitimacy of his/her access requests require multiple rounds of data communications over the untrusted Internet, exposing sensitive data to potential attacks. Thus, protecting these data from security and privacy attacks and ensuring legitimate access is imperative. To address this challenge, we adopt an emerging technology called blockchain to propose a decentralized security framework called BloAC. It ensures secure access control in IoT networks without the intervention of the back-end cloud. We have used the Hyperledger Fabric, an open-source, permissioned blockchain platform, for implementing a prototype system using customized attribute-based access control (ABAC) policies. We have performed simulated and real test bed-based experiments to illustrate that BloAC outperforms the cloud-server-based access control in latency and scalability, significantly reducing latency by up to 42.45% compared to cloud-based solutions. Finally, we conduct a security analysis to formally verify the ABAC policies used in BloAC and establish its robustness against attacks theoretically and using the AVISPA tool.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; Hyperledger fabric; ABAC policy; Access control; Smart contract; Edge-to-edge communication
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Tian, Jin Tian, Junfeng Du, Ruizhong
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】Sharding is a popular technology for blockchain systems that addresses scalability while ensuring security and decentralization. However, there are still many issues. Firstly, the existing sharding solutions exhibit a high percentage of cross-shard transactions, which place a substantial burden on system resources and result in a significant degradation of performance. Secondly, none of these solutions adequately accounts for the inherent heterogeneity among nodes, and the interoperability of different nodes is constrained by security concerns, thereby impeding the practical advancement of blockchain applications. In this paper, a novel subjective logical trust-based tree sharding system, MSLTChain, is introduced to alleviate the processing workload of cross-shard transactions. The proposal encompasses a tree sharding structure and a trust management model, enabling the processing and validation of cross-shard transactions within the parent shard. Moreover, an adaptive algorithm is incorporated to dynamically fine-tune scalability, further augmenting system throughput. A subjective logical trust model is employed to portray the heterogeneity between nodes and enhance the system's security level. The paper also conducts a comprehensive theoretical analysis, evaluating the security, scalability, and performance aspects. Finally, the experimental findings substantiate the capability of MSLTChain to satisfy the dual imperatives of scalability and security within the context of sharding blockchain.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Sharding; Scalability; Peer-to-peer computing; Security; Protocols; Throughput; Blockchain; trust; sharding; scalability
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】Providing low latency, high security, and high resource utilization for Internet of Things (IoT) networks is challenging due to the heterogeneous nature of these networks and the need for more standardization in security algorithms. Current edge computing-based IoT solutions decrease network latency and improve resource utilization but do not provide adequate security because they offer multiple attack surfaces for adversaries. Recent work uses blockchain technology to provide better security in IoT networks. However, blockchain-based solutions suffer from scalability problems and can increase latency. Sidechains are parallel blockchain networks typically used to increase the scalability of blockchain networks. We propose a novel Sidechain-based Access control and Trust evaluation mechanism for IoT networks (SATI) to decrease network latency and improve scalability, security, and energy efficiency. SATI uses a sidechain with the blockchain network to improve its scalability. It also uses edge computing to provide low network latency and high resource utilization in terms of CPU and memory usage. In addition, trust evaluation and attribute-based access control mechanisms are used to improve the security of the IoT network. We compare our work with existing mechanisms in terms of scalability, security, latency, and CPU and memory usage. In addition, we perform a formal security analysis of the SATI mechanism using reduction-based analysis and the Scyther verification tool.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Internet of Things; Blockchains; Security; Scalability; Access control; Edge computing; Resource management; Attribute-based access control; blockchain; edge computing; hyperledger fabric; IoT security; reduction-based analysis; Scyther tool; sidechain; trust mechanism
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】In this paper, we propose a resilient and fast block transmission system for Hyperledger Fabric in multi-cloud environments. The goal of the proposed system is to improve the scalability, transaction throughput, and resilience of Hyperledger Fabric by minimizing the block synchronization time among nodes. To achieve this goal, the proposed system is designed to deliver blocks quickly and reliably to all the participating nodes in time-varying multi-cloud environments. The proposed system includes the delay estimating process with O(N) control message overhead over the P2P network, the effective bandwidth estimating process for block transmission, the Gaussian Mixture Model-based clustering and cluster leader selecting process, and hybrid P2P multicast tree constructing process. In addition, a control message format and delivery process are proposed to efficiently provide hybrid P2P multicast tree and neighbor nodes information to all the participating nodes. And we propose a pull-based local block loss recovery process that can receive lost blocks from multi-node without complicated scheduling using a rateless code. The proposed system is fully implemented by using well-known open sources (e.g., Hyperledger Fabric, Docker, Containernet, and Mininet) and Go/C/Python. Experiment results show that the proposed system can reduce the maximum block arriving time among all the participating nodes by approximately 50%similar to 95% compared to the existing algorithms. This improves not only blockchain transaction per second, but also resilience to various network-layer vulnerabilities and attacks that may occur when the block propagation delay increases.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; block transmission; hyperledger fabric; multi-cloud; P2P network
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】This study proposes an intelligent approach to identifying an injured soldier on blockchain-integrated Internet-of-Battlefield Things (IoBT) employing unmanned aerial vehicles (UAVs). The intelligent approach combines a unique deep learning (DL) model with a smartwatch-based heart-rate (HR) data collection technique. Different activation functions (i.e., MISH and Leaky rectified linear unit) are used in the proposed DL model to enhance the identification task by extracting the in-depth features from the images. Furthermore, a smart-watch-based HR data analyzing technique is introduced to confirm the injury of a soldier. However, due to the UAV's low battery capacity, the identification task is offloaded to the neighboring edge computing server to improve system performance. Moreover, to restrict the access of registered IoT devices (e.g., UAV, smartwatch, etc.) and protect the sensitive data leakage on IoBT, a blockchain-integrated access control (ACL) mechanism is utilized. Detailed experimental results are provided for the proposed DL model that outperforms existing DL models. Besides, implementing a smartwatch-based HR data analysis technique for the soldiers improves the outcome of the proposed DL model. To provide a fine-grained data protection mechanism in the proposed system, a private blockchain-based ACL management policy is constructed utilizing hyperledger, and various assessment metrics have been scrutinized.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Autonomous aerial vehicles; Internet of Things; Wearable Health Monitoring Systems; Object recognition; Convolutional neural networks; Task analysis; Blockchains; Access control; blockchain; deep learning; edge computing; Internet-of-Battlefield Things; unmanned aerial vehicle
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】A blockchain provides decentralization and trustlessness features for the Industrial Internet of Things (IIoT), which expands the application scenarios of IIoT. To address the problem that blockchains cannot actively obtain off-chain data, the blockchain oracle is proposed as a bridge between the blockchain and external data. However, the existing oracle schemes make it difficult to solve the problem of low quality of service caused by frequent data changes and heterogeneous devices in IIoT, and the current oracle node selection schemes are difficult to balance security and quality of service. To tackle these problems, this paper proposes a secure and reliable oracle scheme that can obtain high-quality off-chain data. Specifically, we first design an oracle node selection algorithm based on a Verifiable Random Function (VRF) and reputation mechanism to securely select high-quality nodes. Second, we propose a data filtering algorithm based on a sliding window to further improve the consistency of the collected data. We verify the security of the proposed scheme through security analysis. The experimental results show that the proposed scheme can effectively select high-quality nodes, reduce data differences, and improve the quality of service of the oracle. In the oracle network with malicious nodes accounting for 10%, the data accuracy rate is increased by about 4%, and the data variance is reduced by about 45% on average.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Security; Industrial Internet of Things; Contracts; Quality of service; Task analysis; Soft sensors; IIoT; blockchain; oracle
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Gu, Ke Wang, Yi Qiu, Juan Li, Xiong Zhang, Jianming
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】With the extensive deployment of vehicular ad-hoc networks (VANETs), it becomes an inevitable choice to provide enhanced in-vehicle services for uploading a vast amount of shared vehicular data to cloud storage. However, there is still a lack of effective deduplication and audit methods for cloud-stored data in VANET scenarios. To address the securities of cloud-stored data in VANETs, we propose a blockchain-based data deduplication and distributed audit scheme for shared data under cloud-fog computing-based VANETs in this paper. In our scheme, we construct a distributed audit model for VANETs, where road side units (RSUs) are partitioned as multiple management areas. Each management area can solely make their consensus for data integrity verification to audit the cloud storage provider without depending on any third-party auditors (TPAs). Also, we establish a blockchain-based monitoring mechanism maintained by the fog servers to ensure the integrity of the uploading and auditing records and enable related entities within the system to verify corresponding audit results (or records). Furthermore, we propose a lightweight dual-verifier structure to adapt to resource-constrained VANET scenarios. Through our dual-verifier mechanism, our scheme can effectively resist proof-replay attacks. Related theoretical analysis and experimental results show our data deduplication and distributed audit scheme is efficient and effective for VANET scenarios.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】cloud-fog computing; VANETs; distributed auditing; distributed auditing; data deduplication; data deduplication; data deduplication; data deduplication; data deduplication; blockchain; blockchain; blockchain; distributed auditing; blockchain
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Aggarwal, Shubhani Kaddoum, Georges
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】Information and Communication Technology (ICT) provides customers with utilities and smart grid solutions, enabling enhanced monitoring and control of energy management systems. This technology is poised to elevate the reliability, sustainability, and efficiency of future electric grids through the implementation of advanced metering infrastructure (AMI). However, current Supervisory Control and Data Acquisition (SCADA) systems lack trusted machine authentication in smart grid communications, leaving the electric grid vulnerable to cyberattacks via sophisticated network technologies such as wireless access points, sensors, routers, and gateways. Therefore, ensuring proper management of data integrity from field sensors is crucial to enhance the reliability of SCADA systems. In this context, the utilization of quantum key distribution (QKD) key pairs is proposed to uphold integrity in smart grid communications. This paper presents a fibre optic blockchain network designed to manage and utilize cryptographic keys, facilitating the authentication of peer-to-peer (P2P) communications in SCADA systems. This demonstration underscores the feasibility of employing QKD and blockchain to further strengthen the integrity and authentication of smart grid communications. Additionally, this paper delves into discussing the performance metrics and overhead expenses of the proposed scheme in comparison with existing state-of-the-art proposals. Simulation results highlight the significant impact of blockchain size on the system setup's throughput and latency.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】SCADA; quantum key distribution; Blockchain; MQTT protocol; MQTT protocol; smart grid communications; smart grid communications; authentication; authentication; data integrity; data integrity; authentication; data integrity
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Sharma, Neeraj Kapoor, Kalpesh
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】The use of blockchain-based cryptocurrencies has significantly increased over the last ten years; nevertheless, the broader acceptance of these currencies is hindered by scaling challenges. Payment Channel Networks (PCN), which operates as a layer two solution, presents itself as a viable option for augmenting the scalability of a blockchain network. In order to reduce the time and cost associated with the on-chain settlement, users have the option to conduct off-chain transactions through payment channels within their network. The growth of the PCN is expected to be accompanied by a corresponding increase in the number of transactions. However, the current distributed routing algorithms are unable to manage several simultaneous transactions due to deadlocks efficiently. We illustrate the possibility of deadlock in distributed routing algorithms. We prove that routing two transactions in PCN is NP-complete by reducing it from a two-commodity flow problem. In contrast to earlier work that avoided deadlock by exploiting locking or priority queues, our work emphasizes routing algorithms to avoid conditions for deadlock. We enhance the routing choices to minimize the number of saturated links that can cause deadlock. Resource allocation graphs are used to illustrate the necessary and sufficient conditions required for transactions to be in a deadlock. We also show how the dynamic behavior of resources can affect the deadlock situation in future timestamps. The deadlock trilemma and the relation between concurrency, resources, and deadlocks have also been discussed. The experimental evaluation shows that the proposed methodology yields an improvement in transaction count in the Speedy and the Webflow algorithms by 41% and 27%, respectively.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; payment channel network; lightning network; distributed routing; deadlocks; Blockchain; payment channel network; lightning network; distributed routing; deadlocks
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Li, Yixin Liang, Liang Jia, Yunjian Wen, Wanli
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】Block propagation is a critical step in the consensus process, which determines the fork rate and transaction throughput of public blockchain systems. To accelerate block propagation, existing block relay protocols reduce the block size using transaction hashes, which requires the receiver to reconstruct the block based on the transactions in its mempool. Hence, their performance is highly affected by the number of transactions missed by mempools, especially in the P2P network with frequent arrival and departure of nodes. In this paper, we introduce Presync, a transaction synchronization protocol that can reduce the difference of transactions between the block and the mempool with controllable bandwidth overhead. It allows mining pool servers to synchronize the transactions in candidate blocks before the propagation of a valid block. Low-bandwidth mode provides a lightweight synchronization by identifying the unsynchronized transactions, so that the missing transactions can be detected with a low redundancy. High-bandwidth mode conducts a full synchronization of the candidate block using short hashes, and the Merkle root is utilized to match the valid block. We study the performance of Presync through stochastic modeling and experimental evaluations. The results illustrate that low and high-bandwidth modes can respectively reduce the end-to-end delay of compact block by 60% and 78% with bandwidth usages 25KB and 63KB, in a network with 5 active pool servers and 2/3 online probability of full nodes.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Peer-to-peer computing; Protocols; Relays; Synchronization; Blockchains; Bandwidth; Servers; Blockchain; propagation latency; transaction synchronization; stochastic model
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】With the vigorous development of the blockchain industry, cross-chain transactions can effectively solve the problem of "islands of value" caused by the inability to interact between different chains. However, security risks in reputation management caused by cross-chain transactions implemented through notary solutions have always existed. Consequently, this paper proposes a blockchain cross-chain transaction method based on decentralized dynamic reputation value assessment. The notary election phase addresses the issue of the continually changing behavior of notaries in actual transactions by designing a dynamic evaluation window mechanism based on an RNN. Moreover, a reputation-rating decay mechanism is introduced to avoid the problem of reputation value recovery caused by malicious notaries being inactive for a long time. Relative to alternative reputation assessment models, the proposed method offers a thorough evaluation of user behavior and effectively identifies malicious activities in real-time. Finally, the method was tested by deploying it on the Ethereum blockchain. Our approach offers more dynamic settings for window parameters, adapting to changes in notary behavior and reducing the number of detections within the same timeframe by approximately 59.14%. The weight factor settings are also optimized, allowing for adjustments based on specific situations to achieve accurate reputation values. Overall, this method not only enhances the security of cross-chain transactions but also reduces operational costs by 53.3% compared to traditional technologies.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Smart contracts; Security; Cryptocurrency; Vehicle dynamics; Protocols; Adaptation models; Cross-chain; reputation value; dynamic window; decentralization
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Rao, Zhiyuan You, Lin Hu, Gengran Zhu, Fei
CCF-C
【影响因子】4.758
【主题类别】
--
【Abstract】The volume of the data generated by the Internet of Things (IoT) has been expanding rapidly, primarily driven by the personal devices. However, with the severely limited memory resources and difficult security authentication processes, large amounts of the data must be abandoned. Blockchain of Things (BCoT) provides a scalable solution to these challenges by integrating blockchain and the IoT. In this paper, we propose an efficient BCoT-based data trading system using physical unclonable functions (PUFs) for authentication. PUFs are utilized for iterative keys and pseudo-identity generation to ensure the privacy and security of the IoT devices. To protect the copyright of the sellers' data, the system sets up a data arbitration center to address the issues related to the unauthorized resale of the datasets. In addition, a fuzzy comprehensive evaluation model is proposed to regulate the behavior of the data traders. Our security analysis demonstrates that the proposed system is not only secure under the ROR model but is also resistant to the internal attacks. The experimental results show the reliability and the effectiveness of the proposed system.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchain; trading system; smart contract; smart contract; physical unclonable functions (PUFs); physical unclonable functions (PUFs); smart contract; physical unclonable functions (PUFs)
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】4.199
【主题类别】
--
【Abstract】The financial sector is increasingly facing advanced cyber threats, necessitating a shift from traditional security measures to more dynamic frameworks. This study presents a novel integration of Zero Trust architecture with hybrid access control system and blockchain technology to enhance security in financial institutions. Zero Trust enforces continuous authentication and dynamic access controls, while blockchain secures digital identities and transaction logs through its immutable ledger, ensuring data integrity and non-repudiation. The proposed framework, evaluated using OMNeT++ simulations enhanced by Ethereum-Ganache, shows improved detection accuracy, reduced false positives, and increased resistance to insider threats and other attacks. It also strengthens compliance with regulatory requirements through robust audit trails, providing enhanced protection for sensitive financial data.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Security in financial networks; Zero trust; Blockchain; Hybrid access control; Network simulation; Advanced Persistent threats (APT); Threat detection
【发表时间】2025
【收录时间】2024-11-18
【文献类型】
【影响因子】3.847
【主题类别】
--
【Abstract】In the construction of new power systems, the traditional network security protection mainly based on boundary protection belongs to static defense and still relies mainly on manual processing in vulnerability repair, threat response, etc. It is difficult to adapt to the security protection needs in large-scale distributed new energy, third-party aggregation platforms, and flexible interaction scenarios with power grid enterprise systems. It is necessary to conduct research on dynamic security protection models for IoT and other Blockchain-based IoT architectures. This article proposes a network security comprehensive protection model P2AEDR based on different interaction modes of cloud-edge interaction and cloud-cloud interaction. Through continuous trust evaluation, dynamic access control, and other technologies, it strengthens the internal defense capabilities of power grid business, shifting from static protection as the core mode to a real-time intelligent perception and automated response mode, and ultimately achieving the goal of dynamic defense, meeting the security protection needs of large-scale controlled terminal access and third-party aggregation platforms. Meanwhile, this article proposes a dynamic trust evaluation algorithm based on deep learning, which protects the secure access and use of various resources in a more refined learning approach based on the interaction information monitored in the system. Through experimental verification of the dynamic trust evaluation algorithm, it is shown that the proposed model has good trust evaluation performance. Therefore, this research is beneficial for trustworthy Power IoT and other Blockchain-based IoT architectures.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】low-voltage control; protection model; dynamic defense; trust assessment; deep learning; Internet of Things (IoT); Power IoT (PIoT); blockchain; Blockchain-based IoT (BIoT)
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【DOI】 10.3390/s24216808
【Author】 Nasreen, Mehar Singh, Sunil Kumar
【影响因子】3.817
【主题类别】
--
【Abstract】Designing an efficient distributed blockchain system to store and access rising electronic medical records (EMR) is still challenging. Although many techniques have been designed to utilize EMRs proficiently, they still suffer from accessing time, storage time, and throughput. In this work, we have proposed a Merkle and B+ tree-based hybrid model to improve the performance of the blockchain system. B+ tree has improved the system's performance because of its practical layout and balanced structure. At the same time, Merkle Tree has ensured the integrity and security of the information. The proposed (B+ Merkle tree) BPMT model has reduced the storage time of records, improved the system's throughput, and significantly reduced memory use. These enhancements are supported by a thorough complexity analysis and testing on several datasets, which validate the efficacy and scalability of the model. The outcomes validate the performance improvements of the model and lay the groundwork for further developments in blockchain-based EMR management.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】EMR; Merkle tree; B plus tree; Integrity; Throughput; Security
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【Author】 Yang, Zheng Zhu, Hua Li, Zhao Wang, Gang Su, Meng
【影响因子】3.476
【主题类别】
--
【Abstract】In recent years, convolutional neural network (CNN) has achieved great success in the field of network security protection. With the popularization of smart terminals and the gradual increase of power grid informatization and digitization, the protection of power monitoring systems from various cybersecurity threads is a current scientific problem that needs to be solved urgently. To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. The examples under the public dataset containing 8 kinds of malware show that the proposed method is better than the traditional algorithmic model, and can accurately and efficiently achieve malware detection with strong generalization ability.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Application programming interface; convolutional neural network; convolutional neural network; malware detection; malware detection; network security; network security; power mobile terminal; power mobile terminal; SENet attention mechanism; SENet attention mechanism; SENet attention mechanism
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】3.476
【主题类别】
--
【Abstract】The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on "multivariate" modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate analysis is performed, the paper builds and reports the forecasting accuracy for techniques such as the Transformer-based Multi-head Attention network, Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BI-LSTM), Temporal Convolution Network (TCN), and conventional Vector Autoregressive (VAR) models. The findings revealed that the TCN model achieved the average lowest RMSE values of 0.0589 for stock data and 0.1554 for cryptocurrency data. Notably, the Multi-Head Attention model achieved average $R<^>{2}$ values of 0.92 for stock data and -1.98 for cryptocurrency data with respect to five variables (i.e., open, high, low, close and volume). According to the empirical studies conducted and reported in this paper, the transformer-based Multi-head Attention network outperformed other models such as LSTM, BI-LSTM, and more importantly conventional Vector Auto-Regression Models (VAR) in stocks and cryptocurrencies time series data where several variables were leveraged in building these multivariate-based models.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Data models; Predictive models; Time series analysis; Forecasting; Long short term memory; Analytical models; Biological system modeling; Convolutional neural networks; BiLSTM; Stock markets; Forecasting time series data; multivariate analysis; stock; cryptocurrency; vector autoregressive (VAR); temporal convolutional network (TCN); long short-term memory (LSTM); bidirectional long short-term memory (BI-LSTM)
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】3.476
【主题类别】
--
【Abstract】Recent statistics indicate a continuous rise in cryptojacking malware. This malware covertly exploits users' device resources to mine cryptocurrencies, such as Bitcoin, without their knowledge or consent. Cryptocurrency mining involves participants competing to generate a unique hash, with successful miners earning cryptocurrency tokens as rewards. As the difficulty of mining new cryptocurrencies increases, greater computational power and resources are required. Unfortunately, the growing popularity of cryptocurrencies has led to a significant increase in cryptojacking malware. Compounding this issue is the lack of adequate, practical solutions to combat this threat. Current shortcomings include a limited number of related studies, particularly in host-based cryptojacking, a scarcity of recent research, reliance on small or outdated datasets, and a shallow understanding of the behavior and characteristics of cryptojacking malware. This paper aims to address these gaps by introducing a holistic, intelligent cryptojacking malware detection system that: 1) provides a detailed analysis of the lifecycle of both host-based and web-based cryptojacking malware; 2) conducts a critical comparison of existing solutions, highlighting their weaknesses; 3) applies deep static analysis to identify key indicators crucial for cryptojacking analysis; 4) executes thorough dynamic analysis to demonstrate the real-world impact of cryptojacking; 5) utilizes a new, large, and robust cryptojacking dataset (CJDS) with over 100,000 samples, where the details of constructing this dataset are provided, (f) develops vision-based predictive models using 23 convolutional neural network (CNN) algorithms, extensively evaluated with comprehensive metrics; and 6) integrates the best-performing model to bulid a highly efficient cryptojacking detection system with an accuracy of 99%. This research offers valuable insights into the characteristics and consequences of cryptojacking, paving the way for further advancements in cybersecurity. It aims to protect digital environments from unauthorized resource exploitation and enhance the security of cryptocurrency-based systems.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Malware; Bitcoin; Predictive models; Blockchains; Static analysis; Convolutional neural networks; Prediction algorithms; Heuristic algorithms; Feature extraction; Cryptocurrency; Deep learning; Cryptojacking; malware; blockchain; CNN; cryptocurrency; cryptomining; dataset; deep learning; host-based; web-based; predictive models; detection system; artificial intelligence; static analysis; dynamic analysis
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【影响因子】3.476
【主题类别】
--
【Abstract】With the widespread integration of new technologies, IoT devices are becoming increasingly diverse and capable of handling highly complex tasks, compared to previous generations. This evolution has led to demands for a comprehensive security approach across multiple layers of an IoT architecture. This work proposes a scalable security solution from the edge to the cloud, combining Blockchain technology and anomaly-based Intrusion Detection Systems (IDSs). Smart contracts provide a transparent environment for registering and managing IoT devices on the cloud. Specifically, the smart contract includes two authorization levels for managing administrators and IoT devices. Besides, anomaly-based IDSs are deployed at Gateways to detect network attacks. We propose using lightweight machine learning models on FPGA hardware acceleration for Gateways. We have simulated the Blockchain network on the Ganache software, demonstrating that the smart contract effectively manages administrators and devices such that only authorized entities can access the system. The FPGA-based Gateway, which contains pre-trained Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) detection models from the IoT-23 dataset, has been deployed on the Alveo U280 card. The ANN model has achieved the highest processing speed at 20Gbps. The results indicate that integrating Blockchain and anomaly-based IDS significantly enhances scalable security in IoT networks.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Blockchains; Smart contracts; Security; Internet of Things; Engines; Access control; Distributed ledger; Logic gates; Training; Hardware acceleration; Network architecture; scalable security; IoT access control; blockchain; smart contracts; neural Networks; hardware accelerators; NetFPGA
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
CCF-B
【影响因子】3.180
【主题类别】
--
【Abstract】The education sector is currently experiencing profound changes, primarily driven by the widespread adoption of online platforms for conducting examinations. This paper delves into the utilization of smart contracts as a means to revolutionize the monitoring and execution of online examinations, thereby guaranteeing the traceability of evaluation data and examinee activities. In this context, the integration of advanced technologies such as the PoseNet algorithm, derived from the TensorFlow Model, emerges as a pivotal component. By leveraging PoseNet, the system adeptly identifies both single and multiple faces of examinees, thereby ensuring the authenticity and integrity of examination sessions. Moreover, the incorporation of the COCO dataset facilitates the recognition of objects within examination environments, further bolstering the system's capabilities in monitoring examinee activities.of paramount importance is the secure storage of evidence collected during examinations, a task efficiently accomplished through the implementation of the blockchain technology. This platform not only ensures the immutability of data but also safeguards against potential instances of tampering, thereby upholding the credibility of examination results. Through the utilization of smart contracts, the proposed framework not only streamlines the examination process but also instills transparency and integrity, thereby addressing inherent challenges encountered in traditional examination methods. One of the key advantages of this technological integration lies in its ability to modernize examination procedures while concurrently reinforcing trust and accountability within the educational assessment ecosystem. By harnessing the power of smart contracts, educational institutions can mitigate concerns pertaining to data manipulation and malpractice, thereby fostering a more secure and reliable examination environment. Furthermore, the transparency afforded by blockchain technology ensures that examination outcomes are verifiable and auditable, instilling confidence among stakeholders and enhancing the overall credibility of the assessment process. In conclusion, the adoption of smart contracts represents a paradigm shift in the realm of educational assessment, offering a comprehensive solution to the challenges posed by traditional examination methods. By embracing advanced technologies such as PoseNet and blockchain, educational institutions can not only streamline examination procedures but also uphold the highest standards of integrity and accountability. As such, the integration of smart contracts holds immense potential in shaping the future of online examinations, paving the way for a more efficient, transparent, and trustworthy assessment ecosystem.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Smart contracts; TensorFlow model; Blockchain technology; PoseNet; integration
【发表时间】2025
【收录时间】2024-11-18
【文献类型】
【DOI】 10.1016/j.is.2024.102485
【影响因子】2.592
【主题类别】
--
【Abstract】Hyperledger Fabric is one of the most popular permissioned blockchain platforms widely adopted in enterprise blockchain solutions. To optimize and fully utilize the platform, it is desired to conduct a thorough performance analysis of Hyperledger Fabric. Although numerous studies have analyzed the performance of Hyperledger Fabric, three significant limitations still exist. First, existing blockchain performance evaluation frameworks rely on fixed workload rates, which fail to accurately reflect the performance of blockchain systems in real-world application scenarios. Second, the impact of extending the breadth and depth of endorsement policies on the performance of blockchain systems has yet to be adequately studied. Finally, the impact of node crashes and recoveries on blockchain system performance has yet to be comprehensively investigated. To address these limitations, we propose a framework called BlockLoader, which offers seven different distributions of load rates, including linear, single-peak, and multi-peak patterns. Next, we employ the BlockLoader framework to analyze the impact of endorsement policy breadth and depth on blockchain performance, both qualitatively and quantitatively. Additionally, we investigate the impact of dynamic node changes on performance. The experimental results demonstrate that different endorsement policies exert distinct effects on performance regarding breadth and depth scalability. In the horizontal expansion of endorsement policies, the OR endorsement policy demonstrates stable performance, fluctuating around 88 TPS, indicating that adding organizations and nodes has minimal impact. In contrast, the AND endorsement policy exhibits a declining trend in performance as the number of organizations and nodes increases, with an average decrease of 10 TPS for each additional organization. Moreover, the dynamic behaviour of nodes exerts varying impacts across these endorsement policies. Specifically, under the AND endorsement policy, dynamic changes in nodes significantly affect system performance. The TPS of the AND endorsement policy shows a notable decline, dropping from 79.6 at 100 s to 41.96 at 500 s, reflecting a reduction of approximately 47% over time. Under the OR endorsement policy, the system performance remains almost unaffected.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】hyperledger fabric; BlockLoader; endorsement policy; node dynamic changes
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【DOI】 10.3390/math12213403
【Author】 Nechesov, Andrey Goncharov, Sergey
【影响因子】2.592
【主题类别】
--
【Abstract】In this work, a functional variant of the polynomial analogue of Gandy's fixed point theorem is obtained. Sufficient conditions have been found to ensure that the complexity of recursive functions does not exceed polynomial bounds. This opens up opportunities to enhance the expressivity of p-complete languages by incorporating recursively defined constructs. This approach is particularly relevant in the following areas: AI-driven digital twins of smart cities and complex systems, trustworthy AI, blockchains and smart contracts, transportation, logistics, and aerospace. In these domains, ensuring the reliability of inductively definable processes is crucial for maintaining human safety and well-being.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】polynomial computability; Gandy's fixed point theorem; artificial intelligence; smart cities
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【DOI】 10.3390/math12213429
【影响因子】2.592
【主题类别】
--
【Abstract】IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】IOTA; tangle; Lyapunov optimization theory; rate control; effective width of tangle
【发表时间】2024
【收录时间】2024-11-18
【文献类型】
【DOI】 10.3390/math12213391
【Author】 Merdassi, Imen Ghazel, Cherif Saidane, Leila
【影响因子】2.557
【主题类别】
--
【Abstract】Location-based services (LBSs) rely on geographic information to offer location-based functionality to users, providing comfort to people's lives but also being accompanied by privacy leaks. Many of the central verification methods proposed in recent years are not satisfactory, as they pose a significant risk to the user's privacy. Blockchain technology provides a decentralized, distributed and manipulative solution, providing innovation in data sharing and management, as the technology is employed to enhance data privacy protection through various mechanisms, such as hashing and encryption secure transactions and protect user identities. In this paper, we propose a blockchain-based approach to secure location and time data privacy. We present a novel access control system that leverages location-based policies and multi-authority attributes. This approach allows users to remain anonymous while granting access based on their dynamic location and time. By combining multiple private chains, users' transaction records can be distributed, which can provide users with stronger on-site privacy protection without affecting service quality. Comparative simulation analysis with state-of-the-art methods using benchmark performance metrics shows that our proposed approach provides improved security, efficiency, and transparency. We use the real or random (ROR) model to verify the security of session keys and mutual authentication of the proposed approach. Finally, theoretical security analysis and informal and formal security verifications show that our approach is secure against multiple attacks. We use the Automated Validation of Internet Security Protocols and Applications (AVISPA) tool to simulate the resistance of the proposed approach to security attacks. Our evaluation is based on the use of the JPBC (Java Pairing-Based Cryptography) library. Furthermore, validation and performance discussion show that decrypting our approach is preferable.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Location; Attribute-based encryption; Time; Blockchain; AVISPA; JPBC
【发表时间】2025
【收录时间】2024-11-18
【文献类型】