5G technology has endowed mobile communication terminals with features such as ultrawideband access,low latency,and high reliability transmission,which can complete the network access and interconnection of a large nu...5G technology has endowed mobile communication terminals with features such as ultrawideband access,low latency,and high reliability transmission,which can complete the network access and interconnection of a large number of devices,thus realizing richer application scenarios and constructing 5G-enabled vehicular networks.However,due to the vulnerability of wireless communication,vehicle privacy and communication security have become the key problems to be solved in vehicular networks.Moreover,the large-scale communication in the vehicular networks also makes the higher communication efficiency an inevitable requirement.In order to achieve efficient and secure communication while protecting vehicle privacy,this paper proposes a lightweight key agreement and key update scheme for 5G vehicular networks based on blockchain.Firstly,the key agreement is accomplished using certificateless public key cryptography,and based on the aggregate signature and the cooperation between the vehicle and the trusted authority,an efficient key updating method is proposed,which reduces the overhead and protects the privacy of the vehicle while ensuring the communication security.Secondly,by introducing blockchain and using smart contracts to load the vehicle public key table for key management,this meets the requirements of vehicle traceability and can dynamically track and revoke misbehaving vehicles.Finally,the formal security proof under the eck security model and the informal security analysis is conducted,it turns out that our scheme is more secure than other authentication schemes in the vehicular networks.Performance analysis shows that our scheme has lower overhead than existing schemes in terms of communication and computation.展开更多
As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on vari...As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on various aspects of security,gaps remain in addressing both high security requirements and the resource-constrained nature of VANET environments.This paper proposes an extended-Kerberos protocol that integrates Physical Unclonable Function(PUF)for authentication and key agreement,offering a comprehensive solution to the security challenges in VANETs.The protocol facilitates mutual authentication and secure key agreement between vehicles and APPs,ensuring the confidentiality and integrity of vehicle-to-network(V2N)communications and preventing malicious data injection.Notably,by replacing traditional Kerberos password authentication with Challenge-Response Pairs(CRPs)generated by PUF,the protocol significantly reduces the risk of key leakage.The inherent properties of PUF—such as unclonability and unpredictability—make it an ideal defense against physical attacks,including intrusion,semi-intrusion,and side-channel attacks.The results of this study demonstrate that this approach not only enhances security but also optimizes communication efficiency,reduces latency,and improves overall user experience.The analysis proves that our protocol achieves at least 86%improvement in computational efficiency compared to some existed protocols.This is particularly crucial in resource-constrained VANET environments,where it enables efficient data transmission between vehicles and applications,reduces latency,and enhances the overall user experience.展开更多
With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehi...With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehicles are mobile entities,they move across different domains and need to communicate with the Roadside Unit(RSU)in various regions.However,open environments are highly susceptible to becoming targets for attackers,posing significant risks of malicious attacks.Therefore,it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs,particularly in scenarios where vehicles cross domains.In this paper,we propose a provably secure cross-domain authentication and key agreement protocol for IoV.Our protocol comprises two authentication phases:intra-domain authentication and cross-domain authentication.To ensure the security of our protocol,we conducted rigorous analyses based on the ROR(Real-or-Random)model and Scyther.Finally,we show in-depth comparisons of our protocol with existing ones from both security and performance perspectives,fully demonstrating its security and efficiency.展开更多
Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability ...Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability and accuracy. To address these challenges, this study introduces the K-GCN model, which integrates neighborhood k-shell distribution analysis with Graph Convolutional Network(GCN) technology to enhance key node identification in complex networks. The K-GCN model first leverages neighborhood k-shell distributions to calculate entropy values for each node, effectively quantifying node importance within the network. These entropy values are then used as key features within the GCN, which subsequently formulates intelligent strategies to maximize network connectivity disruption by removing a minimal set of nodes, thereby impacting the overall network architecture. Through iterative interactions with the environment, the GCN continuously refines its strategies, achieving precise identification of key nodes in the network. Unlike traditional methods, the K-GCN model not only captures local node features but also integrates the network structure and complex interrelations between neighboring nodes, significantly improving the accuracy and efficiency of key node identification.Experimental validation in multiple real-world network scenarios demonstrates that the K-GCN model outperforms existing methods.展开更多
With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibilit...With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibility of information leakage.In this paper,we propose a anti-quantum dynamic authenticated group key agreement scheme(AQDA-GKA)according to the ring-learning with errors(RLWE)problem,which is suitable for IoT environments.First,the proposed AQDA-GKA scheme can implement a group key agreement against quantum computing attacks by leveraging an RLWE-based key agreement mechanism.Second,this scheme can achieve dynamic node management,ensuring that any node can freely join or exit the current group.Third,we formally prove that the proposed scheme can resist quantum computing attacks as well as collusion attacks.Finally,the performance and security analysis reveals that the proposed AQDA-GKA scheme is secure and effective.展开更多
As the cornerstone of future information security,quantum key distribution(QKD)is evolving towards large-scale hybrid discrete-variable/continuous-variable(DV/CV)multi-domain quantum networks.Meanwhile,multicast-orien...As the cornerstone of future information security,quantum key distribution(QKD)is evolving towards large-scale hybrid discrete-variable/continuous-variable(DV/CV)multi-domain quantum networks.Meanwhile,multicast-oriented multi-party key negotiation is attracting increasing attention in quantum networks.However,the efficient key provision for multicast services over hybrid DV/CV multi-domain quantum networks remains challenging,due to the limited probability of service success and the inefficient utilization of key resources.Targeting these challenges,this study proposes two key-resource-aware multicast-oriented key provision strategies,namely the link distance-resource balanced key provision strategy and the maximum shared link key provision strategy.The proposed strategies are applicable to hybrid DV/CV multi-domain quantum networks,which are typically implemented by GG02-based intra-domain connections and BB84-based inter-domain connections.Furthermore,the multicast-oriented key provision model is formulated,based on which two heuristic algorithms are designed,i.e.,the shared link distance-resource(SLDR)dependent and the maximum shared link distance-resource(MSLDR)dependent multicast-oriented key provision algorithms.Simulation results verify the applicability of the designed algorithms across different multi-domain quantum networks,and demonstrate their superiority over the benchmark algorithms in terms of the success probability of multicast service requests,the number of shared links,and the key resource utilization.展开更多
Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problem...Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problems in the network can become more severe because each fiber link has limited resources(such as wavelengths and time slots).In addition,QKD optical networks are also affected by external disturbances such as data interception and eavesdropping,resulting in inefficient network communication.In this paper,we exploit the idea of protection path to enhance the anti-interference ability of QKD optical network.By introducing the concept of security metric,we propose a routing wavelength and time slot allocation algorithm(RWTA)based on protection path,which can lessen the blocking problem of QKD optical network.According to simulation analysis,the security-metric-based RWTA algorithm(SM-RWTA)proposed in this paper can substantially improve the success rate of security key(SK)update and significantly reduce the blocking rate of the network.It can also improve the utilization rate of resources such as wavelengths and time slots.Compared with the non-security-metric-based RWTA algorithm(NSM-RWTA),our algorithm is robust and can enhance the anti-interference ability and security of QKD optical networks.展开更多
As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is be...As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.展开更多
The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology play...The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in vehicle localization and navigation. Traditional Simultaneous Localization and Mapping (SLAM) systems are designed for use in static environments, and they can result in poor performance in terms of accuracy and robustness when used in dynamic environments where objects are in constant movement. To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2, MG-SLAM incorporates a dynamic target detection process that enables the detection of both known and unknown moving objects. In this process, a separate semantic segmentation thread is required to segment dynamic target instances, and the Mask R-CNN algorithm is applied on the Graphics Processing Unit (GPU) to accelerate segmentation. To reduce computational cost, only key frames are segmented to identify known dynamic objects. Additionally, a multi-view geometry method is adopted to detect unknown moving objects. The results demonstrate that MG-SLAM achieves higher precision, with an improvement from 0.2730 m to 0.0135 m in precision. Moreover, the processing time required by MG-SLAM is significantly reduced compared to other dynamic scene SLAM algorithms, which illustrates its efficacy in locating objects in dynamic scenes.展开更多
In today’s rapid widespread of digital technologies into all live aspects to enhance efficiency and productivity on the one hand and on the other hand ensure customer engagement, personal data counterfeiting has beco...In today’s rapid widespread of digital technologies into all live aspects to enhance efficiency and productivity on the one hand and on the other hand ensure customer engagement, personal data counterfeiting has become a major concern for businesses and end-users. One solution to ensure data security is encryption, where keys are central. There is therefore a need to find robusts key generation implementation that is effective, inexpensive and non-invasive for protecting and preventing data counterfeiting. In this paper, we use the theory of electromagnetic wave propagation to generate encryption keys.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in c...Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.展开更多
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The la...State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.展开更多
Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impair...Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.展开更多
A mode-pairing quantum key distribution based on heralded pair-coherent source with passive decoy-states is proposed,named HPCS-PDS-MP-QKD protocol,where the light sources at Alice and Bob sides are changed to heralde...A mode-pairing quantum key distribution based on heralded pair-coherent source with passive decoy-states is proposed,named HPCS-PDS-MP-QKD protocol,where the light sources at Alice and Bob sides are changed to heralded pair-coherent sources,and devices designed to implement passive decoy states are included at the transmitter sides to generate the decoy state pulses in the decoy-state window passively.With the defined efficient events and the designed pairing strategy,the key bits and bases can be obtained by data post-processing.Numerical simulation results verify the feasibility of the proposed protocol.The results show that the proposed protocol can exceed PLOB when the pairing interval setting is greater than 10^(3),and the transmission distance exceeds 200 km.When the key transmission distance reaches 300 km and the maximum pairing interval is equivalent to 1,its performance is improved by nearly 1.8 times compared to the original MP-QKD protocol with a weak coherent source(WCS-MP-QKD),and by 6.8 times higher than that of WCS-MPQKD with passive decoy states(WCS-PDS-MP-QKD).Meanwhile,the key transmission distance can reach 480 km,and surpasses the WCS-PDS-MP-QKD protocol by nearly 40 km.When the total pulse length is greater than 10^(11),the key generation rate is almost equal to that of infinite pulses.It is a promising QKD protocol that breaks the PLOB bound without requiring phase tracking and locking,has a longer transmission distance and a higher key generation rate,and eliminates the potential of side channel attack.展开更多
With the deepening cultural and economic ties between China and Italy,Chinese language education in Italy has been at the forefront of Europe,and significant progress has been made in localized teaching in Italy.Howev...With the deepening cultural and economic ties between China and Italy,Chinese language education in Italy has been at the forefront of Europe,and significant progress has been made in localized teaching in Italy.However,the current“Chinese language craze”in Italy seems to have cooled down,and the demand for Italians to learn Chinese has stabilized or even declined.This phenomenon involves multiple factors.From the perspective of cross-cultural perspective,this paper analyzes the current development status of Chinese language education in Italy,as well as the practical problems existing in various aspects such as teachers,textbooks,and curriculum settings.It explores the key factors for the better development of Chinese language education in Italy and provides suggestions on how to solve the current problems,aiming to promote the sound development of Chinese language education in Italy.展开更多
Quantum key distribution(QKD)is a method for secure communication that utilizes quantum mechanics principles to distribute cryptographic keys between parties.Integrated photonics offer benefits such as compactness,sca...Quantum key distribution(QKD)is a method for secure communication that utilizes quantum mechanics principles to distribute cryptographic keys between parties.Integrated photonics offer benefits such as compactness,scalability,energy efficiency and the potential for extensive integration.We have achieved BB84 phase encoding and decoding,time-bin phase QKD,and the coherent one-way(COW)protocol on a planar lightwave circuit(PLC)platform.At the optimal temperature,our chip successfully prepared quantum states,performed decoding and calculated the secure key rate of the time-bin phasedecoding QKD to be 80.46 kbps over a 20 km transmission with a quantum bit error rate(QBER)of 4.23%.The secure key rate of the COW protocol was 18.18 kbps,with a phase error rate of 3.627%and a time error rate of 0.377%.The uniqueness of this technology lies in its combination of high integration and protocol flexibility,providing an innovative solution for the development of future quantum communication networks.展开更多
Upgrading of abundant cellulosic biomass to isosorbide can reduce the dependence on limited fossil resources and provide a sustainable way to produce isosorbide,utilized for polymers,medicine and health care product s...Upgrading of abundant cellulosic biomass to isosorbide can reduce the dependence on limited fossil resources and provide a sustainable way to produce isosorbide,utilized for polymers,medicine and health care product synth-esis.This review comprehensively examines the key steps and catalytic systems involved in the conversion of cel-lulose to isosorbide.Initially,the reaction pathway from cellulose to isosorbide is elucidated,emphasizing three critical steps:cellulose hydrolysis,glucose hydrogenation,and the two-step dehydration of sorbitol to produce isosorbide.Additionally,the activation energy and acidic sites during cellulose hydrolysis,the impact of metal particle size and catalyst support on hydrogenation,and the effects of catalyst acidity,pore structure,and reaction conditions on sorbitol dehydration have been thoroughly examined.Finally,the progress made in cellulose con-version to isosorbide is summarized,current challenges are highlighted,and future development trends are pro-jected in this review.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 61941113,Grant 61971033,and Grant 61671057by the Henan Provincial Department of Science and Technology Project(No.212102210408)by the Henan Provincial Key Scientific Research Project(No.22A520041).
文摘5G technology has endowed mobile communication terminals with features such as ultrawideband access,low latency,and high reliability transmission,which can complete the network access and interconnection of a large number of devices,thus realizing richer application scenarios and constructing 5G-enabled vehicular networks.However,due to the vulnerability of wireless communication,vehicle privacy and communication security have become the key problems to be solved in vehicular networks.Moreover,the large-scale communication in the vehicular networks also makes the higher communication efficiency an inevitable requirement.In order to achieve efficient and secure communication while protecting vehicle privacy,this paper proposes a lightweight key agreement and key update scheme for 5G vehicular networks based on blockchain.Firstly,the key agreement is accomplished using certificateless public key cryptography,and based on the aggregate signature and the cooperation between the vehicle and the trusted authority,an efficient key updating method is proposed,which reduces the overhead and protects the privacy of the vehicle while ensuring the communication security.Secondly,by introducing blockchain and using smart contracts to load the vehicle public key table for key management,this meets the requirements of vehicle traceability and can dynamically track and revoke misbehaving vehicles.Finally,the formal security proof under the eck security model and the informal security analysis is conducted,it turns out that our scheme is more secure than other authentication schemes in the vehicular networks.Performance analysis shows that our scheme has lower overhead than existing schemes in terms of communication and computation.
基金supported in part by the Jiangsu“Qing Lan Project”,Natural Science Foundation of the Jiangsu Higher Education Institutions of China(Major Research Project:23KJA520007)Postgraduate Research&Practice Innovation Program of Jiangsu Province(No.SJCX25_1303).
文摘As the adoption of Vehicular Ad-hoc Networks(VANETs)grows,ensuring secure communication between smart vehicles and remote application servers(APPs)has become a critical challenge.While existing solutions focus on various aspects of security,gaps remain in addressing both high security requirements and the resource-constrained nature of VANET environments.This paper proposes an extended-Kerberos protocol that integrates Physical Unclonable Function(PUF)for authentication and key agreement,offering a comprehensive solution to the security challenges in VANETs.The protocol facilitates mutual authentication and secure key agreement between vehicles and APPs,ensuring the confidentiality and integrity of vehicle-to-network(V2N)communications and preventing malicious data injection.Notably,by replacing traditional Kerberos password authentication with Challenge-Response Pairs(CRPs)generated by PUF,the protocol significantly reduces the risk of key leakage.The inherent properties of PUF—such as unclonability and unpredictability—make it an ideal defense against physical attacks,including intrusion,semi-intrusion,and side-channel attacks.The results of this study demonstrate that this approach not only enhances security but also optimizes communication efficiency,reduces latency,and improves overall user experience.The analysis proves that our protocol achieves at least 86%improvement in computational efficiency compared to some existed protocols.This is particularly crucial in resource-constrained VANET environments,where it enables efficient data transmission between vehicles and applications,reduces latency,and enhances the overall user experience.
基金supported by the Startup Foundation for Introducing Talent of Nanjing University of Information Science and Technology and Natural Science Foundation of Shandong Province,China(Grant no.ZR202111230202).
文摘With the rapid development and widespread adoption of Internet of Things(IoT)technology,the innovative concept of the Internet of Vehicles(IoV)has emerged,ushering in a new era of intelligent transportation.Since vehicles are mobile entities,they move across different domains and need to communicate with the Roadside Unit(RSU)in various regions.However,open environments are highly susceptible to becoming targets for attackers,posing significant risks of malicious attacks.Therefore,it is crucial to design a secure authentication protocol to ensure the security of communication between vehicles and RSUs,particularly in scenarios where vehicles cross domains.In this paper,we propose a provably secure cross-domain authentication and key agreement protocol for IoV.Our protocol comprises two authentication phases:intra-domain authentication and cross-domain authentication.To ensure the security of our protocol,we conducted rigorous analyses based on the ROR(Real-or-Random)model and Scyther.Finally,we show in-depth comparisons of our protocol with existing ones from both security and performance perspectives,fully demonstrating its security and efficiency.
基金Supported by the National Natural Science Foundation of China(Grant No.12031002)。
文摘Accurately identifying key nodes is essential for evaluating network robustness and controlling information propagation in complex network analysis. However, current research methods face limitations in applicability and accuracy. To address these challenges, this study introduces the K-GCN model, which integrates neighborhood k-shell distribution analysis with Graph Convolutional Network(GCN) technology to enhance key node identification in complex networks. The K-GCN model first leverages neighborhood k-shell distributions to calculate entropy values for each node, effectively quantifying node importance within the network. These entropy values are then used as key features within the GCN, which subsequently formulates intelligent strategies to maximize network connectivity disruption by removing a minimal set of nodes, thereby impacting the overall network architecture. Through iterative interactions with the environment, the GCN continuously refines its strategies, achieving precise identification of key nodes in the network. Unlike traditional methods, the K-GCN model not only captures local node features but also integrates the network structure and complex interrelations between neighboring nodes, significantly improving the accuracy and efficiency of key node identification.Experimental validation in multiple real-world network scenarios demonstrates that the K-GCN model outperforms existing methods.
基金Supported by the National Engineering Research Center of Classified Protection and Safeguard Technology for Cybersecurity(No.C23640-XD-07)the Open Foundation of Key Laboratory of Cyberspace Security of Ministry of Education of China and Henan Key Laboratory of Network Cryptography(No.KLCS20240301)。
文摘With the recent advances in quantum computing,the key agreement algorithm based on traditional cryptography theory,which is applied to the Internet of Things(IoT)scenario,will no longer be secure due to the possibility of information leakage.In this paper,we propose a anti-quantum dynamic authenticated group key agreement scheme(AQDA-GKA)according to the ring-learning with errors(RLWE)problem,which is suitable for IoT environments.First,the proposed AQDA-GKA scheme can implement a group key agreement against quantum computing attacks by leveraging an RLWE-based key agreement mechanism.Second,this scheme can achieve dynamic node management,ensuring that any node can freely join or exit the current group.Third,we formally prove that the proposed scheme can resist quantum computing attacks as well as collusion attacks.Finally,the performance and security analysis reveals that the proposed AQDA-GKA scheme is secure and effective.
基金supported by the National Natural Science Foundation of China(Grant Nos.62201276,62350001,U22B2026,and 62425105)the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300701)the Key R&D Program(Industry Foresight and Key Core Technologies)of Jiangsu Province(Grant No.BE2022071)。
文摘As the cornerstone of future information security,quantum key distribution(QKD)is evolving towards large-scale hybrid discrete-variable/continuous-variable(DV/CV)multi-domain quantum networks.Meanwhile,multicast-oriented multi-party key negotiation is attracting increasing attention in quantum networks.However,the efficient key provision for multicast services over hybrid DV/CV multi-domain quantum networks remains challenging,due to the limited probability of service success and the inefficient utilization of key resources.Targeting these challenges,this study proposes two key-resource-aware multicast-oriented key provision strategies,namely the link distance-resource balanced key provision strategy and the maximum shared link key provision strategy.The proposed strategies are applicable to hybrid DV/CV multi-domain quantum networks,which are typically implemented by GG02-based intra-domain connections and BB84-based inter-domain connections.Furthermore,the multicast-oriented key provision model is formulated,based on which two heuristic algorithms are designed,i.e.,the shared link distance-resource(SLDR)dependent and the maximum shared link distance-resource(MSLDR)dependent multicast-oriented key provision algorithms.Simulation results verify the applicability of the designed algorithms across different multi-domain quantum networks,and demonstrate their superiority over the benchmark algorithms in terms of the success probability of multicast service requests,the number of shared links,and the key resource utilization.
基金funded by Youth Program of Shaanxi Provincial Department of Science and Technology(Grant No.2024JC-YBQN-0630)。
文摘Quantum key distribution(QKD)optical networks can provide more secure communications.However,with the increase of the QKD path requests and key updates,network blocking problems will become severe.The blocking problems in the network can become more severe because each fiber link has limited resources(such as wavelengths and time slots).In addition,QKD optical networks are also affected by external disturbances such as data interception and eavesdropping,resulting in inefficient network communication.In this paper,we exploit the idea of protection path to enhance the anti-interference ability of QKD optical network.By introducing the concept of security metric,we propose a routing wavelength and time slot allocation algorithm(RWTA)based on protection path,which can lessen the blocking problem of QKD optical network.According to simulation analysis,the security-metric-based RWTA algorithm(SM-RWTA)proposed in this paper can substantially improve the success rate of security key(SK)update and significantly reduce the blocking rate of the network.It can also improve the utilization rate of resources such as wavelengths and time slots.Compared with the non-security-metric-based RWTA algorithm(NSM-RWTA),our algorithm is robust and can enhance the anti-interference ability and security of QKD optical networks.
基金Scientific Research Project of Liaoning Province Education Department,Code:LJKQZ20222457&LJKMZ20220781Liaoning Province Nature Fund Project,Code:No.2022-MS-291.
文摘As industrialization and informatization becomemore deeply intertwined,industrial control networks have entered an era of intelligence.The connection between industrial control networks and the external internet is becoming increasingly close,which leads to frequent security accidents.This paper proposes a model for the industrial control network.It includes a malware containment strategy that integrates intrusion detection,quarantine,and monitoring.Basedonthismodel,the role of keynodes in the spreadofmalware is studied,a comparisonexperiment is conducted to validate the impact of the containment strategy.In addition,the dynamic behavior of the model is analyzed,the basic reproduction number is computed,and the disease-free and endemic equilibrium of the model is also obtained by the basic reproduction number.Moreover,through simulation experiments,the effectiveness of the containment strategy is validated,the influence of the relevant parameters is analyzed,and the containment strategy is optimized.In otherwords,selective immunity to key nodes can effectively suppress the spread ofmalware andmaintain the stability of industrial control systems.The earlier the immunization of key nodes,the better.Once the time exceeds the threshold,immunizing key nodes is almost ineffective.The analysis provides a better way to contain the malware in the industrial control network.
基金funded by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China(grant number 22KJD440001)Changzhou Science&Technology Program(grant number CJ20220232).
文摘The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in vehicle localization and navigation. Traditional Simultaneous Localization and Mapping (SLAM) systems are designed for use in static environments, and they can result in poor performance in terms of accuracy and robustness when used in dynamic environments where objects are in constant movement. To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2, MG-SLAM incorporates a dynamic target detection process that enables the detection of both known and unknown moving objects. In this process, a separate semantic segmentation thread is required to segment dynamic target instances, and the Mask R-CNN algorithm is applied on the Graphics Processing Unit (GPU) to accelerate segmentation. To reduce computational cost, only key frames are segmented to identify known dynamic objects. Additionally, a multi-view geometry method is adopted to detect unknown moving objects. The results demonstrate that MG-SLAM achieves higher precision, with an improvement from 0.2730 m to 0.0135 m in precision. Moreover, the processing time required by MG-SLAM is significantly reduced compared to other dynamic scene SLAM algorithms, which illustrates its efficacy in locating objects in dynamic scenes.
文摘In today’s rapid widespread of digital technologies into all live aspects to enhance efficiency and productivity on the one hand and on the other hand ensure customer engagement, personal data counterfeiting has become a major concern for businesses and end-users. One solution to ensure data security is encryption, where keys are central. There is therefore a need to find robusts key generation implementation that is effective, inexpensive and non-invasive for protecting and preventing data counterfeiting. In this paper, we use the theory of electromagnetic wave propagation to generate encryption keys.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
基金supported by the National Key R&D Program of China [grant number 2023YFF0805202]the National Natural Science Foun-dation of China [grant number 42175045]the Strategic Priority Research Program of the Chinese Academy of Sciences [grant number XDB42000000]。
文摘Atlantic Meridional Overturning Circulation(AMOC)plays a central role in long-term climate variations through its heat and freshwater transports,which can collapse under a rapid increase of greenhouse gas forcing in climate models.Previous studies have suggested that the deviation of model parameters is one of the major factors in inducing inaccurate AMOC simulations.In this work,with a low-resolution earth system model,the authors try to explore whether a reasonable adjustment of the key model parameter can help to re-establish the AMOC after its collapse.Through a new optimization strategy,the extra freshwater flux(FWF)parameter is determined to be the dominant one affecting the AMOC’s variability.The traditional ensemble optimal interpolation(EnOI)data assimilation and new machine learning methods are adopted to optimize the FWF parameter in an abrupt 4×CO_(2) forcing experiment to improve the adaptability of model parameters and accelerate the recovery of AMOC.The results show that,under an abrupt 4×CO_(2) forcing in millennial simulations,the AMOC will first collapse and then re-establish by the default FWF parameter slowly.However,during the parameter adjustment process,the saltier and colder sea water over the North Atlantic region are the dominant factors in usefully improving the adaptability of the FWF parameter and accelerating the recovery of AMOC,according to their physical relationship with FWF on the interdecadal timescale.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.
文摘State Key Laboratory of Baiyun Obo Rare Earth Resource Researches and Comprehensive Utilization was approved by the Ministry of Science and Technology to be one of the national key laboratories in November 2022.The laboratory was reconstructed based on former State Key Laboratory of Baiyun Obo Rare Earth Resources Researches and Comprehensive Utilization.
基金supported by the National Natural Science Foundation of China(Grant Nos.42277161,42230709).
文摘Accurate identification and effective support of key blocks are crucial for ensuring the stability and safety of rock slopes.The number of structural planes and rock blocks were reduced in previous studies.This impairs the ability to characterize complex rock slopes accurately and inhibits the identification of key blocks.In this paper,a knowledge-data dually driven paradigm for accurate identification of key blocks in complex rock slopes is proposed.Our basic idea is to integrate key block theory into data-driven models based on finely characterizing structural features to identify key blocks in complex rock slopes accurately.The proposed novel paradigm consists of(1)representing rock slopes as graph-structured data based on complex systems theory,(2)identifying key nodes in the graph-structured data using graph deep learning,and(3)mapping the key nodes of graph-structured data to corresponding key blocks in the rock slope.Verification experiments and real-case applications are conducted by the proposed method.The verification results demonstrate excellent model performance,strong generalization capability,and effective classification results.Moreover,the real case application is conducted on the northern slope of the Yanqianshan Iron Mine.The results show that the proposed method can accurately identify key blocks in complex rock slopes,which can provide a decision-making basis and rational recommendations for effective support and instability prevention of rock slopes,thereby ensuring the stability of rock engineering and the safety of life and property.
基金Project supported by the National Natural Science Foundation of China(Grant No.62375140)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(Grant No.KYCX241191 and SJCX250315)the Open Research Fund of the National Laboratory of Solid State Microstructures(Grant No.M36055)。
文摘A mode-pairing quantum key distribution based on heralded pair-coherent source with passive decoy-states is proposed,named HPCS-PDS-MP-QKD protocol,where the light sources at Alice and Bob sides are changed to heralded pair-coherent sources,and devices designed to implement passive decoy states are included at the transmitter sides to generate the decoy state pulses in the decoy-state window passively.With the defined efficient events and the designed pairing strategy,the key bits and bases can be obtained by data post-processing.Numerical simulation results verify the feasibility of the proposed protocol.The results show that the proposed protocol can exceed PLOB when the pairing interval setting is greater than 10^(3),and the transmission distance exceeds 200 km.When the key transmission distance reaches 300 km and the maximum pairing interval is equivalent to 1,its performance is improved by nearly 1.8 times compared to the original MP-QKD protocol with a weak coherent source(WCS-MP-QKD),and by 6.8 times higher than that of WCS-MPQKD with passive decoy states(WCS-PDS-MP-QKD).Meanwhile,the key transmission distance can reach 480 km,and surpasses the WCS-PDS-MP-QKD protocol by nearly 40 km.When the total pulse length is greater than 10^(11),the key generation rate is almost equal to that of infinite pulses.It is a promising QKD protocol that breaks the PLOB bound without requiring phase tracking and locking,has a longer transmission distance and a higher key generation rate,and eliminates the potential of side channel attack.
文摘With the deepening cultural and economic ties between China and Italy,Chinese language education in Italy has been at the forefront of Europe,and significant progress has been made in localized teaching in Italy.However,the current“Chinese language craze”in Italy seems to have cooled down,and the demand for Italians to learn Chinese has stabilized or even declined.This phenomenon involves multiple factors.From the perspective of cross-cultural perspective,this paper analyzes the current development status of Chinese language education in Italy,as well as the practical problems existing in various aspects such as teachers,textbooks,and curriculum settings.It explores the key factors for the better development of Chinese language education in Italy and provides suggestions on how to solve the current problems,aiming to promote the sound development of Chinese language education in Italy.
基金supported by the Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300701)the National Key Research and Development Program of China(Grant No.2018YFA0306403)the Strategic Priority Research Program of Chinese Academy of Sciences(Grant No.XDB43000000).
文摘Quantum key distribution(QKD)is a method for secure communication that utilizes quantum mechanics principles to distribute cryptographic keys between parties.Integrated photonics offer benefits such as compactness,scalability,energy efficiency and the potential for extensive integration.We have achieved BB84 phase encoding and decoding,time-bin phase QKD,and the coherent one-way(COW)protocol on a planar lightwave circuit(PLC)platform.At the optimal temperature,our chip successfully prepared quantum states,performed decoding and calculated the secure key rate of the time-bin phasedecoding QKD to be 80.46 kbps over a 20 km transmission with a quantum bit error rate(QBER)of 4.23%.The secure key rate of the COW protocol was 18.18 kbps,with a phase error rate of 3.627%and a time error rate of 0.377%.The uniqueness of this technology lies in its combination of high integration and protocol flexibility,providing an innovative solution for the development of future quantum communication networks.
文摘Upgrading of abundant cellulosic biomass to isosorbide can reduce the dependence on limited fossil resources and provide a sustainable way to produce isosorbide,utilized for polymers,medicine and health care product synth-esis.This review comprehensively examines the key steps and catalytic systems involved in the conversion of cel-lulose to isosorbide.Initially,the reaction pathway from cellulose to isosorbide is elucidated,emphasizing three critical steps:cellulose hydrolysis,glucose hydrogenation,and the two-step dehydration of sorbitol to produce isosorbide.Additionally,the activation energy and acidic sites during cellulose hydrolysis,the impact of metal particle size and catalyst support on hydrogenation,and the effects of catalyst acidity,pore structure,and reaction conditions on sorbitol dehydration have been thoroughly examined.Finally,the progress made in cellulose con-version to isosorbide is summarized,current challenges are highlighted,and future development trends are pro-jected in this review.
