Based on trust measurement, a new cross-domain access control model is proposed to improve the security performance of the cross-domain access control processes. This model integrates the trust management and trusted ...Based on trust measurement, a new cross-domain access control model is proposed to improve the security performance of the cross-domain access control processes. This model integrates the trust management and trusted platform measurement, defines several concepts （user trust degree, platform configuration integrity and intra/inter-domain trust degree） and calculates them with users＇ uniform identity authentication and historical access behavior analysis. Then this model expands the extensible access control markup language （XACML） model by adding inside trust manager point （ITMP） and outside trust manager point （OTMP）, and describes the architectures and workflows of ITMP and OTMP in details. The experimental results show that this model can achieve more fine-grained access control, implement dynamic authorization in a simple way, and improve the security degrees of the cross-domain access control.展开更多
Data trading enables data owners and data requesters to sell and purchase data.With the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of attention.Particularly...Data trading enables data owners and data requesters to sell and purchase data.With the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of attention.Particularly,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform.Moreover,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace.In the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple domains.In this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading systems.We consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud provider.The proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic techniques.In the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature scheme.Therefore,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each other.To demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.展开更多
Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)...Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.展开更多
With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have i...With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have increased dramatically,especially for providing airborne Internet services.However,due to dynamic service demands and onboard LEO resources over time and space,it poses huge challenges in satellite-aircraft access and service management in ultra-dense LEO satellite networks(UDLSN).In this paper,we propose a deep reinforcement learning-based approach for ultra-dense LEO satellite-aircraft access and service management.Firstly,we develop an airborne Internet architecture based on UDLSN and design a management mechanism including medium earth orbit satellites to guarantee lightweight management.Secondly,considering latency-sensitive and latency-tolerant services,we formulate the problem of satellite-aircraft access and service management for civil aviation to ensure service continuity.Finally,we propose a proximal policy optimization-based access and service management algorithm to solve the formulated problem.Simulation results demonstrate the convergence and effectiveness of the proposed algorithm with satisfying the service continuity when applying to the UDLSN.展开更多
Background:People working outdoors in the Map Ta Phut pollution control area of Thailand require comprehen-sive health monitoring.In the past,studies have been done on the health effects of pollutants.However,there ar...Background:People working outdoors in the Map Ta Phut pollution control area of Thailand require comprehen-sive health monitoring.In the past,studies have been done on the health effects of pollutants.However,there are few studies on musculoskeletal disorders(MSDs),and Thailand is struggling to meet the Sustainable Development Goals.Methods:This cross-sectional study examines access to health services and factors affecting MSDs among outdoor pollution workers(OPWs).The sample group includes OPWs,including local fisherman,street vendors,public car drivers,and traffic police.We studied 50 people from each of these groups,for a total of 200 people.Data were analyzed with inferential statistics using Chi-square test,McNemar test,and Univariate logistic regression.Results:The OPWs reported experiencing significantly more total MSDs pain than they did in the past(P<0.05).Factors affecting current MSDs pain,including occupation and working days per week,were significant(P<0.05).The street vendor group and public car driver group had(odds ratio[OR]=2.253,95%confidence interval[CI]:1.101 to 5.019)and(OR=2.681,95%CI:1.191 to 6.032)times higher risks of MSDs pain,respectively.OPWs who work>5 days per week had a(OR=1.464,95%CI:1.093 to 2.704)times higher risk of MSDs pain.52.7%of OPWs with MSDs,pain(n=110)had received an annual health check-up.In the past year,50.9%had minor illnesses and 21.8%had severe illnesses.OPWs receiving free treatment and visiting health service stations for no cost comprised 77.3%and 51.8%,respectively.60.9%used their right to receive treatment with universal health insurance cards.Conclusions:The study indicates that occupational groups with MSDs pain problems should exercise this right,according to the worker protection law.Local health agencies should organize activities or create accessible media to promote preventive medicine services,as many OPWs believe that health services can only be accessed when illness occurs.展开更多
Renewable Energy Systems(RES)provide a sustainable solution to climate warming and environmental pollution by enhancing stability and reliability through status acquisition and analysis on cloud platforms and intellig...Renewable Energy Systems(RES)provide a sustainable solution to climate warming and environmental pollution by enhancing stability and reliability through status acquisition and analysis on cloud platforms and intelligent processing on edge servers(ES).However,securely distributing encrypted data stored in the cloud to terminals that meet decryption requirements has become a prominent research topic.Additionally,managing attributes,including addition,deletion,and modification,is a crucial issue in the access control scheme for RES.To address these security concerns,a trust-based ciphertext-policy attribute-based encryption(CP-ABE)device access control scheme is proposed for RES(TB-CP-ABE).This scheme effectivelymanages the distribution and control of encrypted data on the cloud through robust attribute key management.By introducing trust management mechanisms and outsourced decryption technology,the ES system can effectively assess and manage the trust worthiness of terminal devices,ensuring that only trusted devices can participate in data exchange and access sensitive information.Besides,the ES system dynamically evaluates trust scores to set decryption trust thresholds,thereby regulating device data access permissions and enhancing the system’s security.To validate the security of the proposed TB-CP-ABE against chosen plaintext attacks,a comprehensive formal security analysis is conducted using the widely accepted random oraclemodel under the decisional q-Bilinear Diffie-Hellman Exponent(q-BDHE)assumption.Finally,comparative analysis with other schemes demonstrates that the TB-CP-ABE scheme cuts energy/communication costs by 43%,and scaleswell with rising terminals,maintaining average latency below 50ms,ensuring real-time service feasibility.The proposed scheme not only provides newinsights for the secure management of RES but also lays a foundation for future secure energy solutions.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
Emotion recognition plays a crucial role in various fields and is a key task in natural language processing (NLP). The objective is to identify and interpret emotional expressions in text. However, traditional emotion...Emotion recognition plays a crucial role in various fields and is a key task in natural language processing (NLP). The objective is to identify and interpret emotional expressions in text. However, traditional emotion recognition approaches often struggle in few-shot cross-domain scenarios due to their limited capacity to generalize semantic features across different domains. Additionally, these methods face challenges in accurately capturing complex emotional states, particularly those that are subtle or implicit. To overcome these limitations, we introduce a novel approach called Dual-Task Contrastive Meta-Learning (DTCML). This method combines meta-learning and contrastive learning to improve emotion recognition. Meta-learning enhances the model’s ability to generalize to new emotional tasks, while instance contrastive learning further refines the model by distinguishing unique features within each category, enabling it to better differentiate complex emotional expressions. Prototype contrastive learning, in turn, helps the model address the semantic complexity of emotions across different domains, enabling the model to learn fine-grained emotions expression. By leveraging dual tasks, DTCML learns from two domains simultaneously, the model is encouraged to learn more diverse and generalizable emotions features, thereby improving its cross-domain adaptability and robustness, and enhancing its generalization ability. We evaluated the performance of DTCML across four cross-domain settings, and the results show that our method outperforms the best baseline by 5.88%, 12.04%, 8.49%, and 8.40% in terms of accuracy.展开更多
Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition d...Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.展开更多
Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current so...Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.展开更多
To facilitate cross-domain data interaction in the Industrial Internet of Things(IIoT),establishing trust between multiple administrative domains is essential.Although blockchain technology has been proposed as a solu...To facilitate cross-domain data interaction in the Industrial Internet of Things(IIoT),establishing trust between multiple administrative domains is essential.Although blockchain technology has been proposed as a solution,current techniques still suffer from issues related to efficiency,security,and privacy.Our research aims to address these challenges by proposing a lightweight,trusted data interaction scheme based on blockchain,which reduces redundant interactions among entities.We enhance the traditional Practical Byzantine Fault Tolerance(PBFT)algorithm to support lightweight distributed consensus in large-scale IIoT scenarios.Introducing a composite digital signature algorithm and incorporating veto power minimizes resource consumption and eliminates ineffective consensus operations.The experimental results show that,compared with PBFT,our scheme reduces latency by 27.2%,thereby improving communication efficiency and resource utilization.Furthermore,we develop a lightweight authentication technique specifically for cross-domain IIoT,leveraging blockchain technology to achieve distributed collaborative authentication.The performance comparisons indicate that our method significantly outperforms traditional schemes,with an average authentication latency of approximately 151 milliseconds.Additionally,we introduce a trusted federated learning(FL)algorithm that ensures comprehensive trust assessments for devices across different domains while protecting data privacy.Extensive simulations and experiments validate the reliability of our approach.展开更多
The lack of facial features caused by wearing masks degrades the performance of facial recognition systems.Traditional occluded face recognition methods cannot integrate the computational resources of the edge layer a...The lack of facial features caused by wearing masks degrades the performance of facial recognition systems.Traditional occluded face recognition methods cannot integrate the computational resources of the edge layer and the device layer.Besides,previous research fails to consider the facial characteristics including occluded and unoccluded parts.To solve the above problems,we put forward a device-edge collaborative occluded face recognition method based on cross-domain feature fusion.Specifically,the device-edge collaborative face recognition architecture gets the utmost out of maximizes device and edge resources for real-time occluded face recognition.Then,a cross-domain facial feature fusion method is presented which combines both the explicit domain and the implicit domain facial.Furthermore,a delay-optimized edge recognition task scheduling method is developed that comprehensively considers the task load,computational power,bandwidth,and delay tolerance constraints of the edge.This method can dynamically schedule face recognition tasks and minimize recognition delay while ensuring recognition accuracy.The experimental results show that the proposed method achieves an average gain of about 21%in recognition latency,while the accuracy of the face recognition task is basically the same compared to the baseline method.展开更多
Although significant progress has been made in micro-expression recognition,effectively modeling the intricate spatial-temporal dynamics remains a persistent challenge owing to their brief duration and complex facial ...Although significant progress has been made in micro-expression recognition,effectively modeling the intricate spatial-temporal dynamics remains a persistent challenge owing to their brief duration and complex facial dynamics.Furthermore,existing methods often suffer from limited gen-eralization,as they primarily focus on single-dataset tasks with small sample sizes.To address these two issues,this paper proposes the cross-domain spatial-temporal graph convolutional network(GCN)(CDST-GCN)model,which comprises two primary components:a siamese attention spa-tial-temporal branch(SASTB)and a global-aware dynamic spatial-temporal branch(GDSTB).Specifically,SASTB utilizes a contrastive learning strategy to project macro-and micro-expressions into a shared,aligned feature space,actively addressing cross-domain discrepancies.Additionally,it integrates an attention-gated mechanism that generates adaptive adjacency matrices to flexibly model collaborative patterns among facial landmarks.While largely preserving the structural paradigm of SASTB,GDSTB enhances the feature representation by integrating global context extracted from a pretrained model.Through this dual-branch architecture,CDST-GCN success-fully models both the global and local spatial-temporal features.The experimental results on CASME II and SAMM datasets demonstrate that the proposed model achieves competitive perfor-mance.Especially in more challenging 5-class tasks,the accuracy of the model on CASME II dataset is as high as 80.5%.展开更多
High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication sys...High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication systems,an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed,that is,the Preamble Slice Orderly Queue Access(PSOQA)scheme.In this scheme,the preamble arrangement is combined with the access control.The preamble arrangement is realized by preamble slices which is from the virtual preamble pool.The access devices learn to queue orderly by deep reinforcement learning.The orderly queue weakens the random and avoids collision.A preamble slice is assigned to an orderly access queue at each access time.The orderly queue is determined by interaction information among multiple agents.With the federated reinforcement learning framework,the PSOQA scheme is implemented to guarantee the privacy and security of agents.Finally,the access performance of PSOQA is compared with other random contention schemes in different load scenarios.Simulation results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.展开更多
The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sens...The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point.In order to enhance the sensing quality for the remote uploading,the passive reflection surface technique is employed.If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks,he may receive the same image from this sensor.Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images.In order to achieve this goal,the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients.Based on this theoretical result,the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor.Finally,the analytical expression is theoretically derived for the optimum uploading power.Numerical simulations verify the design approach.展开更多
基金Supported by the National Key Technology Support Program of China(2013BAK07B04)the Natural Science Foundation of Hebei Province(F2014201152)
文摘Based on trust measurement, a new cross-domain access control model is proposed to improve the security performance of the cross-domain access control processes. This model integrates the trust management and trusted platform measurement, defines several concepts （user trust degree, platform configuration integrity and intra/inter-domain trust degree） and calculates them with users＇ uniform identity authentication and historical access behavior analysis. Then this model expands the extensible access control markup language （XACML） model by adding inside trust manager point （ITMP） and outside trust manager point （OTMP）, and describes the architectures and workflows of ITMP and OTMP in details. The experimental results show that this model can achieve more fine-grained access control, implement dynamic authorization in a simple way, and improve the security degrees of the cross-domain access control.
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2022R1I1A3063257)supported by the MSIT(Ministry of Science and ICT),Korea,under the Special R&D Zone Development Project(R&D)—Development of R&D Innovation Valley Support Program(2023-DD-RD-0152)supervised by the Innovation Foundation.
文摘Data trading enables data owners and data requesters to sell and purchase data.With the emergence of blockchain technology,research on blockchain-based data trading systems is receiving a lot of attention.Particularly,to reduce the on-chain storage cost,a novel paradigm of blockchain and cloud fusion has been widely considered as a promising data trading platform.Moreover,the fact that data can be used for commercial purposes will encourage users and organizations from various fields to participate in the data marketplace.In the data marketplace,it is a challenge how to trade the data securely outsourced to the external cloud in a way that restricts access to the data only to authorized users across multiple domains.In this paper,we propose a cross-domain bilateral access control protocol for blockchain-cloud based data trading systems.We consider a system model that consists of domain authorities,data senders,data receivers,a blockchain layer,and a cloud provider.The proposed protocol enables access control and source identification of the outsourced data by leveraging identity-based cryptographic techniques.In the proposed protocol,the outsourced data of the sender is encrypted under the target receiver’s identity,and the cloud provider performs policy-match verification on the authorization tags of the sender and receiver generated by the identity-based signature scheme.Therefore,data trading can be achieved only if the identities of the data sender and receiver simultaneously meet the policies specified by each other.To demonstrate efficiency,we evaluate the performance of the proposed protocol and compare it with existing studies.
文摘Purpose:For a set of 1,561 Open Access(OA)and non-OA journals in business and economics,this study evaluates the relationships between four citation metrics-five-year Impact Factor(5IF),CiteScore,Article Influence(AI)score,and SCImago Journal Rank(SJR)-and the journal ratings assigned by expert reviewers.We expect that the OA journals will have especially high citation impact relative to their perceived quality(reputation).Design/methodology/approach:Regression is used to estimate the ratings assigned by expert reviewers for the 2021 CABS(Chartered Association of Business Schools)journal assessment exercise.The independent variables are the four citation metrics,evaluated separately,and a dummy variable representing the OA/non-OA status of each journal.Findings:Regardless of the citation metric used,OA journals in business and economics have especially high citation impact relative to their perceived quality(reputation).That is,they have especially low perceived quality(reputation)relative to their citation impact.Research limitations:These results are specific to the CABS journal ratings and the four citation metrics.However,there is strong evidence that CABS is closely related to several other expert ratings,and that 5IF,CiteScore,AI,and SJR are representative of the other citation metrics that might have been chosen.Practical implications:There are at least two possible explanations for these results:(1)expert evaluators are biased against OA journals,and(2)OA journals have especially high citation impact due to their increased accessibility.Although this study does not allow us to determine which of these explanations are supported,the results suggest that authors should consider publishing in OA journals whenever overall readership and citation impact are more important than journal reputation within a particular field.Moreover,the OA coefficients provide a useful indicator of the extent to which anti-OA bias(or the citation advantage of OA journals)is diminishing over time.Originality/value:This is apparently the first study to investigate the impact of OA status on the relationships between expert journal ratings and journal citation metrics.
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1806104in part by Innovation and Entrepreneurship of Jiangsu Province High-level Talent Program+1 种基金in part by Natural Sciences and Engineering Research Council of Canada (NSERC)the support from Huawei
文摘With the deployment of ultra-dense low earth orbit(LEO)satellite constellations,LEO satellite access network(LEO-SAN)is envisioned to achieve global Internet coverage.Meanwhile,the civil aviation communications have increased dramatically,especially for providing airborne Internet services.However,due to dynamic service demands and onboard LEO resources over time and space,it poses huge challenges in satellite-aircraft access and service management in ultra-dense LEO satellite networks(UDLSN).In this paper,we propose a deep reinforcement learning-based approach for ultra-dense LEO satellite-aircraft access and service management.Firstly,we develop an airborne Internet architecture based on UDLSN and design a management mechanism including medium earth orbit satellites to guarantee lightweight management.Secondly,considering latency-sensitive and latency-tolerant services,we formulate the problem of satellite-aircraft access and service management for civil aviation to ensure service continuity.Finally,we propose a proximal policy optimization-based access and service management algorithm to solve the formulated problem.Simulation results demonstrate the convergence and effectiveness of the proposed algorithm with satisfying the service continuity when applying to the UDLSN.
基金grant Fundamental Fund of National Science Research and Innovation Fund(NSRF)via Burapha University of Thailand(Grant number 52/2024).
文摘Background:People working outdoors in the Map Ta Phut pollution control area of Thailand require comprehen-sive health monitoring.In the past,studies have been done on the health effects of pollutants.However,there are few studies on musculoskeletal disorders(MSDs),and Thailand is struggling to meet the Sustainable Development Goals.Methods:This cross-sectional study examines access to health services and factors affecting MSDs among outdoor pollution workers(OPWs).The sample group includes OPWs,including local fisherman,street vendors,public car drivers,and traffic police.We studied 50 people from each of these groups,for a total of 200 people.Data were analyzed with inferential statistics using Chi-square test,McNemar test,and Univariate logistic regression.Results:The OPWs reported experiencing significantly more total MSDs pain than they did in the past(P<0.05).Factors affecting current MSDs pain,including occupation and working days per week,were significant(P<0.05).The street vendor group and public car driver group had(odds ratio[OR]=2.253,95%confidence interval[CI]:1.101 to 5.019)and(OR=2.681,95%CI:1.191 to 6.032)times higher risks of MSDs pain,respectively.OPWs who work>5 days per week had a(OR=1.464,95%CI:1.093 to 2.704)times higher risk of MSDs pain.52.7%of OPWs with MSDs,pain(n=110)had received an annual health check-up.In the past year,50.9%had minor illnesses and 21.8%had severe illnesses.OPWs receiving free treatment and visiting health service stations for no cost comprised 77.3%and 51.8%,respectively.60.9%used their right to receive treatment with universal health insurance cards.Conclusions:The study indicates that occupational groups with MSDs pain problems should exercise this right,according to the worker protection law.Local health agencies should organize activities or create accessible media to promote preventive medicine services,as many OPWs believe that health services can only be accessed when illness occurs.
基金supported by the Science and Technology Project of the State Grid Corporation of China,Grant number 5700-202223189A-1-1-ZN.
文摘Renewable Energy Systems(RES)provide a sustainable solution to climate warming and environmental pollution by enhancing stability and reliability through status acquisition and analysis on cloud platforms and intelligent processing on edge servers(ES).However,securely distributing encrypted data stored in the cloud to terminals that meet decryption requirements has become a prominent research topic.Additionally,managing attributes,including addition,deletion,and modification,is a crucial issue in the access control scheme for RES.To address these security concerns,a trust-based ciphertext-policy attribute-based encryption(CP-ABE)device access control scheme is proposed for RES(TB-CP-ABE).This scheme effectivelymanages the distribution and control of encrypted data on the cloud through robust attribute key management.By introducing trust management mechanisms and outsourced decryption technology,the ES system can effectively assess and manage the trust worthiness of terminal devices,ensuring that only trusted devices can participate in data exchange and access sensitive information.Besides,the ES system dynamically evaluates trust scores to set decryption trust thresholds,thereby regulating device data access permissions and enhancing the system’s security.To validate the security of the proposed TB-CP-ABE against chosen plaintext attacks,a comprehensive formal security analysis is conducted using the widely accepted random oraclemodel under the decisional q-Bilinear Diffie-Hellman Exponent(q-BDHE)assumption.Finally,comparative analysis with other schemes demonstrates that the TB-CP-ABE scheme cuts energy/communication costs by 43%,and scaleswell with rising terminals,maintaining average latency below 50ms,ensuring real-time service feasibility.The proposed scheme not only provides newinsights for the secure management of RES but also lays a foundation for future secure energy solutions.
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 ScientificResearch and Innovation Team Program of Sichuan University of Science and Technology(No.SUSE652A006)Sichuan Key Provincial Research Base of Intelligent Tourism(ZHYJ22-03)In addition,it is also listed as a project of Sichuan Provincial Science and Technology Programme(2022YFG0028).
文摘Emotion recognition plays a crucial role in various fields and is a key task in natural language processing (NLP). The objective is to identify and interpret emotional expressions in text. However, traditional emotion recognition approaches often struggle in few-shot cross-domain scenarios due to their limited capacity to generalize semantic features across different domains. Additionally, these methods face challenges in accurately capturing complex emotional states, particularly those that are subtle or implicit. To overcome these limitations, we introduce a novel approach called Dual-Task Contrastive Meta-Learning (DTCML). This method combines meta-learning and contrastive learning to improve emotion recognition. Meta-learning enhances the model’s ability to generalize to new emotional tasks, while instance contrastive learning further refines the model by distinguishing unique features within each category, enabling it to better differentiate complex emotional expressions. Prototype contrastive learning, in turn, helps the model address the semantic complexity of emotions across different domains, enabling the model to learn fine-grained emotions expression. By leveraging dual tasks, DTCML learns from two domains simultaneously, the model is encouraged to learn more diverse and generalizable emotions features, thereby improving its cross-domain adaptability and robustness, and enhancing its generalization ability. We evaluated the performance of DTCML across four cross-domain settings, and the results show that our method outperforms the best baseline by 5.88%, 12.04%, 8.49%, and 8.40% in terms of accuracy.
基金Supported in part by the National Key R&D Program of China(No.2020YFA0712300)NSFC(No.61872353)。
文摘Fraction repetition(FR)codes are integral in distributed storage systems(DSS)with exact repair-by-transfer,while pliable fraction repetition codes are vital for DSSs in which both the per-node storage and repetition degree can easily be adjusted simultaneously.This paper introduces a new type of pliable FR codes,called absolute balanced pliable FR(ABPFR)codes,in which the access balancing in DSS is considered.Additionally,the equivalence between pliable FR codes and resolvable transversal packings in combinatorial design theory is presented.Then constructions of pliable FR codes and ABPFR codes based on resolvable transversal packings are presented.
基金supported in part by the National Natural Science Foundation of China under Grant U23A20300 and 62072351in part by the Key Research Project of Shaanxi Natural Science Foundation under Grant 2023-JC-ZD-35+1 种基金in part by the Concept Verification Funding of Hangzhou Institute of Technology of Xidian University under Grant GNYZ2024XX007in part by the 111 Project under Grant B16037.
文摘Cross-domain routing in Integrated Heterogeneous Networks(Inte-HetNet)should ensure efficient and secure data transmission across different network domains by satisfying diverse routing requirements.However,current solutions face numerous challenges in continuously ensuring trustworthy routing,fulfilling diverse requirements,achieving reasonable resource allocation,and safeguarding against malicious behaviors of network operators.We propose CrowdRouting,a novel cross-domain routing scheme based on crowdsourcing,dedicated to establishing sustained trust in cross-domain routing,comprehensively considering and fulfilling various customized routing requirements,while ensuring reasonable resource allocation and effectively curbing malicious behavior of network operators.Concretely,CrowdRouting employs blockchain technology to verify the trustworthiness of border routers in different network domains,thereby establishing sustainable and trustworthy crossdomain routing based on sustained trust in these routers.In addition,CrowdRouting ingeniously integrates a crowdsourcing mechanism into the auction for routing,achieving fair and impartial allocation of routing rights by flexibly embedding various customized routing requirements into each auction phase.Moreover,CrowdRouting leverages incentive mechanisms and routing settlement to encourage network domains to actively participate in cross-domain routing,thereby promoting optimal resource allocation and efficient utilization.Furthermore,CrowdRouting introduces a supervisory agency(e.g.,undercover agent)to effectively suppress the malicious behavior of network operators through the game and interaction between the agent and the network operators.Through comprehensive experimental evaluations and comparisons with existing works,we demonstrate that CrowdRouting excels in providing trustworthy and fine-grained customized routing services,stimulating active participation in cross-domain routing,inhibiting malicious operator behavior,and maintaining reasonable resource allocation,all of which outperform baseline schemes.
基金supported in part by the International Science and Technology Cooperation Program of Liaoning Province(Grant No.2022JH2/10700012)the Applied Basic Research Program of Liaoning Province(Grant No.2023JH2/101300188,2022JH2/101300269)+2 种基金the Foundation of Yunnan Key Laboratory of Service Computing(Grant No.YNSC23118)the Basic Research Project of Liaoning Educational Department(Grant No.JYTMS20230011)supported by the Fundamental Research Funds for the Provincial Universities of Liaoning(No.LJ212410150030).
文摘To facilitate cross-domain data interaction in the Industrial Internet of Things(IIoT),establishing trust between multiple administrative domains is essential.Although blockchain technology has been proposed as a solution,current techniques still suffer from issues related to efficiency,security,and privacy.Our research aims to address these challenges by proposing a lightweight,trusted data interaction scheme based on blockchain,which reduces redundant interactions among entities.We enhance the traditional Practical Byzantine Fault Tolerance(PBFT)algorithm to support lightweight distributed consensus in large-scale IIoT scenarios.Introducing a composite digital signature algorithm and incorporating veto power minimizes resource consumption and eliminates ineffective consensus operations.The experimental results show that,compared with PBFT,our scheme reduces latency by 27.2%,thereby improving communication efficiency and resource utilization.Furthermore,we develop a lightweight authentication technique specifically for cross-domain IIoT,leveraging blockchain technology to achieve distributed collaborative authentication.The performance comparisons indicate that our method significantly outperforms traditional schemes,with an average authentication latency of approximately 151 milliseconds.Additionally,we introduce a trusted federated learning(FL)algorithm that ensures comprehensive trust assessments for devices across different domains while protecting data privacy.Extensive simulations and experiments validate the reliability of our approach.
基金supported by National Natural Science Foundation of China(61901071,61871062,61771082,U20A20157)Science and Natural Science Foundation of Chongqing,China(cstc2020jcyjzdxmX0024)+6 种基金University Innovation Research Group of Chongqing(CXQT20017)Program for Innovation Team Building at Institutions of Higher Education in Chongqing(CXTDX201601020)Natural Science Foundation of Chongqing,China(CSTB2022NSCQ-MSX0600)Youth Innovation Group Support Program of ICE Discipline of CQUPT(SCIE-QN-2022-04)Chongqing Municipal Technology Innovation and Application Development Special Key Project(cstc2020jscxdxwtBX0053)China Postdoctoral Science Foundation Project,China(2022MD723723)Chongqing Postdoctoral Research Project Special Funding,China(2023CQBSHTB3092)。
文摘The lack of facial features caused by wearing masks degrades the performance of facial recognition systems.Traditional occluded face recognition methods cannot integrate the computational resources of the edge layer and the device layer.Besides,previous research fails to consider the facial characteristics including occluded and unoccluded parts.To solve the above problems,we put forward a device-edge collaborative occluded face recognition method based on cross-domain feature fusion.Specifically,the device-edge collaborative face recognition architecture gets the utmost out of maximizes device and edge resources for real-time occluded face recognition.Then,a cross-domain facial feature fusion method is presented which combines both the explicit domain and the implicit domain facial.Furthermore,a delay-optimized edge recognition task scheduling method is developed that comprehensively considers the task load,computational power,bandwidth,and delay tolerance constraints of the edge.This method can dynamically schedule face recognition tasks and minimize recognition delay while ensuring recognition accuracy.The experimental results show that the proposed method achieves an average gain of about 21%in recognition latency,while the accuracy of the face recognition task is basically the same compared to the baseline method.
基金funded in part by the National Natural Science Foundation of China(Nos.62322111,62271289,62501186)the Natural Science Fund for Outstanding Young Scholars of Shandong Province(No.ZR2022YQ60)+4 种基金the Research Fund for the Taishan Scholar Project of Shandong Province(No.tsqn202306064)the Natural Science Fund for Distinguished Young Scientists of ShandongProvince(No.ZR2024JQ007)Shenzhen Science and Technology Program(No.JCYJ20240813101228036)Jinan“20 Terms of New Universities”Funding Project(No.202333035)the Fundamental Research funds for theCentral Universities(No.3072025CFJ0805).
文摘Although significant progress has been made in micro-expression recognition,effectively modeling the intricate spatial-temporal dynamics remains a persistent challenge owing to their brief duration and complex facial dynamics.Furthermore,existing methods often suffer from limited gen-eralization,as they primarily focus on single-dataset tasks with small sample sizes.To address these two issues,this paper proposes the cross-domain spatial-temporal graph convolutional network(GCN)(CDST-GCN)model,which comprises two primary components:a siamese attention spa-tial-temporal branch(SASTB)and a global-aware dynamic spatial-temporal branch(GDSTB).Specifically,SASTB utilizes a contrastive learning strategy to project macro-and micro-expressions into a shared,aligned feature space,actively addressing cross-domain discrepancies.Additionally,it integrates an attention-gated mechanism that generates adaptive adjacency matrices to flexibly model collaborative patterns among facial landmarks.While largely preserving the structural paradigm of SASTB,GDSTB enhances the feature representation by integrating global context extracted from a pretrained model.Through this dual-branch architecture,CDST-GCN success-fully models both the global and local spatial-temporal features.The experimental results on CASME II and SAMM datasets demonstrate that the proposed model achieves competitive perfor-mance.Especially in more challenging 5-class tasks,the accuracy of the model on CASME II dataset is as high as 80.5%.
基金supported in part by the National Natural Science Foundation of China under grants 61771255in part by the Provincial and Ministerial Key Laboratory Open Project under grant 20190904in part by the Key Technologies R&D Program of Jiangsu (Prospective and Key Technologies for Industry)under Grants BE2022067,BE2022067-1 and BE2022067-2。
文摘High reliability applications in dense access scenarios have become one of the main goals of 6G environments.To solve the access collision of dense Machine Type Communication(MTC)devices in cell-free communication systems,an intelligent cooperative secure access scheme based on multi-agent reinforcement learning and federated learning is proposed,that is,the Preamble Slice Orderly Queue Access(PSOQA)scheme.In this scheme,the preamble arrangement is combined with the access control.The preamble arrangement is realized by preamble slices which is from the virtual preamble pool.The access devices learn to queue orderly by deep reinforcement learning.The orderly queue weakens the random and avoids collision.A preamble slice is assigned to an orderly access queue at each access time.The orderly queue is determined by interaction information among multiple agents.With the federated reinforcement learning framework,the PSOQA scheme is implemented to guarantee the privacy and security of agents.Finally,the access performance of PSOQA is compared with other random contention schemes in different load scenarios.Simulation results show that PSOQA can not only improve the access success rate but also guarantee low-latency tolerant performances.
基金supported in part by Jiangsu Province High Level“333”Program (0401206044)National Natural Science Foundation of China (61801243,62072255)+4 种基金Program for Scientific Research Foundation for Talented Scholars of Jinling Institute of Technology (JIT-B-202031)University Incubator Foundation of Jinling Institute of Technology (JIT-FHXM-202110)Open Project of Fujian Provincial Key Lab.of Network Security and Cryptology (NSCL-KF2021-02)Open Foundation of National Railway Intelligence Transportation System Engineering Tech.Research Center (RITS2021KF02)China Postdoctoral Science Foundation (2019M651914)。
文摘The secured access is studied in this paper for the network of the image remote sensing.Each sensor in this network encounters the information security when uploading information of the images wirelessly from the sensor to the central collection point.In order to enhance the sensing quality for the remote uploading,the passive reflection surface technique is employed.If one eavesdropper that exists nearby this sensor is keeping on accessing the same networks,he may receive the same image from this sensor.Our goal in this paper is to improve the SNR of legitimate collection unit while cut down the SNR of the eavesdropper as much as possible by adaptively adjust the uploading power from this sensor to enhance the security of the remote sensing images.In order to achieve this goal,the secured energy efficiency performance is theoretically analyzed with respect to the number of the passive reflection elements by calculating the instantaneous performance over the channel fading coefficients.Based on this theoretical result,the secured access is formulated as a mathematical optimization problem by adjusting the sensor uploading power as the unknown variables with the objective of the energy efficiency maximization while satisfying any required maximum data rate of the eavesdropper sensor.Finally,the analytical expression is theoretically derived for the optimum uploading power.Numerical simulations verify the design approach.
