The year 2025 marks both the 25th anniversary of the Forum on China-Africa Cooperation(FOCAC)and the first year of implementation of the outcomes of the 2024 FOCAC Beijing Summit.Throughout the year,China has supporte...The year 2025 marks both the 25th anniversary of the Forum on China-Africa Cooperation(FOCAC)and the first year of implementation of the outcomes of the 2024 FOCAC Beijing Summit.Throughout the year,China has supported Africa in addressing historical injustices at diplomatic and political levels and firmly backed South Africa in hosting the G20 Leaders’Summit,further deepening China-Africa strategic mutual trust.展开更多
Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,com...Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.展开更多
GS1 is an international standards organization,which focuses on product identification and product data,helping businesses and governments to improve commerce and supply chain.Why trusted data is essential to high-qua...GS1 is an international standards organization,which focuses on product identification and product data,helping businesses and governments to improve commerce and supply chain.Why trusted data is essential to high-quality development?More than 50 years ago,GS1 was initiated with the bar code,a profound transformation of the way we work and live.From then on,a simple scan connected a physical product to its digital identity.It transformed commerce,improving supply chains and enabling safer healthcare.Collaboration between industry and governments,and a strong partnership with ISO and IEC laid the foundations for the global adoption of a common product identification over the past 50 years and all around the world.展开更多
Since the guarantee of trustiness is considered inadequate in traditional software development methods,software developed using these methods lacks effective measures for ensuring its trustiness.Combining agent techni...Since the guarantee of trustiness is considered inadequate in traditional software development methods,software developed using these methods lacks effective measures for ensuring its trustiness.Combining agent technique with the support of trusted computing provided by TPM,a trust-shell-based constitution model of trusted software(TSCMTS)is demonstrated,trust shell ensures the trustiness of software logically.The concept of Trust Engine is proposed,which extends the "chain of trust" of TCG into application,and cooperates with TPM to perform integrity measurement for software entity to ensure the static trustiness;Data Structure called trust view is defined to represent the characteristic of software behavior.For the purpose of improving the accuracy of trustiness constraints,a strategy for determining the weights of characteristic attributes based on information entropy is proposed.Simulation experiments illustrate that the trustiness of software developed by the TSCMTS is improved effectively without performance degradation.展开更多
Today,I want to share how international standards can forge trust and fuel innovation,laying the foundation for a future where AI benefits everyone,everywhere.First,AI standards,developed jointly by ISO and IEC-the In...Today,I want to share how international standards can forge trust and fuel innovation,laying the foundation for a future where AI benefits everyone,everywhere.First,AI standards,developed jointly by ISO and IEC-the International Electrotechnical Commission-help build global trust and enable responsible innovation by bringing clarity and coherence to an ever-changing AI landscape.As developments in AI continue to emerge at speed,regulation is struggling to keep up and the proliferation of competing standards has created confusion rather than clarity.ISO and our partner IEC are addressing this challenge through the work of our expert committee on AI,SC 42,which takes a holistic,cohesive approach to AI standardization.展开更多
Nowadays,we are witnessing the tremendous changes brought by AI technologies.What role can standards play in this process?How can we build global trust and enable responsible innovation?
With the introduction of 5G,users and devices can access the industrial network from anywhere in the world.Therefore,traditional perimeter-based security technologies for industrial networks can no longer work well.To...With the introduction of 5G,users and devices can access the industrial network from anywhere in the world.Therefore,traditional perimeter-based security technologies for industrial networks can no longer work well.To solve this problem,a new security model called Zero Trust(ZT)is desired,which believes in“never trust and always verify”.Every time the asset in the industrial network is accessed,the subject is authenticated and its trustworthiness is assessed.In this way,the asset in industrial network can be well protected,whether the subject is in the internal network or the external network.However,in order to construct the zero trust model in the 5G Industrial Internet collaboration system,there are still many problems to be solved.In this paper,we first introduce the security issues in the 5G Industrial Internet collaboration system,and illustrate the zero trust architecture.Then,we analyze the gap between existing security techniques and the zero trust architecture.Finally,we discuss several potential security techniques that can be used to implement the zero trust model.The purpose of this paper is to point out the further direction for the realization of the Zero Trust Architecture(ZTA)in the 5G Industrial Internet collaboration system.展开更多
In the complex environment of Wireless Sensor Networks(WSNs),various malicious attacks have emerged,among which internal attacks pose particularly severe security risks.These attacks seriously threaten network stabili...In the complex environment of Wireless Sensor Networks(WSNs),various malicious attacks have emerged,among which internal attacks pose particularly severe security risks.These attacks seriously threaten network stability,data transmission reliability,and overall performance.To effectively address this issue and significantly improve intrusion detection speed,accuracy,and resistance to malicious attacks,this research designs a Three-level Intrusion Detection Model based on Dynamic Trust Evaluation(TIDM-DTE).This study conducts a detailed analysis of how different attack types impact node trust and establishes node models for data trust,communication trust,and energy consumption trust by focusing on characteristics such as continuous packet loss and energy consumption changes.By dynamically predicting node trust values using the grey Markov model,the model accurately and sensitively reflects changes in node trust levels during attacks.Additionally,DBSCAN(Density-Based Spatial Clustering of Applications with Noise)data noise monitoring technology is employed to quickly identify attacked nodes,while a trust recovery mechanism restores the trust of temporarily faulty nodes to reduce False Alarm Rate.Simulation results demonstrate that TIDM-DTE achieves high detection rates,fast detection speed,and low False Alarm Rate when identifying various network attacks,including selective forwarding attacks,Sybil attacks,switch attacks,and black hole attacks.TIDM-DTE significantly enhances network security,ensures secure and reliable data transmission,moderately improves network energy efficiency,reduces unnecessary energy consumption,and provides strong support for the stable operation of WSNs.Meanwhile,the research findings offer new ideas and methods for WSN security protection,possessing important theoretical significance and practical application value.展开更多
The core missions of IoT are to sense data,transmit data and give feedback to the real world based on the calculation of the sensed data.The trust of sensing source data and transmission network is extremely important...The core missions of IoT are to sense data,transmit data and give feedback to the real world based on the calculation of the sensed data.The trust of sensing source data and transmission network is extremely important to IoT security.5G-IoT with its low latency,wide connectivity and high-speed transmission extends the business scenarios of IoT,yet it also brings new challenges to trust proof solutions of IoT.Currently,there is a lack of efficient and reliable trust proof solutions for massive dynamically connected nodes,while the existing solutions have high computational complexity and can't adapt to time-sensitive services in 5G-IoT scenarios.In order to solve the above problems,this paper proposes an adaptive multi-dimensional trust proof solution.Firstly,the static and dynamic attributes of sensing nodes are metricized,and the historical interaction as well as the recommendation information are combined with the comprehensive metric of sensing nodes,and a multi-dimensional fine-grained trusted metric model is established in this paper.Then,based on the comprehensive metrics,the sensing nodes are logically grouped and assigned with service levels to achieve the screening and isolation of malicious nodes.At the same time,the proposed solution reduces the energy consumption of the metric process and optimizes the impact of real-time metrics on the interaction latency.Simulation experiments show that the solution can accurately and efficiently identify malicious nodes and effectively guarantee the safe and trustworthy operation of 5G-IoT nodes,while having a small impact on the latency of the 5G network.展开更多
Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algo...Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algorithm based on TrustSVD++and XGBoost.Firstly,the explicit trust and implicit trust were introduced into the SVD++model to construct the TrustSVD++model.Secondly,considering that there is much data in the interaction matrix after filling,which may lead to a rather complex calculation process,the K-means algorithm is introduced to cluster and extract user and item features at the same time.Then,in order to improve the accuracy of rating prediction for target users,an XGBoost model is proposed to train user and item features,and finally,it is verified on the data sets MovieLens-1M and MovieLens-100k.Experiments show that compared with the SVD++model and the recommendation algorithm without XGBoost model training,the proposed algorithm has the RMSE value reduced by 2.9%and the MAE value reduced by 3%.展开更多
The rapid growth of Internet of things devices and the emergence of rapidly evolving network threats have made traditional security assessment methods inadequate.Federated learning offers a promising solution to exped...The rapid growth of Internet of things devices and the emergence of rapidly evolving network threats have made traditional security assessment methods inadequate.Federated learning offers a promising solution to expedite the training of security assessment models.However,ensuring the trustworthiness and robustness of federated learning under multi-party collaboration scenarios remains a challenge.To address these issues,this study proposes a shard aggregation network structure and a malicious node detection mechanism,along with improvements to the federated learning training process.First,we extract the data features of the participants by using spectral clustering methods combined with a Gaussian kernel function.Then,we introduce a multi-objective decision-making approach that combines data distribution consistency,consensus communication overhead,and consensus result reliability in order to determine the final network sharing scheme.Finally,by integrating the federated learning aggregation process with the malicious node detection mechanism,we improve the traditional decentralized learning process.Our proposed ShardFed algorithm outperforms conventional classification algorithms and state-of-the-art machine learning methods like FedProx and FedCurv in convergence speed,robustness against data interference,and adaptability across multiple scenarios.Experimental results demonstrate that the proposed approach improves model accuracy by up to 2.33%under non-independent and identically distributed data conditions,maintains higher performance with malicious nodes containing poisoned data ratios of 20%–50%,and significantly enhances model resistance to low-quality data.展开更多
In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relation...In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relationship among these objects in a trusted system according to trusted computing specifications. Inference rules of trusted relation are given too. With the semantics proposed, some trusted computing models are formalized and verified, which shows that Predicate calculus logic provides a general and effective method for modeling and reasoning trusted computing systems.展开更多
The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is impor...The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is imported into distributed system, such as chain of trust, trusted root and so on. Based on distributed database server system （DDSS）, a novel model of trusted distributed database server system （TDDSS） is presented ultimately. In TDDSS role-based access control, two-level of logs and other technologies are adopted to ensure the trustworthiness of the system.展开更多
To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply rel...To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply relationships in the automotive market,improving data sharing and interactions across various platforms,and achieving more detailed integration of data and operations.We propose a trust evaluation permission delegation method based on the automotive industry chain.The proposed method combines smart contracts with trust evaluation mechanisms,dynamically calculating the trust value of users based on the historical behavior of the delegated entity,network environment,and other factors to avoid malicious node attacks during the permission delegation process.We also introduce strict control over the cross-domain permission granting and revocation mechanisms to manage the delegation path,prevent information leakage caused by malicious node interception,and effectively protect data integrity and privacy.Experimental analysis shows that this method meets the realtime requirements of collaborative interaction in the automotive industry chain and provides a feasible solution to permission delegation issues in the automotive industry chain,offering dynamic flexibility in authorization and scalability compared to most existing solutions.展开更多
Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks.To address such threats towards cloud services,num...Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks.To address such threats towards cloud services,numerous techniques exist that mitigate the service threats according to different metrics.The rule-based approaches are unsuitable for new threats,whereas trust-based systems estimate trust value based on behavior,flow,and other features.However,the methods suffer from mitigating intrusion attacks at a higher rate.This article presents a novel Multi Fractal Trust Evaluation Model(MFTEM)to overcome these deficiencies.The method involves analyzing service growth,network growth,and quality of service growth.The process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support(TSS).Also,the user’s trust in supporting network stream by computing Trusted Network Support(TNS).Similarly,the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support(TQS).Using all these measures,the method adds the Trust User Score(TUS)value to decide on the clearance of user requests.The proposed MFTEM model improves intrusion detection accuracy with higher performance.展开更多
This study investigates the effects of AI-mediated communication (AMC) on trust-building and negotiation outcomes in professional remote collaboration settings. Through a mixed-methods approach combining experimental ...This study investigates the effects of AI-mediated communication (AMC) on trust-building and negotiation outcomes in professional remote collaboration settings. Through a mixed-methods approach combining experimental design and qualitative analysis (N = 120), we examine how AI intermediaries influence communication dynamics, relationship building, and decision-making processes. Results indicate that while AMC initially creates barriers to trust formation, it ultimately leads to enhanced communication outcomes and stronger professional relationships when implemented with appropriate transparency and support. The study revealed a 31% improvement in cross-cultural understanding and a 24% increase in negotiation satisfaction rates when using AI-mediated channels with proper transparency measures. These findings contribute to the theoretical understanding of technology-mediated communication and practical applications for organizations implementing AI communication tools.展开更多
目的评估不同孕周应用苄星青霉素G对妊娠梅毒患者的疗效,及其对母婴结局和甲苯胺红不加热血清试验(TRUST)滴度的干预效果。方法回顾性选取2021年6月至2024年6月西北妇女儿童医院收治的98例妊娠梅毒患者,按不同孕周应用苄星青霉素G分为3...目的评估不同孕周应用苄星青霉素G对妊娠梅毒患者的疗效,及其对母婴结局和甲苯胺红不加热血清试验(TRUST)滴度的干预效果。方法回顾性选取2021年6月至2024年6月西北妇女儿童医院收治的98例妊娠梅毒患者,按不同孕周应用苄星青霉素G分为3组:孕早期组(≤13+6周,n=32)、孕中期组(14~27+6周,n=33)和孕晚期组(≥28周,n=33)。比较3组产妇治疗前、治疗2个疗程后的氧化应激指标[超氧化物歧化酶(SOD)、丙二醛、晚期氧化蛋白产物(AOPP)]水平、新生儿及产妇TRUST滴度比、产妇情况(产后出血率、早产率)及新生儿情况(先天梅毒儿、出生后5 min Apgar评分、体质量)。结果(1)较治疗前,3组产妇治疗2个疗程后血清SOD水平均更高,丙二醛、AOPP水平均更低,差异均有统计学意义(P<0.05);较孕早期组,孕中期组、孕晚期组产妇治疗2个疗程后SOD水平更低,丙二醛、AOPP水平更高,差异均有统计学意义(P<0.05)。(2)孕中期组、孕晚期组新生儿治疗后TRUST阴性率分别为30.30%、24.24%,较孕早期组(56.25%)更低,差异有统计学意义(P<0.05)。(3)孕中期组、孕晚期组产妇治疗后TRUST阴性率分别为9.09%、3.03%,较孕早期组(28.13%)更低,差异有统计学意义(P<0.05)。(4)较孕早期组,孕中期组、孕晚期组新生儿先天梅毒儿占比更高,出生后5 min Apgar评分、体质量更低,差异均有统计学意义(P<0.05)。结论妊娠梅毒患者孕早期应用苄星青霉素G疗效优于孕中期和孕晚期,对氧化应激改善更为显著,能进一步提升母婴TRUST阴性率及改善母婴结局。展开更多
文摘The year 2025 marks both the 25th anniversary of the Forum on China-Africa Cooperation(FOCAC)and the first year of implementation of the outcomes of the 2024 FOCAC Beijing Summit.Throughout the year,China has supported Africa in addressing historical injustices at diplomatic and political levels and firmly backed South Africa in hosting the G20 Leaders’Summit,further deepening China-Africa strategic mutual trust.
基金funded by the National Natural Science Foundation of China,grant numbers(62272007,62001007)the Natural Science Foundation of Beijing,grant numbers(4234083,4212018)The authors also extend their appreciation to King Khalid University for funding this work through the Large Group Project under grant number RGP.2/373/45.
文摘Border Gateway Protocol(BGP),as the standard inter-domain routing protocol,is a distance-vector dynamic routing protocol used for exchanging routing information between distributed Autonomous Systems(AS).BGP nodes,communicating in a distributed dynamic environment,face several security challenges,with trust being one of the most important issues in inter-domain routing.Existing research,which performs trust evaluation when exchanging routing information to suppress malicious routing behavior,cannot meet the scalability requirements of BGP nodes.In this paper,we propose a blockchain-based trust model for inter-domain routing.Our model achieves scalability by allowing the master node of an AS alliance to transmit the trust evaluation data of its member nodes to the blockchain.The BGP nodes can expedite the trust evaluation process by accessing a global view of other BGP nodes through the master node of their respective alliance.We incorporate security service evaluation before direct evaluation and indirect recommendations to assess the security services that BGP nodes provide for themselves and prioritize to guarantee their security of routing service.We forward the trust evaluation for neighbor discovery and prioritize the nodes with high trust as neighbor nodes to reduce the malicious exchange routing behavior.We use simulation software to simulate a real BGP environments and employ a comparative experimental research approach to demonstrate the performance evaluation of our trust model.Compared with the classical trust model,our trust model not only saves more storage overhead,but also provides higher security,especially reducing the impact of collusion attacks.
文摘GS1 is an international standards organization,which focuses on product identification and product data,helping businesses and governments to improve commerce and supply chain.Why trusted data is essential to high-quality development?More than 50 years ago,GS1 was initiated with the bar code,a profound transformation of the way we work and live.From then on,a simple scan connected a physical product to its digital identity.It transformed commerce,improving supply chains and enabling safer healthcare.Collaboration between industry and governments,and a strong partnership with ISO and IEC laid the foundations for the global adoption of a common product identification over the past 50 years and all around the world.
基金National Natural Science Foundation of China under Grant No. 60873203Foundation of Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education under Grant No. AISTC2009_03+1 种基金Hebei National Funds for Distinguished Young Scientists under Grant No. F2010000317National Science Foundation of Hebei Province under Grant No. F2010000319
文摘Since the guarantee of trustiness is considered inadequate in traditional software development methods,software developed using these methods lacks effective measures for ensuring its trustiness.Combining agent technique with the support of trusted computing provided by TPM,a trust-shell-based constitution model of trusted software(TSCMTS)is demonstrated,trust shell ensures the trustiness of software logically.The concept of Trust Engine is proposed,which extends the "chain of trust" of TCG into application,and cooperates with TPM to perform integrity measurement for software entity to ensure the static trustiness;Data Structure called trust view is defined to represent the characteristic of software behavior.For the purpose of improving the accuracy of trustiness constraints,a strategy for determining the weights of characteristic attributes based on information entropy is proposed.Simulation experiments illustrate that the trustiness of software developed by the TSCMTS is improved effectively without performance degradation.
文摘Today,I want to share how international standards can forge trust and fuel innovation,laying the foundation for a future where AI benefits everyone,everywhere.First,AI standards,developed jointly by ISO and IEC-the International Electrotechnical Commission-help build global trust and enable responsible innovation by bringing clarity and coherence to an ever-changing AI landscape.As developments in AI continue to emerge at speed,regulation is struggling to keep up and the proliferation of competing standards has created confusion rather than clarity.ISO and our partner IEC are addressing this challenge through the work of our expert committee on AI,SC 42,which takes a holistic,cohesive approach to AI standardization.
文摘Nowadays,we are witnessing the tremendous changes brought by AI technologies.What role can standards play in this process?How can we build global trust and enable responsible innovation?
基金supported by the National Natural Science Foundation of China(U22B2026)the ZTE Industry-Academia-Research Project(HC-CN-20221029003,IA20230628015)。
文摘With the introduction of 5G,users and devices can access the industrial network from anywhere in the world.Therefore,traditional perimeter-based security technologies for industrial networks can no longer work well.To solve this problem,a new security model called Zero Trust(ZT)is desired,which believes in“never trust and always verify”.Every time the asset in the industrial network is accessed,the subject is authenticated and its trustworthiness is assessed.In this way,the asset in industrial network can be well protected,whether the subject is in the internal network or the external network.However,in order to construct the zero trust model in the 5G Industrial Internet collaboration system,there are still many problems to be solved.In this paper,we first introduce the security issues in the 5G Industrial Internet collaboration system,and illustrate the zero trust architecture.Then,we analyze the gap between existing security techniques and the zero trust architecture.Finally,we discuss several potential security techniques that can be used to implement the zero trust model.The purpose of this paper is to point out the further direction for the realization of the Zero Trust Architecture(ZTA)in the 5G Industrial Internet collaboration system.
基金supported by Gansu Provincial Higher Education Teachers’Innovation Fund under Grant 2025A-124Key Research Project of Gansu University of Political Science and Law under Grant No.GZF2022XZD08Soft Science Special Project of Gansu Basic Research Plan under Grant No.22JR11RA106.
文摘In the complex environment of Wireless Sensor Networks(WSNs),various malicious attacks have emerged,among which internal attacks pose particularly severe security risks.These attacks seriously threaten network stability,data transmission reliability,and overall performance.To effectively address this issue and significantly improve intrusion detection speed,accuracy,and resistance to malicious attacks,this research designs a Three-level Intrusion Detection Model based on Dynamic Trust Evaluation(TIDM-DTE).This study conducts a detailed analysis of how different attack types impact node trust and establishes node models for data trust,communication trust,and energy consumption trust by focusing on characteristics such as continuous packet loss and energy consumption changes.By dynamically predicting node trust values using the grey Markov model,the model accurately and sensitively reflects changes in node trust levels during attacks.Additionally,DBSCAN(Density-Based Spatial Clustering of Applications with Noise)data noise monitoring technology is employed to quickly identify attacked nodes,while a trust recovery mechanism restores the trust of temporarily faulty nodes to reduce False Alarm Rate.Simulation results demonstrate that TIDM-DTE achieves high detection rates,fast detection speed,and low False Alarm Rate when identifying various network attacks,including selective forwarding attacks,Sybil attacks,switch attacks,and black hole attacks.TIDM-DTE significantly enhances network security,ensures secure and reliable data transmission,moderately improves network energy efficiency,reduces unnecessary energy consumption,and provides strong support for the stable operation of WSNs.Meanwhile,the research findings offer new ideas and methods for WSN security protection,possessing important theoretical significance and practical application value.
基金supported by National Key R&D Program of China (2019YFB2102303)National Natural Science Foundation of China (NSFC61971014,NSFC11675199)+2 种基金Beijing Postdoctoral Research Foundation (2021-ZZ-079)Young Backbone Teacher Training Program of Henan Colleges and Universities (2021GGJS170)Henan Province Higher Education Key Research Project (23B520014)。
文摘The core missions of IoT are to sense data,transmit data and give feedback to the real world based on the calculation of the sensed data.The trust of sensing source data and transmission network is extremely important to IoT security.5G-IoT with its low latency,wide connectivity and high-speed transmission extends the business scenarios of IoT,yet it also brings new challenges to trust proof solutions of IoT.Currently,there is a lack of efficient and reliable trust proof solutions for massive dynamically connected nodes,while the existing solutions have high computational complexity and can't adapt to time-sensitive services in 5G-IoT scenarios.In order to solve the above problems,this paper proposes an adaptive multi-dimensional trust proof solution.Firstly,the static and dynamic attributes of sensing nodes are metricized,and the historical interaction as well as the recommendation information are combined with the comprehensive metric of sensing nodes,and a multi-dimensional fine-grained trusted metric model is established in this paper.Then,based on the comprehensive metrics,the sensing nodes are logically grouped and assigned with service levels to achieve the screening and isolation of malicious nodes.At the same time,the proposed solution reduces the energy consumption of the metric process and optimizes the impact of real-time metrics on the interaction latency.Simulation experiments show that the solution can accurately and efficiently identify malicious nodes and effectively guarantee the safe and trustworthy operation of 5G-IoT nodes,while having a small impact on the latency of the 5G network.
基金Guangdong Science and Technology University Young Projects(GKY-2023KYQNK-1 and GKY-2023KYQNK-10)Guangdong Provincial Key Discipline Research Capacity Improvement Project(2022ZDJS147)。
文摘Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it,this paper proposes a recommendation algorithm based on TrustSVD++and XGBoost.Firstly,the explicit trust and implicit trust were introduced into the SVD++model to construct the TrustSVD++model.Secondly,considering that there is much data in the interaction matrix after filling,which may lead to a rather complex calculation process,the K-means algorithm is introduced to cluster and extract user and item features at the same time.Then,in order to improve the accuracy of rating prediction for target users,an XGBoost model is proposed to train user and item features,and finally,it is verified on the data sets MovieLens-1M and MovieLens-100k.Experiments show that compared with the SVD++model and the recommendation algorithm without XGBoost model training,the proposed algorithm has the RMSE value reduced by 2.9%and the MAE value reduced by 3%.
基金supported by State Grid Hebei Electric Power Co.,Ltd.Science and Technology Project,Research on Security Protection of Power Services Carried by 4G/5G Networks(Grant No.KJ2024-127).
文摘The rapid growth of Internet of things devices and the emergence of rapidly evolving network threats have made traditional security assessment methods inadequate.Federated learning offers a promising solution to expedite the training of security assessment models.However,ensuring the trustworthiness and robustness of federated learning under multi-party collaboration scenarios remains a challenge.To address these issues,this study proposes a shard aggregation network structure and a malicious node detection mechanism,along with improvements to the federated learning training process.First,we extract the data features of the participants by using spectral clustering methods combined with a Gaussian kernel function.Then,we introduce a multi-objective decision-making approach that combines data distribution consistency,consensus communication overhead,and consensus result reliability in order to determine the final network sharing scheme.Finally,by integrating the federated learning aggregation process with the malicious node detection mechanism,we improve the traditional decentralized learning process.Our proposed ShardFed algorithm outperforms conventional classification algorithms and state-of-the-art machine learning methods like FedProx and FedCurv in convergence speed,robustness against data interference,and adaptability across multiple scenarios.Experimental results demonstrate that the proposed approach improves model accuracy by up to 2.33%under non-independent and identically distributed data conditions,maintains higher performance with malicious nodes containing poisoned data ratios of 20%–50%,and significantly enhances model resistance to low-quality data.
基金Supported by the National High-Technology Re-search and Development Program ( 863 Program)China(2004AA113020)
文摘In this paper, a formal approach based on predicate logic is proposed for representing and reasoning of trusted computing models. Predicates are defined to represent the characteristics of the objects and the relationship among these objects in a trusted system according to trusted computing specifications. Inference rules of trusted relation are given too. With the semantics proposed, some trusted computing models are formalized and verified, which shows that Predicate calculus logic provides a general and effective method for modeling and reasoning trusted computing systems.
基金Supported by the Natural Science Foundation ofHebei Province (F2004000133)
文摘The most significant strategic development in information technology over the past years has been ＂trusted computing＂ and trusted computers have been produced. In this paper trusted mechanisms adopted by PC is imported into distributed system, such as chain of trust, trusted root and so on. Based on distributed database server system （DDSS）, a novel model of trusted distributed database server system （TDDSS） is presented ultimately. In TDDSS role-based access control, two-level of logs and other technologies are adopted to ensure the trustworthiness of the system.
基金funded by the Sichuan Science and Technology Program,Grant Nos.2024NSFSC0515,2024ZHCG0182 and MZGC20230013.
文摘To solve the challenges of connecting and coordinating multiple platforms in the automotive industry and to enhance collaboration among different participants,this research focuses on addressing the complex supply relationships in the automotive market,improving data sharing and interactions across various platforms,and achieving more detailed integration of data and operations.We propose a trust evaluation permission delegation method based on the automotive industry chain.The proposed method combines smart contracts with trust evaluation mechanisms,dynamically calculating the trust value of users based on the historical behavior of the delegated entity,network environment,and other factors to avoid malicious node attacks during the permission delegation process.We also introduce strict control over the cross-domain permission granting and revocation mechanisms to manage the delegation path,prevent information leakage caused by malicious node interception,and effectively protect data integrity and privacy.Experimental analysis shows that this method meets the realtime requirements of collaborative interaction in the automotive industry chain and provides a feasible solution to permission delegation issues in the automotive industry chain,offering dynamic flexibility in authorization and scalability compared to most existing solutions.
文摘Handling service access in a cloud environment has been identified as a critical challenge in the modern internet world due to the increased rate of intrusion attacks.To address such threats towards cloud services,numerous techniques exist that mitigate the service threats according to different metrics.The rule-based approaches are unsuitable for new threats,whereas trust-based systems estimate trust value based on behavior,flow,and other features.However,the methods suffer from mitigating intrusion attacks at a higher rate.This article presents a novel Multi Fractal Trust Evaluation Model(MFTEM)to overcome these deficiencies.The method involves analyzing service growth,network growth,and quality of service growth.The process estimates the user’s trust in various ways and the support of the user in achieving higher service performance by calculating Trusted Service Support(TSS).Also,the user’s trust in supporting network stream by computing Trusted Network Support(TNS).Similarly,the user’s trust in achieving higher throughput is analyzed by computing Trusted QoS Support(TQS).Using all these measures,the method adds the Trust User Score(TUS)value to decide on the clearance of user requests.The proposed MFTEM model improves intrusion detection accuracy with higher performance.
文摘This study investigates the effects of AI-mediated communication (AMC) on trust-building and negotiation outcomes in professional remote collaboration settings. Through a mixed-methods approach combining experimental design and qualitative analysis (N = 120), we examine how AI intermediaries influence communication dynamics, relationship building, and decision-making processes. Results indicate that while AMC initially creates barriers to trust formation, it ultimately leads to enhanced communication outcomes and stronger professional relationships when implemented with appropriate transparency and support. The study revealed a 31% improvement in cross-cultural understanding and a 24% increase in negotiation satisfaction rates when using AI-mediated channels with proper transparency measures. These findings contribute to the theoretical understanding of technology-mediated communication and practical applications for organizations implementing AI communication tools.
文摘目的评估不同孕周应用苄星青霉素G对妊娠梅毒患者的疗效,及其对母婴结局和甲苯胺红不加热血清试验(TRUST)滴度的干预效果。方法回顾性选取2021年6月至2024年6月西北妇女儿童医院收治的98例妊娠梅毒患者,按不同孕周应用苄星青霉素G分为3组:孕早期组(≤13+6周,n=32)、孕中期组(14~27+6周,n=33)和孕晚期组(≥28周,n=33)。比较3组产妇治疗前、治疗2个疗程后的氧化应激指标[超氧化物歧化酶(SOD)、丙二醛、晚期氧化蛋白产物(AOPP)]水平、新生儿及产妇TRUST滴度比、产妇情况(产后出血率、早产率)及新生儿情况(先天梅毒儿、出生后5 min Apgar评分、体质量)。结果(1)较治疗前,3组产妇治疗2个疗程后血清SOD水平均更高,丙二醛、AOPP水平均更低,差异均有统计学意义(P<0.05);较孕早期组,孕中期组、孕晚期组产妇治疗2个疗程后SOD水平更低,丙二醛、AOPP水平更高,差异均有统计学意义(P<0.05)。(2)孕中期组、孕晚期组新生儿治疗后TRUST阴性率分别为30.30%、24.24%,较孕早期组(56.25%)更低,差异有统计学意义(P<0.05)。(3)孕中期组、孕晚期组产妇治疗后TRUST阴性率分别为9.09%、3.03%,较孕早期组(28.13%)更低,差异有统计学意义(P<0.05)。(4)较孕早期组,孕中期组、孕晚期组新生儿先天梅毒儿占比更高,出生后5 min Apgar评分、体质量更低,差异均有统计学意义(P<0.05)。结论妊娠梅毒患者孕早期应用苄星青霉素G疗效优于孕中期和孕晚期,对氧化应激改善更为显著,能进一步提升母婴TRUST阴性率及改善母婴结局。
