In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation...In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation,individual similarity function,group similarity function,direct trust assessment function,and generalized predictive control,this model can guarantee the trust of an end user and users in its network.Compared with traditional measurement model,the model considers different characteristics of various networks.The trusted measurement policies established according to different network environments have better adaptability.By constructing trusted group,the threats to trusted group will be reduced greatly.Utilizing trusted group to restrict individuals in network can ensure the fault tolerance of trustworthiness of trusted individuals and group.The simulation shows that this scheme can support behavior measurement more efficiently than traditional ones and the model resists viruses and Trojans more efficiently than older ones.展开更多
The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network.But the trusted network...The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network.But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection,it is easy to cause the loss of identity privacy.In order to solve the abovedescribed problems,this paper presents a trust measurement scheme suitable for clients in the trusted network,the scheme integrates the following attributes such as authentication mechanism,state measurement,and real-time state measurement and so on,and based on the authentication mechanism and the initial state measurement,the scheme uses the realtime state measurement as the core method to complete the trust measurement for the client.This scheme presented in this paper supports both static and dynamic measurements.Overall,the characteristics of this scheme such as fine granularity,dynamic,real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.展开更多
As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development req...As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development requirements. Offering the system with secure and trusted services has become a new focus in network research. This paper first discusses the meaning of and aspects involved in the trusted network. According to this paper, the trusted network should be a network where the network’s and users’ behaviors and their results are always predicted and manageable. The trustworthiness of a network mainly involves three aspects: service provider, information transmission and terminal user. This paper also analyzes the trusted network in terms of trusted model for network/user behaviors, architecture of trusted network, service survivability and network manageability, which is designed to give ideas on solving the problems that may be faced in developing the trusted network.展开更多
Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Define...Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Defined Network(SDN)provides solutions through centralized control and dynamic resource allocation,but the existing scheduling methods based on Deep Reinforcement Learning(DRL)are insufficient in terms of convergence speed and dynamic optimization capability.To solve these problems,this paper proposes DRL-AMIR,which is an efficient flow scheduling method for software defined ZTN.This method constructs a flow scheduling optimization model that comprehensively considers service delay,bandwidth occupation,and path hops.Additionally,it balances the differentiated requirements of delay-critical K-flows,bandwidth-intensive D-flows,and background B-flows through adaptiveweighting.Theproposed framework employs a customized state space comprising node labels,link bandwidth,delaymetrics,and path length.It incorporates an action space derived fromnode weights and a hybrid reward function that integrates both single-step and multi-step excitation mechanisms.Based on these components,a hierarchical architecture is designed,effectively integrating the data plane,control plane,and knowledge plane.In particular,the adaptive expert mechanism is introduced,which triggers the shortest path algorithm in the training process to accelerate convergence,reduce trial and error costs,and maintain stability.Experiments across diverse real-world network topologies demonstrate that DRL-AMIR achieves a 15–20%reduction in K-flow transmission delays,a 10–15%improvement in link bandwidth utilization compared to SPR,QoSR,and DRSIR,and a 30%faster convergence speed via adaptive expert mechanisms.展开更多
In order to solve the problem of uncertainty and fuzzy information in the process of weapon equipment system selec-tion,a multi-attribute decision-making(MADM)method based on probabilistic hesitant fuzzy set(PHFS)is p...In order to solve the problem of uncertainty and fuzzy information in the process of weapon equipment system selec-tion,a multi-attribute decision-making(MADM)method based on probabilistic hesitant fuzzy set(PHFS)is proposed.Firstly,we introduce the concept of probability and fuzzy entropy to mea-sure the ambiguity,hesitation and uncertainty of probabilistic hesitant fuzzy elements(PHFEs).Sequentially,the expert trust network is constructed,and the importance of each expert in the network can be obtained by calculating the cumulative trust value under multiple trust propagation paths,so as to obtain the expert weight vector.Finally,we put forward an MADM method combining the probabilistic hesitant fuzzy entropy and grey rela-tion analysis(GRA)model,and an illustrative case is employed to prove the feasibility and effectiveness of the method when solving the weapon system selection decision-making problem.展开更多
The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it...The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.展开更多
The conception of trusted network connection （TNC） is introduced, and the weakness of TNC to control user＇s action is analyzed. After this, the paper brings out a set of secure access and control model based on acc...The conception of trusted network connection （TNC） is introduced, and the weakness of TNC to control user＇s action is analyzed. After this, the paper brings out a set of secure access and control model based on access, authorization and control, and related authentication protocol. At last the security of this model is analyzed. The model can improve TNC＇s security of user control and authorization.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
Matrix factorization （MF） has been proved to be a very effective technique for collaborative filtering （ CF）, and hence has been widely adopted in today＇s recommender systems, Yet due to its lack of consideration...Matrix factorization （MF） has been proved to be a very effective technique for collaborative filtering （ CF）, and hence has been widely adopted in today＇s recommender systems, Yet due to its lack of consideration of the users＇ and items＇ local structures, the recommendation accuracy is not fully satisfied. By taking the trusts among users＇ and between items＇ effect on rating information into consideration, trust-aware recommendation systems （TARS） made a relatively good performance. In this paper, a method of incorporating trust into MF was proposed by building user-based and item-based implicit trust network under different contexts and implementing two implicit trust-based context-aware MF （]TMF） models. Experimental results proved the effectiveness of the methods.展开更多
Purpose-Experts may adjust their assessments through communication and mutual influence,and this dynamic evolution relies on the spread of internal trust relationships.Due to differences in educational backgrounds and...Purpose-Experts may adjust their assessments through communication and mutual influence,and this dynamic evolution relies on the spread of internal trust relationships.Due to differences in educational backgrounds and knowledge experiences,trust relationships among experts are often incomplete.To address such issues and reduce decision biases,this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network(InSTN).Design/methodology/approach-In this paper,we first define the new trust propagation operators based on the operations of Probability Language Term Set(PLTS)with algebraic t-conorm and t-norm,which are combined with trust aggregation operators to estimate InSTN.The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation.Finally,the particle swarm algorithm(PSO)is used to optimize the expert evaluation to meet the consensus threshold.Findings-This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases.The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods,mainly due to the effective regulation of trust relations in the decision-making process,which reduces decision bias and inconsistencies.Originality/value-This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN.It proposes a redefined trust propagation and aggregation approach to estimate the InSTN.Moreover,the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.展开更多
User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media platfo...User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media platforms.These issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.展开更多
With the trend of digitalization,intelligence,and networking sweeping the world,functional safety and cyber security are increasingly intertwined and overlapped,evolving into the issue of generalized functional safety...With the trend of digitalization,intelligence,and networking sweeping the world,functional safety and cyber security are increasingly intertwined and overlapped,evolving into the issue of generalized functional safety.Traditional system reliability technology and network defense technology cannot provide quantifiable design implementation theories and methods.As the cornerstone of software systems,operating systems in particular are in need of efficient safety assurance.The DHR architecture is a mature and comprehensive solution,and it is necessary to implement an OS-level DHR architecture,for which the multi-kernel operating system is a good carrier.The multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy,heterogeneity,and dynamism on the kernel,so it has the generalized robustness of the DHR architecture.This article analyzes the significance and requirements of OS-level DHR architecture,and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.展开更多
The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia.The transformation of the Metaverse from science fiction to reality is being actively promote...The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia.The transformation of the Metaverse from science fiction to reality is being actively promoted by technology,industry,and capital.However,the development of the Metaverse is still in its early stages,and the system architecture and theoretical technology of the Metaverse are not yet mature.This paper provides a comprehensive analysis of the Metaverse and summarizes its holographic,omnipotent,multidimensional,and multifaceted characteristics.The development of the Metaverse is founded on the relevant infrastructure,and we elaborate on the primary components of the Metaverse infrastructure.Furthermore,we systematically summarize the security risks inherent in the Metaverse infrastructure.Based on this,we propose utilizing the system security technology concept to guide the construction of a Metaverse security protection system from various perspectives at each level of computing,cloud,network,digital assets,and terminals,in order to construct a secure foundation for addressing the Metaverse’s security risks and challenges.展开更多
Considering the fact that P2P （Peer-to-Peer） systems are self-organized and autonomous, social-control mechanism （like trust and reputation） is essential to evaluate the trustworthiness of participating peers and ...Considering the fact that P2P （Peer-to-Peer） systems are self-organized and autonomous, social-control mechanism （like trust and reputation） is essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest and malicious peer behaviors. So, naturally, we advocate that P2P systems that gradually act as an important information infrastructure should be multi-disciplinary research topic, and reflect certain features of our society. So, from economic and social perspective, this paper designs the incentive-compatible reputation feedback scheme based on well-known economic model, and characterizes the social features of trust network in terms of efficiency and cost. Specifically, our framework has two distinctive purposes： first, from high-level perspective, we argue trust system is a special kind of social network, and an accurate characterization of the structural properties of the network can be of fundamental importance to understand the dynamics of the system. Thus, inspired by the concept of weighted small-world, this paper proposes new measurements to characterize the social properties of trust system, that is, high global and local efficiency, and low cost; then, from relative low-level perspective, we argue that reputation feedback is a special kind of information, and it is not free. So, based on economic model, VCG （Vickrey-Clarke-Grove）-like reputation remuneration mechanism is proposed to stimulate rational peers not only to provide reputation feedback, but truthfully offer feedback. Furthermore, considering that trust and reputation is subjective, we classify the trust into functional trust and referral trust, and extend the referral trust to include two factors： similarity and truthfulness, which can efficiently reduce the trust inference error. The preliminary simulation results show the benefits of our proposal and the emergence of certain social properties in trust network.展开更多
Social trust network(STN)and minimum cost consensus(MCC)models have been widely used to address consensus issues in multi-attribute group decision-making(MAGDM)problems with limited resources.However,most researchers ...Social trust network(STN)and minimum cost consensus(MCC)models have been widely used to address consensus issues in multi-attribute group decision-making(MAGDM)problems with limited resources.However,most researchers have overlooked the decision maker‘(DMs)’confidence levels(CLs)and adjustment willingness implicit in their evaluations.To address these problems,this paper explores a confidence-based MCC model that considers DMs’adjustment willingness in the STN.The proposed model includes several modifications to the traditional trust propagation and consensus optimization models.Firstly,the improved method for measuring CLs of DMs and the confidence-based normalization approach are defined,respectively.Secondly,the bounded trust propagation operator is proposed,which considers the credibility of mediators to complete the STN.Thirdly,the identification rules based on the consensus index and CL are defined,and the MCC model with personalized cost functions and acceptable adjustment thresholds is built to automatically generate adjustment values for non-consensus DMs.Finally,a model to identify the non-cooperative behavior at the element level is established and the hybrid MCC model with persuasion strategies is provided.Finally,a case study is processed to verify the applicability of the proposed model,and comparison and sensitivity analysis are conducted to highlight its benefits.展开更多
基金This work was supported by the National Basic Research Pro-gram of China under Crant No.2007CB311100 Funds of Key Lab of Fujlan Province University Network Security and Cryp- toll1009+3 种基金 the National Science Foundation for Young Scholars of China under Crant No.61001091 Beijing Nature Science Foundation under Crant No. 4122012 ＂Next-Generation Broad-band Wireless Mobile Communication Network＂ National Sci-ence and Technology Major Special Issue Funding under Grant No. 2012ZX03002003 Funding Program for Academic tturmn Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality of Chi-na.
文摘In order to construct the trusted network and realize the trust of network behavior,a new multi-dimensional behavior measurement model based on prediction and control is presented.By using behavior predictive equation,individual similarity function,group similarity function,direct trust assessment function,and generalized predictive control,this model can guarantee the trust of an end user and users in its network.Compared with traditional measurement model,the model considers different characteristics of various networks.The trusted measurement policies established according to different network environments have better adaptability.By constructing trusted group,the threats to trusted group will be reduced greatly.Utilizing trusted group to restrict individuals in network can ensure the fault tolerance of trustworthiness of trusted individuals and group.The simulation shows that this scheme can support behavior measurement more efficiently than traditional ones and the model resists viruses and Trojans more efficiently than older ones.
基金ACKNOWLEDGMENT This work was supported by the National Basic Research Program of China （973 Project） （NO.2007CB311100）, the National Science Foundation for Young Scholars of China （Grant No.61001091）, Beijing Nature Science Foundation（No. 4122012）, ＂next-generation broadband wireless mobile communication network＂ National Science and Technology major Special issue funding（No. 2012ZX03002003）, Funding Program for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality of China and the key technology research and validation issue for the emergency treatment telemedicine public service platform which integrates the military and civilian and bases on the broadband wireless networks（No.2013ZX03006001-005）, the issue belongs to Major national science and technology projects.
文摘The trusted network connection is a hot spot in trusted computing field and the trust measurement and access control technology are used to deal with network security threats in trusted network.But the trusted network connection lacks fine-grained states and real-time measurement support for the client and the authentication mechanism is difficult to apply in the trusted network connection,it is easy to cause the loss of identity privacy.In order to solve the abovedescribed problems,this paper presents a trust measurement scheme suitable for clients in the trusted network,the scheme integrates the following attributes such as authentication mechanism,state measurement,and real-time state measurement and so on,and based on the authentication mechanism and the initial state measurement,the scheme uses the realtime state measurement as the core method to complete the trust measurement for the client.This scheme presented in this paper supports both static and dynamic measurements.Overall,the characteristics of this scheme such as fine granularity,dynamic,real-time state measurement make it possible to make more fine-grained security policy and therefore it overcomes inadequacies existing in the current trusted network connection.
基金the National NaturalScience Foundation of China under Grant90412012 and 60673187
文摘As the information network plays a more and more important role globally, the traditional network theories and technologies, especially those related to network security, can no longer meet the network development requirements. Offering the system with secure and trusted services has become a new focus in network research. This paper first discusses the meaning of and aspects involved in the trusted network. According to this paper, the trusted network should be a network where the network’s and users’ behaviors and their results are always predicted and manageable. The trustworthiness of a network mainly involves three aspects: service provider, information transmission and terminal user. This paper also analyzes the trusted network in terms of trusted model for network/user behaviors, architecture of trusted network, service survivability and network manageability, which is designed to give ideas on solving the problems that may be faced in developing the trusted network.
基金supported in part by Scientific Research Fund of Zhejiang Provincial Education Department under Grant Y202351110in part by Huzhou Science and Technology Plan Project under Grant 2024YZ23+1 种基金in part by Research Fund of National Key Laboratory of Advanced Communication Networks under Grant SCX23641X004in part by Postgraduate Research and Innovation Project of Huzhou University under Grant 2024KYCX50.
文摘Zero Trust Network(ZTN)enhances network security through strict authentication and access control.However,in the ZTN,optimizing flow control to improve the quality of service is still facing challenges.Software Defined Network(SDN)provides solutions through centralized control and dynamic resource allocation,but the existing scheduling methods based on Deep Reinforcement Learning(DRL)are insufficient in terms of convergence speed and dynamic optimization capability.To solve these problems,this paper proposes DRL-AMIR,which is an efficient flow scheduling method for software defined ZTN.This method constructs a flow scheduling optimization model that comprehensively considers service delay,bandwidth occupation,and path hops.Additionally,it balances the differentiated requirements of delay-critical K-flows,bandwidth-intensive D-flows,and background B-flows through adaptiveweighting.Theproposed framework employs a customized state space comprising node labels,link bandwidth,delaymetrics,and path length.It incorporates an action space derived fromnode weights and a hybrid reward function that integrates both single-step and multi-step excitation mechanisms.Based on these components,a hierarchical architecture is designed,effectively integrating the data plane,control plane,and knowledge plane.In particular,the adaptive expert mechanism is introduced,which triggers the shortest path algorithm in the training process to accelerate convergence,reduce trial and error costs,and maintain stability.Experiments across diverse real-world network topologies demonstrate that DRL-AMIR achieves a 15–20%reduction in K-flow transmission delays,a 10–15%improvement in link bandwidth utilization compared to SPR,QoSR,and DRSIR,and a 30%faster convergence speed via adaptive expert mechanisms.
基金supported by the National Natural Science Foundation of China(71901214).
文摘In order to solve the problem of uncertainty and fuzzy information in the process of weapon equipment system selec-tion,a multi-attribute decision-making(MADM)method based on probabilistic hesitant fuzzy set(PHFS)is proposed.Firstly,we introduce the concept of probability and fuzzy entropy to mea-sure the ambiguity,hesitation and uncertainty of probabilistic hesitant fuzzy elements(PHFEs).Sequentially,the expert trust network is constructed,and the importance of each expert in the network can be obtained by calculating the cumulative trust value under multiple trust propagation paths,so as to obtain the expert weight vector.Finally,we put forward an MADM method combining the probabilistic hesitant fuzzy entropy and grey rela-tion analysis(GRA)model,and an illustrative case is employed to prove the feasibility and effectiveness of the method when solving the weapon system selection decision-making problem.
基金supported by National Key R&D Program of China—Industrial Internet Application Demonstration-Sub-topic Intelligent Network Operation and Security Protection(2018YFB1802400).
文摘The important issues of network TCP congestion control are how to compute the link price according to the link status and regulate the data sending rate based on link congestion pricing feedback information.However,it is difficult to predict the congestion state of the link-end accurately at the source.In this paper,we presented an improved NUMFabric algorithm for calculating the overall congestion price.In the proposed scheme,the whole network structure had been obtained by the central control server in the Software Defined Network,and a kind of dual-hierarchy algorithm for calculating overall network congestion price had been demonstrated.In this scheme,the first hierarchy algorithm was set up in a central control server like Opendaylight and the guiding parameter B is obtained based on the intelligent data of global link state information.Based on the historical data,the congestion state of the network and the guiding parameter B is accurately predicted by the machine learning algorithm.The second hierarchy algorithm was installed in the Openflow link and the link price was calculated based on guiding parameter B given by the first algorithm.We evaluate this evolved NUMFabric algorithm in NS3,which demonstrated that the proposed NUMFabric algorithm could efficiently increase the link bandwidth utilization of cloud computing IoT datacenters.
基金Supported by Specialized Research Fund for theDoctoral Programof Higher Education of China (20050013011)
文摘The conception of trusted network connection （TNC） is introduced, and the weakness of TNC to control user＇s action is analyzed. After this, the paper brings out a set of secure access and control model based on access, authorization and control, and related authentication protocol. At last the security of this model is analyzed. The model can improve TNC＇s security of user control and authorization.
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Matrix factorization （MF） has been proved to be a very effective technique for collaborative filtering （ CF）, and hence has been widely adopted in today＇s recommender systems, Yet due to its lack of consideration of the users＇ and items＇ local structures, the recommendation accuracy is not fully satisfied. By taking the trusts among users＇ and between items＇ effect on rating information into consideration, trust-aware recommendation systems （TARS） made a relatively good performance. In this paper, a method of incorporating trust into MF was proposed by building user-based and item-based implicit trust network under different contexts and implementing two implicit trust-based context-aware MF （]TMF） models. Experimental results proved the effectiveness of the methods.
基金funded in part by the National Natural Science Foundation of China(No.12271211)the Open Fund of Digital Fujian Big Data Modeling and Intelligent Computing Institute,Pre-Research Fund of Jimei University.
文摘Purpose-Experts may adjust their assessments through communication and mutual influence,and this dynamic evolution relies on the spread of internal trust relationships.Due to differences in educational backgrounds and knowledge experiences,trust relationships among experts are often incomplete.To address such issues and reduce decision biases,this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network(InSTN).Design/methodology/approach-In this paper,we first define the new trust propagation operators based on the operations of Probability Language Term Set(PLTS)with algebraic t-conorm and t-norm,which are combined with trust aggregation operators to estimate InSTN.The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation.Finally,the particle swarm algorithm(PSO)is used to optimize the expert evaluation to meet the consensus threshold.Findings-This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases.The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods,mainly due to the effective regulation of trust relations in the decision-making process,which reduces decision bias and inconsistencies.Originality/value-This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN.It proposes a redefined trust propagation and aggregation approach to estimate the InSTN.Moreover,the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.
基金supported by the National Natural Science Foundation of China(Nos.61602057 and 11690012)the China Postdoctoral Science Foundation(No.2017M611301)+3 种基金the Science and Technology Department of Jilin Province,China(No.20170520059JH)the Education Department of Jilin Province,China(No.2016311)the Key Laboratory of Symbolic Computation and Knowledge Engineering(No.93K172016K13)the Guangxi Key Laboratory of Trusted Software(No.kx201533)
文摘User-specified trust relations are often very sparse and dynamic, making them difficult to accurately predict from online social media. In addition, trust relations are usually unavailable for most social media platforms.These issues pose a great challenge for predicting trust relations and further building trust networks. In this study,we investigate whether we can predict trust relations via a sparse learning model, and propose to build a trust network without trust relations using only pervasively available interaction data and homophily effect in an online world. In particular, we analyze the reliability of predicting trust relations by interaction behaviors, and provide a principled way to mathematically incorporate interaction behaviors and homophily effect in a novel framework,b Trust. Results of experiments on real-world datasets from Epinions and Ciao demonstrated the effectiveness of the proposed framework. Further experiments were conducted to understand the importance of interaction behaviors and homophily effect in building trust networks.
基金supported in part by the National Natural Science Foundation of China(No.62141211)in part by the Open Project Program of the State Key Laboratory of Mathematical Engineering and Advanced Computing
文摘With the trend of digitalization,intelligence,and networking sweeping the world,functional safety and cyber security are increasingly intertwined and overlapped,evolving into the issue of generalized functional safety.Traditional system reliability technology and network defense technology cannot provide quantifiable design implementation theories and methods.As the cornerstone of software systems,operating systems in particular are in need of efficient safety assurance.The DHR architecture is a mature and comprehensive solution,and it is necessary to implement an OS-level DHR architecture,for which the multi-kernel operating system is a good carrier.The multi-kernel operating system takes the kernel as the processing scenario element and constructs redundancy,heterogeneity,and dynamism on the kernel,so it has the generalized robustness of the DHR architecture.This article analyzes the significance and requirements of OS-level DHR architecture,and systematically explains how the multi-kernel operating system responds to the requirements of OS-level DHR architecture by analyzing the technical routes of multi-kernel operating systems and develops an operating system solution idea for the generalized functionally safety.
文摘The Metaverse is a significant field that is currently receiving considerable attention from both the industry and academia.The transformation of the Metaverse from science fiction to reality is being actively promoted by technology,industry,and capital.However,the development of the Metaverse is still in its early stages,and the system architecture and theoretical technology of the Metaverse are not yet mature.This paper provides a comprehensive analysis of the Metaverse and summarizes its holographic,omnipotent,multidimensional,and multifaceted characteristics.The development of the Metaverse is founded on the relevant infrastructure,and we elaborate on the primary components of the Metaverse infrastructure.Furthermore,we systematically summarize the security risks inherent in the Metaverse infrastructure.Based on this,we propose utilizing the system security technology concept to guide the construction of a Metaverse security protection system from various perspectives at each level of computing,cloud,network,digital assets,and terminals,in order to construct a secure foundation for addressing the Metaverse’s security risks and challenges.
基金This work was partly supported by the 21st Century COE Program"Reconstruction of Social Infrastructure Related to Information Science and Electrical Engineering"in Kyushu University,Japan,and by the National Grand Fundamental Research 973 Program of China under Grant No.2007CB310607the National Natural Science Foundation of China under Grant Nos.60472067,60572131 and JiangSu Education Bureau(Grant No.5KJB510091).
文摘Considering the fact that P2P （Peer-to-Peer） systems are self-organized and autonomous, social-control mechanism （like trust and reputation） is essential to evaluate the trustworthiness of participating peers and to combat the selfish, dishonest and malicious peer behaviors. So, naturally, we advocate that P2P systems that gradually act as an important information infrastructure should be multi-disciplinary research topic, and reflect certain features of our society. So, from economic and social perspective, this paper designs the incentive-compatible reputation feedback scheme based on well-known economic model, and characterizes the social features of trust network in terms of efficiency and cost. Specifically, our framework has two distinctive purposes： first, from high-level perspective, we argue trust system is a special kind of social network, and an accurate characterization of the structural properties of the network can be of fundamental importance to understand the dynamics of the system. Thus, inspired by the concept of weighted small-world, this paper proposes new measurements to characterize the social properties of trust system, that is, high global and local efficiency, and low cost; then, from relative low-level perspective, we argue that reputation feedback is a special kind of information, and it is not free. So, based on economic model, VCG （Vickrey-Clarke-Grove）-like reputation remuneration mechanism is proposed to stimulate rational peers not only to provide reputation feedback, but truthfully offer feedback. Furthermore, considering that trust and reputation is subjective, we classify the trust into functional trust and referral trust, and extend the referral trust to include two factors： similarity and truthfulness, which can efficiently reduce the trust inference error. The preliminary simulation results show the benefits of our proposal and the emergence of certain social properties in trust network.
基金This work has been supported in part by the National Natural Science Foundation of China(NSFC),under grants Nos.72101168,72071135.
文摘Social trust network(STN)and minimum cost consensus(MCC)models have been widely used to address consensus issues in multi-attribute group decision-making(MAGDM)problems with limited resources.However,most researchers have overlooked the decision maker‘(DMs)’confidence levels(CLs)and adjustment willingness implicit in their evaluations.To address these problems,this paper explores a confidence-based MCC model that considers DMs’adjustment willingness in the STN.The proposed model includes several modifications to the traditional trust propagation and consensus optimization models.Firstly,the improved method for measuring CLs of DMs and the confidence-based normalization approach are defined,respectively.Secondly,the bounded trust propagation operator is proposed,which considers the credibility of mediators to complete the STN.Thirdly,the identification rules based on the consensus index and CL are defined,and the MCC model with personalized cost functions and acceptable adjustment thresholds is built to automatically generate adjustment values for non-consensus DMs.Finally,a model to identify the non-cooperative behavior at the element level is established and the hybrid MCC model with persuasion strategies is provided.Finally,a case study is processed to verify the applicability of the proposed model,and comparison and sensitivity analysis are conducted to highlight its benefits.
