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
In an era where artificial intelligence(AI)is permeating many aspects of scientific research activity,what science and technology(S&T)journals can do to uphold research integrity and secure scholarly quality?What ...In an era where artificial intelligence(AI)is permeating many aspects of scientific research activity,what science and technology(S&T)journals can do to uphold research integrity and secure scholarly quality?What kind of revolution is needed in such a rapidly drifting world to hold on to the essential value of science?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
With the rapid development of digital technologies such as big data,cloud computing,and the Internet of Things(loT),data security and privacy protection have become the core challenges facing modern computing systems....With the rapid development of digital technologies such as big data,cloud computing,and the Internet of Things(loT),data security and privacy protection have become the core challenges facing modern computing systems.Traditional security mechanisms are difficult to effectively deal with advanced adversarial attacks due to their reliance on a centralized trust model.In this context,the Trusted Execution Environment(TEE),as a hardware-enabled secure isolation technology,offers a potential solution to protect sensitive computations and data.This paper systematically discusses TEE's technical principle,application status,and future development trend.First,the underlying architecture of TEE and its core characteristics,including isolation,integrity,and confidentiality,are analyzed.Secondly,practical application cases of TEE in fields such as finance,the IoT,artificial intelligence,and privacy computing are studied.Finally,the future development direction of TEE is prospected.展开更多
With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.Th...With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.展开更多
Due to the need for massive device connectivity,low communication latency,and various customizations in 6G architecture,a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integra...Due to the need for massive device connectivity,low communication latency,and various customizations in 6G architecture,a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integrated network scenario.However,the openness and heterogeneity of the 6G network cause the problems of network security.To improve the trustworthiness of 6G networks,we propose a trusted computing-based approach for establishing trust relationships inmulti-cloud scenarios.The proposed method shows the relationship of trust based on dual-level verification.It separates the trustworthy states of multiple complex cloud units in 6G architecture into the state within and between cloud units.Firstly,SM3 algorithm establishes the chain of trust for the system’s trusted boot phase.Then,the remote attestation server(RAS)of distributed cloud units verifies the physical servers.Meanwhile,the physical servers use a ring approach to verify the cloud servers.Eventually,the centralized RAS takes one-time authentication to the critical evidence information of distributed cloud unit servers.Simultaneously,the centralized RAS also verifies the evidence of distributed RAS.We establish our proposed approach in a natural OpenStack-based cloud environment.The simulation results show that the proposed method achieves higher security with less than a 1%system performance loss.展开更多
In recent years,the Industrial Internet and Industry 4.0 came into being.With the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are...In recent years,the Industrial Internet and Industry 4.0 came into being.With the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are also proposed.These applications apply architectures such as distributed learning,resource sharing,and arithmetic trading,which make high demands on identity authentication,asset authentication,resource addressing,and service location.Therefore,an efficient,secure,and trustworthy Industrial Internet identity resolution system is needed.However,most of the traditional identity resolution systems follow DNS architecture or tree structure,which has the risk of a single point of failure and DDoS attack.And they cannot guarantee the security and privacy of digital identity,personal assets,and device information.So we consider a decentralized approach for identity management,identity authentication,and asset verification.In this paper,we propose a distributed trusted active identity resolution system based on the inter-planetary file system(IPFS)and non-fungible token(NFT),which can provide distributed identity resolution services.And we have designed the system architecture,identity service process,load balancing strategy and smart contract service.In addition,we use Jmeter to verify the performance of the system,and the results show that the system has good high concurrent performance and robustness.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
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
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.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
With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in p...With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in privacy protection and data verification,especially for sensitive data.Existing schemes often suffer from inefficiency and high overhead.We propose a privacy protection scheme using BGV homomorphic encryption and Pedersen Secret Sharing.This scheme enables secure computation on encrypted data,with Pedersen sharding and verifying the private key,ensuring data consistency and immutability.The blockchain framework manages key shards,verifies secrets,and aids security auditing.This approach allows for trusted computation without revealing the underlying data.Preliminary results demonstrate the scheme's feasibility in ensuring data privacy and security,making data available but not visible.This study provides an effective solution for data sharing and privacy protection in blockchain applications.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
As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent...As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.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
True friendship is like a strong tree-its roots grow deep through trust,loyalty and care.Unlike casual acquaintances(泛泛之交),real friends stay by your side through life's storms and sunshine.A genuine friendship...True friendship is like a strong tree-its roots grow deep through trust,loyalty and care.Unlike casual acquaintances(泛泛之交),real friends stay by your side through life's storms and sunshine.A genuine friendship begins with honesty.Friends who truly care about you will tell you the truth kindly,even when it's hard.For example,if you make a mistake,a real friend won't laugh but will help you learn.They create a safe space where you can share fears or dreams without judgment-this is called emotional safety.展开更多
Measuring the impact of AI systems The recent 2025 AI Index Report from Stanford University revealed that skepticism about the ethical conduct of AI companies is growing,and trust in fairness is shrinking.There is als...Measuring the impact of AI systems The recent 2025 AI Index Report from Stanford University revealed that skepticism about the ethical conduct of AI companies is growing,and trust in fairness is shrinking.There is also less confidence that personal data will be protected and fewer people believe AI systems are unbiased and free of discrimination.Trust and transparency are essential for AI to deliver on its promises in a safe and responsible way.Governments are stepping up with new AI-related regulations,and international standards such as ISO/IEC 42001 have been developed to support them,but a lot more needs to be done to reduce potential risks and address societal concerns.展开更多
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.
文摘In an era where artificial intelligence(AI)is permeating many aspects of scientific research activity,what science and technology(S&T)journals can do to uphold research integrity and secure scholarly quality?What kind of revolution is needed in such a rapidly drifting world to hold on to the essential value of science?
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.
文摘With the rapid development of digital technologies such as big data,cloud computing,and the Internet of Things(loT),data security and privacy protection have become the core challenges facing modern computing systems.Traditional security mechanisms are difficult to effectively deal with advanced adversarial attacks due to their reliance on a centralized trust model.In this context,the Trusted Execution Environment(TEE),as a hardware-enabled secure isolation technology,offers a potential solution to protect sensitive computations and data.This paper systematically discusses TEE's technical principle,application status,and future development trend.First,the underlying architecture of TEE and its core characteristics,including isolation,integrity,and confidentiality,are analyzed.Secondly,practical application cases of TEE in fields such as finance,the IoT,artificial intelligence,and privacy computing are studied.Finally,the future development direction of TEE is prospected.
文摘With the recent technological developments,massive vehicular ad hoc networks(VANETs)have been established,enabling numerous vehicles and their respective Road Side Unit(RSU)components to communicate with oneanother.The best way to enhance traffic flow for vehicles and traffic management departments is to share thedata they receive.There needs to be more protection for the VANET systems.An effective and safe methodof outsourcing is suggested,which reduces computation costs by achieving data security using a homomorphicmapping based on the conjugate operation of matrices.This research proposes a VANET-based data outsourcingsystem to fix the issues.To keep data outsourcing secure,the suggested model takes cryptography models intoaccount.Fog will keep the generated keys for the purpose of vehicle authentication.For controlling and overseeingthe outsourced data while preserving privacy,the suggested approach considers the Trusted Certified Auditor(TCA).Using the secret key,TCA can identify the genuine identity of VANETs when harmful messages aredetected.The proposed model develops a TCA-based unique static vehicle labeling system using cryptography(TCA-USVLC)for secure data outsourcing and privacy preservation in VANETs.The proposed model calculatesthe trust of vehicles in 16 ms for an average of 180 vehicles and achieves 98.6%accuracy for data encryption toprovide security.The proposedmodel achieved 98.5%accuracy in data outsourcing and 98.6%accuracy in privacypreservation in fog-enabled VANETs.Elliptical curve cryptography models can be applied in the future for betterencryption and decryption rates with lightweight cryptography operations.
基金This work was supported by the Ministry of Education and China Mobile Research Fund Project(MCM20200102)the 173 Project(No.2019-JCJQ-ZD-342-00)+2 种基金the National Natural Science Foundation of China(No.U19A2081)the Fundamental Research Funds for the Central Universities(No.2023SCU12129)the Science and Engineering Connotation Development Project of Sichuan University(No.2020SCUNG129).
文摘Due to the need for massive device connectivity,low communication latency,and various customizations in 6G architecture,a distributed cloud deployment approach will be more relevant to the space-air-ground-sea integrated network scenario.However,the openness and heterogeneity of the 6G network cause the problems of network security.To improve the trustworthiness of 6G networks,we propose a trusted computing-based approach for establishing trust relationships inmulti-cloud scenarios.The proposed method shows the relationship of trust based on dual-level verification.It separates the trustworthy states of multiple complex cloud units in 6G architecture into the state within and between cloud units.Firstly,SM3 algorithm establishes the chain of trust for the system’s trusted boot phase.Then,the remote attestation server(RAS)of distributed cloud units verifies the physical servers.Meanwhile,the physical servers use a ring approach to verify the cloud servers.Eventually,the centralized RAS takes one-time authentication to the critical evidence information of distributed cloud unit servers.Simultaneously,the centralized RAS also verifies the evidence of distributed RAS.We establish our proposed approach in a natural OpenStack-based cloud environment.The simulation results show that the proposed method achieves higher security with less than a 1%system performance loss.
基金supported by the National Natural Science Foundation of China(No.92267301).
文摘In recent years,the Industrial Internet and Industry 4.0 came into being.With the development of modern industrial intelligent manufacturing technology,digital twins,Web3 and many other digital entity applications are also proposed.These applications apply architectures such as distributed learning,resource sharing,and arithmetic trading,which make high demands on identity authentication,asset authentication,resource addressing,and service location.Therefore,an efficient,secure,and trustworthy Industrial Internet identity resolution system is needed.However,most of the traditional identity resolution systems follow DNS architecture or tree structure,which has the risk of a single point of failure and DDoS attack.And they cannot guarantee the security and privacy of digital identity,personal assets,and device information.So we consider a decentralized approach for identity management,identity authentication,and asset verification.In this paper,we propose a distributed trusted active identity resolution system based on the inter-planetary file system(IPFS)and non-fungible token(NFT),which can provide distributed identity resolution services.And we have designed the system architecture,identity service process,load balancing strategy and smart contract service.In addition,we use Jmeter to verify the performance of the system,and the results show that the system has good high concurrent performance and robustness.
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.
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.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
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.
基金supported by the National Key Research and Development Plan in China(Grant No.2020YFB1005500)。
文摘With increasing demand for data circulation,ensuring data security and privacy is paramount,specifically protecting privacy while maximizing utility.Blockchain,while decentralized and transparent,faces challenges in privacy protection and data verification,especially for sensitive data.Existing schemes often suffer from inefficiency and high overhead.We propose a privacy protection scheme using BGV homomorphic encryption and Pedersen Secret Sharing.This scheme enables secure computation on encrypted data,with Pedersen sharding and verifying the private key,ensuring data consistency and immutability.The blockchain framework manages key shards,verifies secrets,and aids security auditing.This approach allows for trusted computation without revealing the underlying data.Preliminary results demonstrate the scheme's feasibility in ensuring data privacy and security,making data available but not visible.This study provides an effective solution for data sharing and privacy protection in blockchain applications.
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 in part by the National Natural Science Foundation of China(Grant Nos.62201276,62350001,U22B2026,and 62471248)Innovation Program for Quantum Science and Technology(Grant No.2021ZD0300701)+1 种基金the Key R&D Program(Industry Foresight and Key Core Technologies)of Jiangsu Province(Grant No.BE2022071)Natural Science Research of Jiangsu Higher Education Institutions of China(Grant No.22KJB510007)。
文摘As the first stage of the quantum Internet,quantum key distribution(QKD)networks hold the promise of providing long-term security for diverse users.Most existing QKD networks have been constructed based on independent QKD protocols,and they commonly rely on the deployment of single-protocol trusted relay chains for long reach.Driven by the evolution of QKD protocols,large-scale QKD networking is expected to migrate from a single-protocol to a multi-protocol paradigm,during which some useful evolutionary elements for the later stages of the quantum Internet may be incorporated.In this work,we delve into a pivotal technique for large-scale QKD networking,namely,multi-protocol relay chaining.A multi-protocol relay chain is established by connecting a set of trusted/untrusted relays relying on multiple QKD protocols between a pair of QKD nodes.The structures of diverse multi-protocol relay chains are described,based on which the associated model is formulated and the policies are defined for the deployment of multi-protocol relay chains.Furthermore,we propose three multi-protocol relay chaining heuristics.Numerical simulations indicate that the designed heuristics can effectively reduce the number of trusted relays deployed and enhance the average security level versus the commonly used single-protocol trusted relay chaining methods on backbone network topologies.
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.
文摘True friendship is like a strong tree-its roots grow deep through trust,loyalty and care.Unlike casual acquaintances(泛泛之交),real friends stay by your side through life's storms and sunshine.A genuine friendship begins with honesty.Friends who truly care about you will tell you the truth kindly,even when it's hard.For example,if you make a mistake,a real friend won't laugh but will help you learn.They create a safe space where you can share fears or dreams without judgment-this is called emotional safety.
文摘Measuring the impact of AI systems The recent 2025 AI Index Report from Stanford University revealed that skepticism about the ethical conduct of AI companies is growing,and trust in fairness is shrinking.There is also less confidence that personal data will be protected and fewer people believe AI systems are unbiased and free of discrimination.Trust and transparency are essential for AI to deliver on its promises in a safe and responsible way.Governments are stepping up with new AI-related regulations,and international standards such as ISO/IEC 42001 have been developed to support them,but a lot more needs to be done to reduce potential risks and address societal concerns.
