In the "Internet +" convergence environment to promote the development of enterprises, the need to rely on "Internet +" industrial convergence index and the actual work system of enterprise financi...In the "Internet +" convergence environment to promote the development of enterprises, the need to rely on "Internet +" industrial convergence index and the actual work system of enterprise financial management innovation, actively improve enterprise financial management problems existing, which in turn will "Internet +" industrial convergence environment characteristics of enterprise financial management. This paper focuses on the study of enterprise financial management under the environment of "Internet +" industrial integration, clarifying the characteristics and existing problems of financial management, and then puts forward relevant innovation strategies according to the performance of various problems to ensure that enterprise financial management meets the specific requirements of "Internet +" industrial integration.展开更多
With the rapid development of the industrial Internet,the network security environment has become increasingly complex and variable.Intrusion detection,a core technology for ensuring the security of industrial control...With the rapid development of the industrial Internet,the network security environment has become increasingly complex and variable.Intrusion detection,a core technology for ensuring the security of industrial control systems,faces the challenge of unbalanced data samples,particularly the low detection rates for minority class attack samples.Therefore,this paper proposes a data enhancement method for intrusion detection in the industrial Internet based on a Self-Attention Wasserstein Generative Adversarial Network(SA-WGAN)to address the low detection rates of minority class attack samples in unbalanced intrusion detection scenarios.The proposed method integrates a selfattention mechanism with a Wasserstein Generative Adversarial Network(WGAN).The self-attention mechanism automatically learns important features from the input data and assigns different weights to emphasize the key features related to intrusion behaviors,providing strong guidance for subsequent data generation.The WGAN generates new data samples through adversarial training to expand the original dataset.In the SA-WGAN framework,the WGAN directs the data generation process based on the key features extracted by the self-attention mechanism,ensuring that the generated samples exhibit both diversity and similarity to real data.Experimental results demonstrate that the SA-WGAN-based data enhancement method significantly improves detection performance for attack samples from minority classes,addresses issues of insufficient data and category imbalance,and enhances the generalization ability and overall performance of the intrusion detection model.展开更多
Under the current background of an information society,the digital transformation of enterprises has become a necessary means to enhance the competitiveness of enterprises.This article is based on the industrial Inter...Under the current background of an information society,the digital transformation of enterprises has become a necessary means to enhance the competitiveness of enterprises.This article is based on the industrial Internet platform,the digital planning and architecture of enterprises research.First,we analyze the current challenges of digital transformation and the development opportunities brought by the industrial Internet.Then,we propose a digital planning method based on the industrial Internet platform,which takes the full connectivity of people,machine and things and intelligent decision making as the core,takes data collection,processing,analysis and application as the main line,and finally forms the top-level design of the digital transformation of enterprises.At the same time,we also built an industrial Internet platform architecture model,including the previous end perception layer,network transmission layer,platform service layer,and application innovation layer for four levels,to support enterprises in innovative applications and decision support under the industrial Internet environment.Research shows that this kind of enterprise digital planning and architecture based on an industrial Internet platform can effectively promote enterprises to achieve business model innovation,system innovation,and strengthen the flexibility and agility of enterprises to respond to market changes.The results of this research not only have important theoretical and practical significance for guiding enterprises to carry out digital planning and build an industrial Internet platform,but also provide useful reference for relevant policy formulation.展开更多
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
Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from...Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.展开更多
As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds...As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.展开更多
The year 2024 marks the 10th anniversary of the strategic goal of building China into a cyberpower proposed by General Secretary Xi Jinping.It is also the 30th anniversary of China's full-function access to the in...The year 2024 marks the 10th anniversary of the strategic goal of building China into a cyberpower proposed by General Secretary Xi Jinping.It is also the 30th anniversary of China's full-function access to the internet,and launch of China's law-based cyberspace governance.Over the past three decades,under the strong leadership of the Central Committee of the Communist Party of China(CPC)and the State Council,and guided by the major strategies regarding cyberpower and digital China,China's Internet industry kept forging ahead with a strong momentum.It has travelled an extraordinary journey,and achieved leapfrog development.展开更多
Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the pro...Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.展开更多
The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new ch...The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.展开更多
The Industrial Internet is a promising technology combining industrial systems with Internet connectivity to significantly improve the product efficiency and reduce production cost by cooperating with intelligent devi...The Industrial Internet is a promising technology combining industrial systems with Internet connectivity to significantly improve the product efficiency and reduce production cost by cooperating with intelligent devices,in which the advanced computing,big data analysis and intelligent perception techniques have been involved.This paper comprehensively surveys the recent advances of the Industrial Internet,including reference architectures,key technologies,relative applications and future challenges.Reference architectures which have been proposed for different application scenarios and their corresponding characteristics are summarized.Key technologies,such as cloud computing,mobile edge computing,fog computing,which are classified according to different layers in the architecture,are presented to support a variety of applications in the Industrial Internet.Meanwhile,future challenges and research trends are discussed as well to promote further research of the Industrial Internet.展开更多
Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based ...Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.展开更多
To ensure the safe operation of industrial digital twins network and avoid the harm to the system caused by hacker invasion,a series of discussions on network security issues are carried out based on game theory.From ...To ensure the safe operation of industrial digital twins network and avoid the harm to the system caused by hacker invasion,a series of discussions on network security issues are carried out based on game theory.From the perspective of the life cycle of network vulnerabilities,mining and repairing vulnerabilities are analyzed by applying evolutionary game theory.The evolution process of knowledge sharing among white hats under various conditions is simulated,and a game model of the vulnerability patch cooperative development strategy among manufacturers is constructed.On this basis,the differential evolution is introduced into the update mechanism of the Wolf Colony Algorithm(WCA)to produce better replacement individuals with greater probability from the perspective of both attack and defense.Through the simulation experiment,it is found that the convergence speed of the probability(X)of white Hat 1 choosing the knowledge sharing policy is related to the probability(x0)of white Hat 2 choosing the knowledge sharing policy initially,and the probability(y0)of white hat 2 choosing the knowledge sharing policy initially.When y0?0.9,X converges rapidly in a relatively short time.When y0 is constant and x0 is small,the probability curve of the“cooperative development”strategy converges to 0.It is concluded that the higher the trust among the white hat members in the temporary team,the stronger their willingness to share knowledge,which is conducive to the mining of loopholes in the system.The greater the probability of a hacker attacking the vulnerability before it is fully disclosed,the lower the willingness of manufacturers to choose the"cooperative development"of vulnerability patches.Applying the improved wolf colonyco-evolution algorithm can obtain the equilibrium solution of the"attack and defense game model",and allocate the security protection resources according to the importance of nodes.This study can provide an effective solution to protect the network security for digital twins in the industry.展开更多
COVID-19 pandemic has accelerated the re-shaping of globalized manufacturing industry.Achieving a high level of resilience is thereby a recognized,essential ability of future manufacturing systems with the advances in...COVID-19 pandemic has accelerated the re-shaping of globalized manufacturing industry.Achieving a high level of resilience is thereby a recognized,essential ability of future manufacturing systems with the advances in smart manufacturing and Industry 4.0.In this work,a conceptual framework for resilient manufacturing strategy enabled by Industrial Internet is proposed.It is elaborated as a four-phase,closed-loop process that centered on proactive industry assessment.Key enabling technologies for the proposed framework are outlined in data acquisition and management,big data analysis,intelligent services,and others.Industrial Internet-enabled implementations in China in response to COVID-19 have then been reviewed and discussed from 3Rs’perspective,i.e.manufacturer capacity Recovery,supply chain Resilience and emergency Response.It is suggested that an industry-specific and comprehensive selection coordinated with the guiding policy and supporting regulations should be performed at the national,at least regional level.展开更多
The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the appl...The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the application of ultra-reliable and low latency communications(URLLC) in the 5G system. The data analysis model represented by digital twins isthe core of IIoT development in the manufacturing industry. In this paper, the efforts of3GPP are introduced for the development of URLLC in reducing delay and enhancing reliability,as well as the research on little jitter and high transmission efficiency. The enhancedkey technologies required in the IIoT are also analyzed. Finally, digital twins are analyzedaccording to the actual IIoT situation.展开更多
The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0...The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0,intelligent transformation is taking place in the industrial field.As a new concept,an industrial IoT system has also attracted the attention of industry and academia.In an actual industrial scenario,a large number of devices will generate numerous industrial datasets.The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing.However,privacy issues may seriously harmed interests of users.In this article,we summarize privacy issues in a cloud-or an edge-based industrial IoT system.The privacy analysis includes data privacy,location privacy,query and identity privacy.In addition,we also review privacy solutions when applying software defined network and blockchain under the above two systems.Next,we analyze the computational complexity and privacy protection performance of these solutions.Finally,we discuss open issues to facilitate further studies.展开更多
By identifying and responding to any malicious behavior that could endanger the system,the Intrusion Detection System(IDS)is crucial for preserving the security of the Industrial Internet of Things(IIoT)network.The be...By identifying and responding to any malicious behavior that could endanger the system,the Intrusion Detection System(IDS)is crucial for preserving the security of the Industrial Internet of Things(IIoT)network.The benefit of anomaly-based IDS is that they are able to recognize zeroday attacks due to the fact that they do not rely on a signature database to identify abnormal activity.In order to improve control over datasets and the process,this study proposes using an automated machine learning(AutoML)technique to automate the machine learning processes for IDS.Our groundbreaking architecture,known as AID4I,makes use of automatic machine learning methods for intrusion detection.Through automation of preprocessing,feature selection,model selection,and hyperparameter tuning,the objective is to identify an appropriate machine learning model for intrusion detection.Experimental studies demonstrate that the AID4I framework successfully proposes a suitablemodel.The integrity,security,and confidentiality of data transmitted across the IIoT network can be ensured by automating machine learning processes in the IDS to enhance its capacity to identify and stop threatening activities.With a comprehensive solution that takes advantage of the latest advances in automated machine learning methods to improve network security,AID4I is a powerful and effective instrument for intrusion detection.In preprocessing module,three distinct imputation methods are utilized to handle missing data,ensuring the robustness of the intrusion detection system in the presence of incomplete information.Feature selection module adopts a hybrid approach that combines Shapley values and genetic algorithm.The Parameter Optimization module encompasses a diverse set of 14 classification methods,allowing for thorough exploration and optimization of the parameters associated with each algorithm.By carefully tuning these parameters,the framework enhances its adaptability and accuracy in identifying potential intrusions.Experimental results demonstrate that the AID4I framework can achieve high levels of accuracy in detecting network intrusions up to 14.39%on public datasets,outperforming traditional intrusion detection methods while concurrently reducing the elapsed time for training and testing.展开更多
With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smar...With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be addressed.The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems.Unfortunately,it still suffers from the problem of key exposure.In order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 algorithm.This scheme boasts strong key insulation and secure keyupdates.Our scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud environments.Finally,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.展开更多
The Industrial Internet of Things(IIoT)has been growing for presentations in industry in recent years.Security for the IIoT has unavoidably become a problem in terms of creating safe applications.Due to continual need...The Industrial Internet of Things(IIoT)has been growing for presentations in industry in recent years.Security for the IIoT has unavoidably become a problem in terms of creating safe applications.Due to continual needs for new functionality,such as foresight,the number of linked devices in the industrial environment increases.Certification of fewer signatories gives strong authentication solutions and prevents trustworthy third parties from being publicly certified among available encryption instruments.Hence this blockchain-based endpoint protection platform(BCEPP)has been proposed to validate the network policies and reduce overall latency in isolation or hold endpoints.A resolver supports the encoded model as an input;network functions can be optimized as an output in an infrastructure network.The configuration of the virtual network functions(VNFs)involved fulfills network characteristics.The output ensures that the final service is supplied at the least cost,including processing time and network latency.According to the findings of this comparison,our design is better suited to simplified trust management in IIoT devices.Thus,the experimental results show the adaptability and resilience of our suggested confidence model against behavioral changes in hostile settings in IIoT networks.The experimental results show that our proposed method,BCEPP,has the following,when compared to other methods:high computational cost of 95.3%,low latency ratio of 28.5%,increased data transmitting rate up to 94.1%,enhanced security rate of 98.6%,packet reception ratio of 96.1%,user satisfaction index of 94.5%,and probability ratio of 33.8%.展开更多
The emergence of industry 4.0 stems from research that has received a great deal of attention in the last few decades.Consequently,there has been a huge paradigm shift in the manufacturing and production sectors.Howev...The emergence of industry 4.0 stems from research that has received a great deal of attention in the last few decades.Consequently,there has been a huge paradigm shift in the manufacturing and production sectors.However,this poses a challenge for cybersecurity and highlights the need to address the possible threats targeting(various pillars of)industry 4.0.However,before providing a concrete solution certain aspect need to be researched,for instance,cybersecurity threats and privacy issues in the industry.To fill this gap,this paper discusses potential solutions to cybersecurity targeting this industry and highlights the consequences of possible attacks and countermeasures(in detail).In particular,the focus of the paper is on investigating the possible cyber-attacks targeting 4 layers of IIoT that is one of the key pillars of Industry 4.0.Based on a detailed review of existing literature,in this study,we have identified possible cyber threats,their consequences,and countermeasures.Further,we have provided a comprehensive framework based on an analysis of cybersecurity and privacy challenges.The suggested framework provides for a deeper understanding of the current state of cybersecurity and sets out directions for future research and applications.展开更多
Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various applications.Therefore,a novel localisation algorithm is proposed for noisy range measurements in IIoT networks...Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various applications.Therefore,a novel localisation algorithm is proposed for noisy range measurements in IIoT networks.The position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position estimation.Therefore,the AMs selection algorithm for the localisation of BMs in the IIoT network is introduced.Only those AMs will participate in the localisation process,which increases the accuracy of the final location estimate.Then,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement noise.The results are compared with the state‐of‐the‐art and verified through numerous simulations.展开更多
文摘In the "Internet +" convergence environment to promote the development of enterprises, the need to rely on "Internet +" industrial convergence index and the actual work system of enterprise financial management innovation, actively improve enterprise financial management problems existing, which in turn will "Internet +" industrial convergence environment characteristics of enterprise financial management. This paper focuses on the study of enterprise financial management under the environment of "Internet +" industrial integration, clarifying the characteristics and existing problems of financial management, and then puts forward relevant innovation strategies according to the performance of various problems to ensure that enterprise financial management meets the specific requirements of "Internet +" industrial integration.
基金supported by the National Natural Science Foundation of China(62473341)Key Technologies R&D Program of Henan Province(242102211071,252102211086,252102210166).
文摘With the rapid development of the industrial Internet,the network security environment has become increasingly complex and variable.Intrusion detection,a core technology for ensuring the security of industrial control systems,faces the challenge of unbalanced data samples,particularly the low detection rates for minority class attack samples.Therefore,this paper proposes a data enhancement method for intrusion detection in the industrial Internet based on a Self-Attention Wasserstein Generative Adversarial Network(SA-WGAN)to address the low detection rates of minority class attack samples in unbalanced intrusion detection scenarios.The proposed method integrates a selfattention mechanism with a Wasserstein Generative Adversarial Network(WGAN).The self-attention mechanism automatically learns important features from the input data and assigns different weights to emphasize the key features related to intrusion behaviors,providing strong guidance for subsequent data generation.The WGAN generates new data samples through adversarial training to expand the original dataset.In the SA-WGAN framework,the WGAN directs the data generation process based on the key features extracted by the self-attention mechanism,ensuring that the generated samples exhibit both diversity and similarity to real data.Experimental results demonstrate that the SA-WGAN-based data enhancement method significantly improves detection performance for attack samples from minority classes,addresses issues of insufficient data and category imbalance,and enhances the generalization ability and overall performance of the intrusion detection model.
文摘Under the current background of an information society,the digital transformation of enterprises has become a necessary means to enhance the competitiveness of enterprises.This article is based on the industrial Internet platform,the digital planning and architecture of enterprises research.First,we analyze the current challenges of digital transformation and the development opportunities brought by the industrial Internet.Then,we propose a digital planning method based on the industrial Internet platform,which takes the full connectivity of people,machine and things and intelligent decision making as the core,takes data collection,processing,analysis and application as the main line,and finally forms the top-level design of the digital transformation of enterprises.At the same time,we also built an industrial Internet platform architecture model,including the previous end perception layer,network transmission layer,platform service layer,and application innovation layer for four levels,to support enterprises in innovative applications and decision support under the industrial Internet environment.Research shows that this kind of enterprise digital planning and architecture based on an industrial Internet platform can effectively promote enterprises to achieve business model innovation,system innovation,and strengthen the flexibility and agility of enterprises to respond to market changes.The results of this research not only have important theoretical and practical significance for guiding enterprises to carry out digital planning and build an industrial Internet platform,but also provide useful reference for relevant policy formulation.
基金supported by the National Natural Science Foundation of China(U22B2026)the ZTE Industry-Academia-Research Project(HC-CN-20221029003,IA20230628015)。
文摘With the introduction of 5G,users and devices can access the industrial network from anywhere in the world.Therefore,traditional perimeter-based security technologies for industrial networks can no longer work well.To solve this problem,a new security model called Zero Trust(ZT)is desired,which believes in“never trust and always verify”.Every time the asset in the industrial network is accessed,the subject is authenticated and its trustworthiness is assessed.In this way,the asset in industrial network can be well protected,whether the subject is in the internal network or the external network.However,in order to construct the zero trust model in the 5G Industrial Internet collaboration system,there are still many problems to be solved.In this paper,we first introduce the security issues in the 5G Industrial Internet collaboration system,and illustrate the zero trust architecture.Then,we analyze the gap between existing security techniques and the zero trust architecture.Finally,we discuss several potential security techniques that can be used to implement the zero trust model.The purpose of this paper is to point out the further direction for the realization of the Zero Trust Architecture(ZTA)in the 5G Industrial Internet collaboration system.
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)Henan Provincial Science and Technology Research Project(No.252102211085,No.252102211105)+3 种基金Endogenous Security Cloud Network Convergence R&D Center(No.602431011PQ1)The Special Project for Research and Development in Key Areas of Guangdong Province(No.2021ZDZX1098)The Stabilization Support Program of Science,Technology and Innovation Commission of Shenzhen Municipality(No.20231128083944001)The Key scientific research projects of Henan higher education institutions(No.24A520042).
文摘Existing feature selection methods for intrusion detection systems in the Industrial Internet of Things often suffer from local optimality and high computational complexity.These challenges hinder traditional IDS from effectively extracting features while maintaining detection accuracy.This paper proposes an industrial Internet ofThings intrusion detection feature selection algorithm based on an improved whale optimization algorithm(GSLDWOA).The aim is to address the problems that feature selection algorithms under high-dimensional data are prone to,such as local optimality,long detection time,and reduced accuracy.First,the initial population’s diversity is increased using the Gaussian Mutation mechanism.Then,Non-linear Shrinking Factor balances global exploration and local development,avoiding premature convergence.Lastly,Variable-step Levy Flight operator and Dynamic Differential Evolution strategy are introduced to improve the algorithm’s search efficiency and convergence accuracy in highdimensional feature space.Experiments on the NSL-KDD and WUSTL-IIoT-2021 datasets demonstrate that the feature subset selected by GSLDWOA significantly improves detection performance.Compared to the traditional WOA algorithm,the detection rate and F1-score increased by 3.68%and 4.12%.On the WUSTL-IIoT-2021 dataset,accuracy,recall,and F1-score all exceed 99.9%.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(RS-2023-00242528,50%)supported by the Korea Internet&Security Agency(KISA)through the Information Security Specialized University Support Project(50%).
文摘As attack techniques evolve and data volumes increase,the integration of artificial intelligence-based security solutions into industrial control systems has become increasingly essential.Artificial intelligence holds significant potential to improve the operational efficiency and cybersecurity of these systems.However,its dependence on cyber-based infrastructures expands the attack surface and introduces the risk that adversarial manipulations of artificial intelligence models may cause physical harm.To address these concerns,this study presents a comprehensive review of artificial intelligence-driven threat detection methods and adversarial attacks targeting artificial intelligence within industrial control environments,examining both their benefits and associated risks.A systematic literature review was conducted across major scientific databases,including IEEE,Elsevier,Springer Nature,ACM,MDPI,and Wiley,covering peer-reviewed journal and conference papers published between 2017 and 2026.Studies were selected based on predefined inclusion and exclusion criteria following a structured screening process.Based on an analysis of 101 selected studies,this survey categorizes artificial intelligence-based threat detection approaches across the physical,control,and application layers of industrial control systems and examines poisoning,evasion,and extraction attacks targeting industrial artificial intelligence.The findings identify key research trends,highlight unresolved security challenges,and discuss implications for the secure deployment of artificial intelligence-enabled cybersecurity solutions in industrial control systems.
文摘The year 2024 marks the 10th anniversary of the strategic goal of building China into a cyberpower proposed by General Secretary Xi Jinping.It is also the 30th anniversary of China's full-function access to the internet,and launch of China's law-based cyberspace governance.Over the past three decades,under the strong leadership of the Central Committee of the Communist Party of China(CPC)and the State Council,and guided by the major strategies regarding cyberpower and digital China,China's Internet industry kept forging ahead with a strong momentum.It has travelled an extraordinary journey,and achieved leapfrog development.
基金This research was supported by the National Natural Science Foundation of China(61991400,61991403,and 61991404)China Institute of Engineering Consulting Research Project(2019-ZD-12)the 2020 Science and Technology Major Project of Liaoning Province(2020JH1/10100008),China.
文摘Based on the analysis of the characteristics and operation status of the process industry,as well as the development of the global intelligent manufacturing industry,a new mode of intelligent manufacturing for the process industry,namely,deep integration of industrial artificial intelligence and the Industrial Internet with the process industry,is proposed.This paper analyzes the development status of the existing three-tier structure of the process industry,which consists of the enterprise resource planning,the manufacturing execution system,and the process control system,and examines the decision-making,control,and operation management adopted by process enterprises.Based on this analysis,it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system.Finally,this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.
基金supported in part by the National Science Foundation Project of China (61931001, 61873026)the National Key R&D Program of China (2017YFC0820700)
文摘The industrial Internet of Things(IoT)is a trend of factory development and a basic condition of intelligent factory.It is very important to ensure the security of data transmission in industrial IoT.Applying a new chaotic secure communication scheme to address the security problem of data transmission is the main contribution of this paper.The scheme is proposed and studied based on the synchronization of different-structure fractional-order chaotic systems with different order.The Lyapunov stability theory is used to prove the synchronization between the fractional-order drive system and the response system.The encryption and decryption process of the main data signals is implemented by using the n-shift encryption principle.We calculate and analyze the key space of the scheme.Numerical simulations are introduced to show the effectiveness of theoretical approach we proposed.
基金the State Major Science and Technology Special Projects(Grant 2018ZX03001023-005)the National Natural Science Foundation of China under Grant No.61831002,61728101,and 61671074the Beijing Natural Science Foundation under Grant No.JQ18016.
文摘The Industrial Internet is a promising technology combining industrial systems with Internet connectivity to significantly improve the product efficiency and reduce production cost by cooperating with intelligent devices,in which the advanced computing,big data analysis and intelligent perception techniques have been involved.This paper comprehensively surveys the recent advances of the Industrial Internet,including reference architectures,key technologies,relative applications and future challenges.Reference architectures which have been proposed for different application scenarios and their corresponding characteristics are summarized.Key technologies,such as cloud computing,mobile edge computing,fog computing,which are classified according to different layers in the architecture,are presented to support a variety of applications in the Industrial Internet.Meanwhile,future challenges and research trends are discussed as well to promote further research of the Industrial Internet.
文摘Considered as a top priority of industrial devel- opment, Industry 4.0 （or Industrie 4.0 as the German ver- sion） has being highlighted as the pursuit of both academy and practice in companies. In this paper, based on the review of state of art and also the state of practice in dif- ferent countries, shortcomings have been revealed as the lacking of applicable framework for the implementation of Industrie 4.0. Therefore, in order to shed some light on the knowledge of the details, a reference architecture is developed, where four perspectives namely manufacturing process, devices, software and engineering have been highlighted. Moreover, with a view on the importance of Cyber-Physical systems, the structure of Cyber-Physical System are established for the in-depth analysis. Further cases with the usage of Cyber-Physical System are also arranged, which attempts to provide some implications to match the theoretical findings together with the experience of companies. In general, results of this paper could be useful for the extending on the theoretical understanding of Industrie 4.0. Additionally, applied framework and proto- types based on the usage of Cyber-Physical Systems are also potential to help companies to design the layout of sensor nets, to achieve coordination and controlling of smart machines, to realize synchronous production with systematic structure, and to extend the usage of information and communication technologies to the maintenance scheduling.
文摘To ensure the safe operation of industrial digital twins network and avoid the harm to the system caused by hacker invasion,a series of discussions on network security issues are carried out based on game theory.From the perspective of the life cycle of network vulnerabilities,mining and repairing vulnerabilities are analyzed by applying evolutionary game theory.The evolution process of knowledge sharing among white hats under various conditions is simulated,and a game model of the vulnerability patch cooperative development strategy among manufacturers is constructed.On this basis,the differential evolution is introduced into the update mechanism of the Wolf Colony Algorithm(WCA)to produce better replacement individuals with greater probability from the perspective of both attack and defense.Through the simulation experiment,it is found that the convergence speed of the probability(X)of white Hat 1 choosing the knowledge sharing policy is related to the probability(x0)of white Hat 2 choosing the knowledge sharing policy initially,and the probability(y0)of white hat 2 choosing the knowledge sharing policy initially.When y0?0.9,X converges rapidly in a relatively short time.When y0 is constant and x0 is small,the probability curve of the“cooperative development”strategy converges to 0.It is concluded that the higher the trust among the white hat members in the temporary team,the stronger their willingness to share knowledge,which is conducive to the mining of loopholes in the system.The greater the probability of a hacker attacking the vulnerability before it is fully disclosed,the lower the willingness of manufacturers to choose the"cooperative development"of vulnerability patches.Applying the improved wolf colonyco-evolution algorithm can obtain the equilibrium solution of the"attack and defense game model",and allocate the security protection resources according to the importance of nodes.This study can provide an effective solution to protect the network security for digital twins in the industry.
基金Supported by Natural Science Foundation of Zhejiang Province(Grant No.LY19E050019).
文摘COVID-19 pandemic has accelerated the re-shaping of globalized manufacturing industry.Achieving a high level of resilience is thereby a recognized,essential ability of future manufacturing systems with the advances in smart manufacturing and Industry 4.0.In this work,a conceptual framework for resilient manufacturing strategy enabled by Industrial Internet is proposed.It is elaborated as a four-phase,closed-loop process that centered on proactive industry assessment.Key enabling technologies for the proposed framework are outlined in data acquisition and management,big data analysis,intelligent services,and others.Industrial Internet-enabled implementations in China in response to COVID-19 have then been reviewed and discussed from 3Rs’perspective,i.e.manufacturer capacity Recovery,supply chain Resilience and emergency Response.It is suggested that an industry-specific and comprehensive selection coordinated with the guiding policy and supporting regulations should be performed at the national,at least regional level.
文摘The industrial Internet of Things (IIoT) is an important engine for manufacturingenterprises to provide intelligent products and services. With the development of IIoT, moreand more attention has been paid to the application of ultra-reliable and low latency communications(URLLC) in the 5G system. The data analysis model represented by digital twins isthe core of IIoT development in the manufacturing industry. In this paper, the efforts of3GPP are introduced for the development of URLLC in reducing delay and enhancing reliability,as well as the research on little jitter and high transmission efficiency. The enhancedkey technologies required in the IIoT are also analyzed. Finally, digital twins are analyzedaccording to the actual IIoT situation.
基金the National Natural Science Foundation of China(Grant No.61871023 and 61931001)Beijing Natural Science Foundation(Grant No.4202054).
文摘The concept of Internet of Everything is like a revolutionary storm,bringing the whole society closer together.Internet of Things(IoT)has played a vital role in the process.With the rise of the concept of Industry 4.0,intelligent transformation is taking place in the industrial field.As a new concept,an industrial IoT system has also attracted the attention of industry and academia.In an actual industrial scenario,a large number of devices will generate numerous industrial datasets.The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing.However,privacy issues may seriously harmed interests of users.In this article,we summarize privacy issues in a cloud-or an edge-based industrial IoT system.The privacy analysis includes data privacy,location privacy,query and identity privacy.In addition,we also review privacy solutions when applying software defined network and blockchain under the above two systems.Next,we analyze the computational complexity and privacy protection performance of these solutions.Finally,we discuss open issues to facilitate further studies.
文摘By identifying and responding to any malicious behavior that could endanger the system,the Intrusion Detection System(IDS)is crucial for preserving the security of the Industrial Internet of Things(IIoT)network.The benefit of anomaly-based IDS is that they are able to recognize zeroday attacks due to the fact that they do not rely on a signature database to identify abnormal activity.In order to improve control over datasets and the process,this study proposes using an automated machine learning(AutoML)technique to automate the machine learning processes for IDS.Our groundbreaking architecture,known as AID4I,makes use of automatic machine learning methods for intrusion detection.Through automation of preprocessing,feature selection,model selection,and hyperparameter tuning,the objective is to identify an appropriate machine learning model for intrusion detection.Experimental studies demonstrate that the AID4I framework successfully proposes a suitablemodel.The integrity,security,and confidentiality of data transmitted across the IIoT network can be ensured by automating machine learning processes in the IDS to enhance its capacity to identify and stop threatening activities.With a comprehensive solution that takes advantage of the latest advances in automated machine learning methods to improve network security,AID4I is a powerful and effective instrument for intrusion detection.In preprocessing module,three distinct imputation methods are utilized to handle missing data,ensuring the robustness of the intrusion detection system in the presence of incomplete information.Feature selection module adopts a hybrid approach that combines Shapley values and genetic algorithm.The Parameter Optimization module encompasses a diverse set of 14 classification methods,allowing for thorough exploration and optimization of the parameters associated with each algorithm.By carefully tuning these parameters,the framework enhances its adaptability and accuracy in identifying potential intrusions.Experimental results demonstrate that the AID4I framework can achieve high levels of accuracy in detecting network intrusions up to 14.39%on public datasets,outperforming traditional intrusion detection methods while concurrently reducing the elapsed time for training and testing.
基金This work was supported in part by the National Natural Science Foundation of China(Nos.62072074,62076054,62027827,62002047)the Sichuan Science and Technology Innovation Platform and Talent Plan(Nos.2020JDJQ0020,2022JDJQ0039)+2 种基金the Sichuan Science and Technology Support Plan(Nos.2020YFSY0010,2022YFQ0045,2022YFS0220,2023YFG0148,2021YFG0131)the YIBIN Science and Technology Support Plan(No.2021CG003)the Medico-Engineering Cooperation Funds from University of Electronic Science and Technology of China(Nos.ZYGX2021YGLH212,ZYGX2022YGRH012).
文摘With the continuous expansion of the Industrial Internet of Things(IIoT),more andmore organisations are placing large amounts of data in the cloud to reduce overheads.However,the channel between cloud servers and smart equipment is not trustworthy,so the issue of data authenticity needs to be addressed.The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems.Unfortunately,it still suffers from the problem of key exposure.In order to address this concern,this study first introduces a key-insulated scheme,SM2-KI-SIGN,based on the SM2 algorithm.This scheme boasts strong key insulation and secure keyupdates.Our scheme uses the elliptic curve algorithm,which is not only more efficient but also more suitable for IIoT-cloud environments.Finally,the security proof of SM2-KI-SIGN is given under the Elliptic Curve Discrete Logarithm(ECDL)assumption in the random oracle.
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number IFPHI-218-611-2020.”。
文摘The Industrial Internet of Things(IIoT)has been growing for presentations in industry in recent years.Security for the IIoT has unavoidably become a problem in terms of creating safe applications.Due to continual needs for new functionality,such as foresight,the number of linked devices in the industrial environment increases.Certification of fewer signatories gives strong authentication solutions and prevents trustworthy third parties from being publicly certified among available encryption instruments.Hence this blockchain-based endpoint protection platform(BCEPP)has been proposed to validate the network policies and reduce overall latency in isolation or hold endpoints.A resolver supports the encoded model as an input;network functions can be optimized as an output in an infrastructure network.The configuration of the virtual network functions(VNFs)involved fulfills network characteristics.The output ensures that the final service is supplied at the least cost,including processing time and network latency.According to the findings of this comparison,our design is better suited to simplified trust management in IIoT devices.Thus,the experimental results show the adaptability and resilience of our suggested confidence model against behavioral changes in hostile settings in IIoT networks.The experimental results show that our proposed method,BCEPP,has the following,when compared to other methods:high computational cost of 95.3%,low latency ratio of 28.5%,increased data transmitting rate up to 94.1%,enhanced security rate of 98.6%,packet reception ratio of 96.1%,user satisfaction index of 94.5%,and probability ratio of 33.8%.
基金The author(s)acknowledge Jouf University,Saudi Arabia for his funding support.
文摘The emergence of industry 4.0 stems from research that has received a great deal of attention in the last few decades.Consequently,there has been a huge paradigm shift in the manufacturing and production sectors.However,this poses a challenge for cybersecurity and highlights the need to address the possible threats targeting(various pillars of)industry 4.0.However,before providing a concrete solution certain aspect need to be researched,for instance,cybersecurity threats and privacy issues in the industry.To fill this gap,this paper discusses potential solutions to cybersecurity targeting this industry and highlights the consequences of possible attacks and countermeasures(in detail).In particular,the focus of the paper is on investigating the possible cyber-attacks targeting 4 layers of IIoT that is one of the key pillars of Industry 4.0.Based on a detailed review of existing literature,in this study,we have identified possible cyber threats,their consequences,and countermeasures.Further,we have provided a comprehensive framework based on an analysis of cybersecurity and privacy challenges.The suggested framework provides for a deeper understanding of the current state of cybersecurity and sets out directions for future research and applications.
文摘Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various applications.Therefore,a novel localisation algorithm is proposed for noisy range measurements in IIoT networks.The position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position estimation.Therefore,the AMs selection algorithm for the localisation of BMs in the IIoT network is introduced.Only those AMs will participate in the localisation process,which increases the accuracy of the final location estimate.Then,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement noise.The results are compared with the state‐of‐the‐art and verified through numerous simulations.
