The security performance of cloud services is a key factor influencing users’selection of Cloud Service Providers(CSPs).Continuous monitoring of the security status of cloud services is critical.However,existing rese...The security performance of cloud services is a key factor influencing users’selection of Cloud Service Providers(CSPs).Continuous monitoring of the security status of cloud services is critical.However,existing research lacks a practical framework for such ongoing monitoring.To address this gap,this paper proposes the first NonCollaborative Container-Based Cloud Service Operation State Continuous Monitoring Framework(NCCMF),based on relevant standards.NCCMF operates without the CSP’s collaboration by:1)establishing a scalable supervisory index system through the identification of security responsibilities for each role,and 2)designing a Continuous Metrics Supervision Protocol(CMA)to automate the negotiation of supervisory metrics.The framework also outlines the supervision process for cloud services across different deployment models.Experimental results demonstrate that NCCMF effectively monitors the operational state of two real-world IoT(Internet of Things)cloud services,with an average supervision error of less than 15%.展开更多
New industrial automation applications necessitate flexibility,scalability,and ability to be reconfigured in response to alterations that occur during their operation,to attain optimal operational points.This work pre...New industrial automation applications necessitate flexibility,scalability,and ability to be reconfigured in response to alterations that occur during their operation,to attain optimal operational points.This work presents an architecture for the development of industrial automation applications with different real-time requirements.The proposed architecture employs a scheduler based on fixed priorities to manage the execution of containerized tasks,which are integrated through the Data Distribution Service(DDS)middleware,and incorporates a bridge to a Controller Area Network(CAN),thereby enabling the fulfillment of End-to-End(E2E)real-time deadlines in distributed applications.The results of the implemented case studies provide corroboration for the validity of the proposed solution.This architecture facilitates scalability,reconfiguration,and consistency of information,addressing the solution of two of the main challenges currently presented in the development of industrial automation systems.The first of these challenges is related to the integration of industrial automation solutions,while the second is related to the reconfiguration of the systems in compliance with real-time requirements.展开更多
基金supported in part by the Intelligent Policing and National Security Risk Management Laboratory 2023 Opening Project(No.ZHKFYB2304)the Fundamental Research Funds for the Central Universities(Nos.SCU2023D008,2023SCU12129)+2 种基金the Natural Science Foundation of Sichuan Province(No.2024NSFSC1449)the Science and Engineering Connotation Development Project of Sichuan University(No.2020SCUNG129)the Key Laboratory of Data Protection and Intelligent Management(Sichuan University),Ministry of Education.
文摘The security performance of cloud services is a key factor influencing users’selection of Cloud Service Providers(CSPs).Continuous monitoring of the security status of cloud services is critical.However,existing research lacks a practical framework for such ongoing monitoring.To address this gap,this paper proposes the first NonCollaborative Container-Based Cloud Service Operation State Continuous Monitoring Framework(NCCMF),based on relevant standards.NCCMF operates without the CSP’s collaboration by:1)establishing a scalable supervisory index system through the identification of security responsibilities for each role,and 2)designing a Continuous Metrics Supervision Protocol(CMA)to automate the negotiation of supervisory metrics.The framework also outlines the supervision process for cloud services across different deployment models.Experimental results demonstrate that NCCMF effectively monitors the operational state of two real-world IoT(Internet of Things)cloud services,with an average supervision error of less than 15%.
文摘New industrial automation applications necessitate flexibility,scalability,and ability to be reconfigured in response to alterations that occur during their operation,to attain optimal operational points.This work presents an architecture for the development of industrial automation applications with different real-time requirements.The proposed architecture employs a scheduler based on fixed priorities to manage the execution of containerized tasks,which are integrated through the Data Distribution Service(DDS)middleware,and incorporates a bridge to a Controller Area Network(CAN),thereby enabling the fulfillment of End-to-End(E2E)real-time deadlines in distributed applications.The results of the implemented case studies provide corroboration for the validity of the proposed solution.This architecture facilitates scalability,reconfiguration,and consistency of information,addressing the solution of two of the main challenges currently presented in the development of industrial automation systems.The first of these challenges is related to the integration of industrial automation solutions,while the second is related to the reconfiguration of the systems in compliance with real-time requirements.
