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
In order processing in the industrial Internet platform for textile and clothing,assigning optimal order quantities to each factory is the focus and the existing difficulty.The order allocation is a typical NP⁃hard pr...In order processing in the industrial Internet platform for textile and clothing,assigning optimal order quantities to each factory is the focus and the existing difficulty.The order allocation is a typical NP⁃hard problem in combinatorial optimization,and typical research of this kind is still at the initial stage.This paper aims to improve the optimization approach to select factories and to allocate proper orders to each one.It designs a genetic algorithm by making a deviation constraint rule for the initial population and introducing a penalty function to improve convergence.Remarkably,the objective functions of total cost along with the related constraints undergo optimization in the model.The experimental results indicate that the proposed algorithm can effectively solve the model and provide an optimal order allocation for multi⁃factories with less cost and computational duration.展开更多
为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用...为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用改进的蜣螂优化算法对工作流调度问题进行求解。改进的算法使用HEFT(heterogeneous earliest finish time)算法对蜣螂种群进行初始化,降低了原始算法中随机性带来的影响。同时引入了镜面反射和反向学习思想,提高了算法的搜索性能。实验结果表明,该算法相比于其他一些传统的调度算法在完工时间与成本方面都有一定的性能提升。展开更多
The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated...The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.展开更多
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Shanghai Foundation for Development of Industrial Internet Innovation,China(No.2019⁃GYHLW⁃004)。
文摘In order processing in the industrial Internet platform for textile and clothing,assigning optimal order quantities to each factory is the focus and the existing difficulty.The order allocation is a typical NP⁃hard problem in combinatorial optimization,and typical research of this kind is still at the initial stage.This paper aims to improve the optimization approach to select factories and to allocate proper orders to each one.It designs a genetic algorithm by making a deviation constraint rule for the initial population and introducing a penalty function to improve convergence.Remarkably,the objective functions of total cost along with the related constraints undergo optimization in the model.The experimental results indicate that the proposed algorithm can effectively solve the model and provide an optimal order allocation for multi⁃factories with less cost and computational duration.
文摘为了解决在工业物联网(industrial Internet of things,IIoT)环境下,现有的调度算法在调度工作流中对数据安全、响应时间有一定要求的任务所带来的完工时间上升、成本增加的问题,提出一种基于雾环境负载率而变化的任务调度策略,并使用改进的蜣螂优化算法对工作流调度问题进行求解。改进的算法使用HEFT(heterogeneous earliest finish time)算法对蜣螂种群进行初始化,降低了原始算法中随机性带来的影响。同时引入了镜面反射和反向学习思想,提高了算法的搜索性能。实验结果表明,该算法相比于其他一些传统的调度算法在完工时间与成本方面都有一定的性能提升。
文摘The Industrial Internet of Things(IIoT)has brought numerous benefits,such as improved efficiency,smart analytics,and increased automation.However,it also exposes connected devices,users,applications,and data generated to cyber security threats that need to be addressed.This work investigates hybrid cyber threats(HCTs),which are now working on an entirely new level with the increasingly adopted IIoT.This work focuses on emerging methods to model,detect,and defend against hybrid cyber attacks using machine learning(ML)techniques.Specifically,a novel ML-based HCT modelling and analysis framework was proposed,in which L1 regularisation and Random Forest were used to cluster features and analyse the importance and impact of each feature in both individual threats and HCTs.A grey relation analysis-based model was employed to construct the correlation between IIoT components and different threats.
