Design and verification of secure communication scheme for industrial IoT intelligent production line system with multi-path redundancy and collaboration

Li, Mingshi; Yin, Zhenyu; Ma, Yue; Wang, Chunxiao; Chai, Anying; Lian, Mengjia

doi:10.1007/s00521-021-05990-z

Cited by 10 publications

(5 citation statements)

References 30 publications

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“…• IntroducesanewimprovedK-means+SMOTEbasedoversamplingforsolvingtheoversampling problems. In Li, et al, 2021 In this study, they have developed a redundant collaboration secure communication scheme (TS-RCSCS) for IIoT smart manufacturing line systems. This approach presents a superfluous transmission method based on multiple auxiliary pathways and creates a redundant-synergysafecommunicationmodelbasedonthepeaksignaturestechnique.Thisstrategy may successfully avoid state data transfer interruption due by wireless transmission component failuresinIIoTsmartmanufacturinglinesystems,reducingthelikelihoodofdatapacketbecoming capturedbyhostilenodes.…”

Section: Industrial Iot (Iiot) Network: Ids Requirementmentioning

confidence: 99%

“…effectivelywiththeirclientsandpartners (Althobaiti,et al,2021;Selim,et al,2021;Li,et al,2021).Industrial4.0seekstosolveindustryproductivitychallengesviatheuseof data-drivensolutionsandsmartdevices.Improvedefficiencyaswellasimprovementsthroughout productioncanindeedbeachievedusingthisknowledge.Thisextendedconnection,nevertheless, exposesthoselinkeddevicestodistinctcyber-threats.Cybercriminalshavebecomemoreproficient asmanufacturingsitesbecomeincreasinglynetworked.Theterm"industrialcontrolsystem"refers tothenumeroustypesofcontrolfunctionsaswellasintegratedcomponentsusedonlytomanage manufacturingprocesses.TheICShasindeedbeensubjectedtoanupsurgeincyber-attacksthatalso haveresultedinavarietyofproblems.Safetyprecautionsthatareineffectivehavesuchanegative effectonworkersaswellastheorganisation.Productiondelays,damagetobuildings,healthand compensationexpenditures,materialsexpenses,companysetbacks,legalfees,andequipmentand materialsinjuryarejustafewoftheconsequences.Intrusiondetectionsystems(IDS)uncoversecurity flawsintrafficonthenetworkandnetworkinfrastructure.Itcanalsobeusedtodiscoverwhether attackerscommenceexploringequipment,whichwouldbethefirststeptowardsbuildingtrustworthy IIoT (Basheer,et al,2021;Saigopal,et al,2020;Koroniotis,et al,2021;Wadsworth,et al,2019). The IDS system involves gathering network activity, accounting records, log management, and informationacrossnetworkimportantaspectstodeterminewhetherthenetworkinghasanysecurity vulnerabilities.TheIDSapproachforIIoTmustbetailoredtowardsthetypeoftheinstruments.To increasetheefficiencyofIIoToperations,deeplearningapproachesareemployedalongsideIoT.…”

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confidence: 99%

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Deep Ensemble Model for Detecting Attacks in Industrial IoT

Behera¹,

Pattanayak²,

Mohanty

2022

International Journal of Information Security and Privacy

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In this research work, a novel IIoT attack detection framework is designed by following four major phases: pre-processing, imbalance processing, feature extraction, and attack detection. The attack detection is carried out using the projected ensemble classification framework. The projected ensemble classification framework encapsulates the recurrent neural network, CNN, and optimized bi-directional long short-term memory (BI-LSTM). The RNN and CNN in the ensemble classification framework is trained with the extracted features. The outcome acquired from RNN and CNN is utilized for training the optimized BI-LSTM model. The final outcome regarding the presence/absence of attacks in the industrial IoT is portrayed by the optimized BI-LSTM model. Therefore, the weight of BI-LSTM model is fine-tuned using the newly projected hybrid optimization model referred as cat mouse updated slime mould algorithm (CMUSMA). The projected hybrids the concepts of both the standard slime mould algorithm (SMA) and cat and mouse-based optimizer(CMBO), respectively.

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Section: Industrial Iot (Iiot) Network: Ids Requirementmentioning

confidence: 99%

mentioning

confidence: 99%

Deep Ensemble Model for Detecting Attacks in Industrial IoT

Behera¹,

Pattanayak²,

Mohanty

2022

International Journal of Information Security and Privacy

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“…Reference [5] studies the communication delay in the economic dispatch of the power system. Reference [6] studies the adverse effects of communication delay on economic dispatch. It concludes that communication delays affect the convergence speed of the system, and in severe cases, they can even lead to the failure of the system to converge.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Communication Simulation Model of Urban Comprehensive Energy Network Based on the Internet of Things

Fang

Yuan

Pan

et al. 2023

J. Phys.: Conf. Ser.

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In urban construction, all energy infrastructures have been realized by the information structure. However, due to the non-uniform structure of each energy network, the data cannot be more compatible, and the communication guarantee based on the Internet of Things is one of the most urgent problems to be solved. In this paper, a reasonable network computing offloading model is designed in the edge computing layer, and the computing offloading algorithm is introduced. Considering the dependency between subtasks, an optimization problem is established, and a central scheduling algorithm is proposed to solve it. An optimized distributed unloading algorithm is proposed according to the solution idea of the classical distributed unloading algorithm. Simulation results show that the optimized distributed unloading algorithm proposed in this paper has good solving efficiency and performance, and reduces the task processing delay. At the same time, the experimental simulation proves that the efficiency of multiple edge servers in processing subtasks is higher than that of a single server. It is established that changing the convergence speed and communication delay stability margin of the system by changing the system eigenvalue is beneficial to design a better communication network structure to keep the system stable.

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“…The ZTNA security framework detects the management issues that are presented in Industry 5.0. ZTNA provides a secure authentication policy that prevents third-party members from accessing the network [11]. ZTNA-based applications are also used in Industry 5.0.…”

Section: Introductionmentioning

confidence: 99%

A Zero-Trust Network-Based Access Control Scheme for Sustainable and Resilient Industry 5.0

Abuhasel

2023

IEEE Access

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This new era of the industry is characterized by the integration of artificial intelligence and the Internet of Things (IoT) to optimize production processes and reduce waste while also promoting humancentric approaches to work. To ensure sustainability and continuous industrial performance, Industry 5.0 integrates automated technology, robots, humans, and others. This modern paradigm relies on data and highlevel security to achieve sustainability and error-free production operations. For improving the resilience of Industry 5.0 through adversary mitigation, this manuscript introduces a Zero-Trust Network-based Access Control Scheme (ZTN-ACS). This scheme extends its remote and limitless support for managing, monitoring, and controlling devices and operation schedules. For its limiting network over the available controllers, deep learning aids access control. The industrial controller output over the defined access is verified for efficiency and consistency compared to the expected and previous production outputs. In the verification scheme, access interrupts the controllers, and the schedules are initiated using the learning paradigm. This learning process considers the achievable production outcome and the low or high variations in the current access-based output. Therefore, the access control and security features are extended or limited depending on the learning output over the adversaries. This scheme leverages consistency and reduces controller denials, failures, and false positives in Industry 5.0.

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Design and verification of secure communication scheme for industrial IoT intelligent production line system with multi-path redundancy and collaboration

Cited by 10 publications

References 30 publications

Deep Ensemble Model for Detecting Attacks in Industrial IoT

Deep Ensemble Model for Detecting Attacks in Industrial IoT

Analysis of Communication Simulation Model of Urban Comprehensive Energy Network Based on the Internet of Things

A Zero-Trust Network-Based Access Control Scheme for Sustainable and Resilient Industry 5.0

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