Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T17:36:30.099568Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2603.23416.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T17:36:30.099568Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
32 of 32 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation fd6a4d38-b93d-4932-a4ae-3d430b937bad · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Integration of 5g and opc ua for smart manufacturing of the future
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aec3369a-01bb-403d-874f-53c1a9140793 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Private 5G: The Future of Industrial Wireless.IEEE Industrial Electronics Magazine, 14(4): 136–145, 2020
Reference 2
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e37ba553-a63f-4af0-ba8b-c940fd973a05 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks 5g security challenges and opportunities: A system approach
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf4c5ae1-7668-4e37-9541-a4addc931078 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Easing the conscience with opc ua: an internet-wide study on insecure deployments
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9deaeb41-0bb9-408b-9a29-15b1bd18e342 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks The Performance of OPC-UA Security Model at Field Device Level
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 686e2ec9-2aac-4cfd-98ac-a2eb36c555b5 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks OPC UA Security Analysis, 2017
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7bc66d0f-e221-4998-a6ff-15f1bff27d00 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Opc ua security analysis.Federal Office for Information Security (BSI), 2022
Reference 7
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b3b2d2cb-55c2-46c5-b78a-0b820a122e34 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Simulating and Detecting Attacks of Untrusted Clients in OPC UA Networks
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe80a4b8-4b04-4d59-8dfb-053d5aef370e · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Assessing the Impact of Attacks on opc-ua Applications in the Industry 4.0 Era
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ada88d3-9bb8-445d-99e6-5b8aa38674b9 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Deep Learning-based Enhanced Security in Cyber- Physical Systems: A Multi-Attack Perspective
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14a71da8-ae76-4eb3-bbf5-837fc26e427a · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Research on network traffic identification based on machine learning and deep packet inspection
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f46f0d51-96f2-4272-bd27-b16bd1fc39a6 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Ai-based network security enhancement for 5g industrial internet of things environments
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dd11f5b-7cb1-4722-9823-71888592b172 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Role of machine learning and deep learning in securing 5g-driven industrial iot applications.Ad Hoc Networks, 123:102685, 2021
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e12419c7-67bf-406c-921b-28f0577a40a6 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Vet5g: A virtual end-to-end testbed for 5g network security experimentation
Reference 14
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac7a7512-91c9-40d4-868f-a3596e91232d · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks An experimental testbed for 5g network security assessment
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a003c3c6-058e-4ddb-9c24-f057b14c8e49 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks A 5g and beyond testbed for cybersecurity research and education
Reference 16
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Unavailable: canonical work link unavailable.
Observation 58faebae-c678-48d9-9f61-a353188dc000 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks A case study on the representativeness of public DoS network traffic data for cybersecurity research
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3893c667-2ae5-4bb3-b88b-99e1819c7498 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks A Survey on Industrial Control System Testbeds and Datasets for Security Research.IEEE Communications Surveys & Tutorials, 23(4):2248–2294, 2021
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation afafa8ea-e1b6-4f40-8149-0d15b91d8ba0 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Testing Commercial Intrusion Detection Systems for Industrial Control Systems in a Substation Hardware in the Loop Testlab
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ee5adde3-d802-461e-8e37-fad818466922 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks A Review of Deep Learning IDS for DDoS Attacks in WLANs
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 673dbaa9-3f3f-410f-bc24-6c4160f1556e · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Cyber security of OT networks: A tutorial, survey of attacks and overview of current state of defense tools, protocols, & challenges
Reference 21
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4200e20c-f451-482c-8ac1-4c71bdd74dc0 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks It-ot integration challenges in utilities
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b19cd0b9-9fca-4677-96c0-2b3d27bfdec9 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks September 2023
Reference 23
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6d237a3-b160-483e-98d5-6213595e64ef · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Licster – a low-cost ics security testbed for education and research
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf86e9ef-ce66-40db-84d1-5ce0256c2782 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Creating a european scada security testbed
Reference 25
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba82bd3b-7382-45f0-87ba-263a218404e0 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks OTG: A Gateway for Cybersecurity in the Context of OPC UA PubSub Pattern.Journal of Physics: Conference Series, 1693(1):012016, December 2020
Reference 26
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f01fffca-3546-4394-9242-6ac7a869c85d · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks TR 21.916 version 16.2.0 Release 16
Reference 27
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2d62ae71-2504-421b-95ea-cf55ddb6620a · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks 5G NR Jam- ming, Spoofing, and Sniffing: Threat Assessment and Mitigation
Reference 28
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d429c919-be9e-4ceb-9556-e698b8310eb3 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Testbed and Software Architecture for Enhancing Security in Industrial Private 5G Networks
Reference 29
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe9877ee-1e7a-476b-aff3-907d3d46fa34 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Factory I/O: 3D factory simulation software
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43350394-0354-4019-80e7-bdfc493139dc · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Opc-ua exploitation framework
Reference 31
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Unavailable: canonical work link unavailable.
Observation e410c492-e016-423a-9989-ba205431d5a6 · outbound
An Experimental Study of Machine Learning-Based Intrusion Detection for OPC UA over Industrial Private 5G Networks Unresolved cited work
Reference 2019
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
No inbound Pith citation observations are available.