A Robust Deep-Learning-Enabled Trust-Boundary Protection for Adversarial Industrial IoT Environment
Version 2 2024-06-04, 04:38
Version 1 2021-01-01, 00:00
journal contribution
posted on 2024-06-04, 04:38 authored by MM Hassan, MR Hassan, Shamsul HudaShamsul Huda, VHC De AlbuquerqueA Robust Deep-Learning-Enabled Trust-Boundary Protection for Adversarial Industrial IoT Environment
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Location
Piscataway, N.J.Language
EnglishPublication classification
C1 Refereed article in a scholarly journalCopyright notice
2020, IEEEJournal
IEEE Internet of Things JournalVolume
8Pagination
9611-9621ISSN
2327-4662eISSN
2327-4662Issue
12Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INCUsage metrics
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Keywords
Science & TechnologyTechnologyComputer Science, Information SystemsEngineering, Electrical & ElectronicTelecommunicationsComputer ScienceEngineeringTrainingGenerative adversarial networksRobustnessGallium nitrideData modelsInternet of ThingsMachine learningAdversarial attackdeep learning (DL)Industrial Internet of Things (IIoT)robustnesstrust boundary protectionCYBER-PHYSICAL SYSTEMSATTACKSMODELNETWORKSMALWARE4606 Distributed computing and systems software
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