Differentially-private federated intrusion detection via knowledge distillation in third-party IoT systems of smart airports

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dc.contributor.authorChen, Yang
dc.contributor.authorAl-Rubaye, Saba
dc.contributor.authorTsourdos, Antonios
dc.contributor.authorBaker, Lawrence
dc.contributor.authorGillingham, Colin
dc.date.accessioned2023-10-24T15:09:44Z
dc.date.available2023-10-24T15:09:44Z
dc.date.issued2023-10-24
dc.description.abstractWith the increasing deployment of IoT and Industry 4.0, the federated learning system was presented to preserve the privacy between the third-party IoT systems and the security operation center in smart airports. Nonetheless, the extremely skewed distribution of cyber threats increases the complexity of intrusion detection system (IDS) in smart airports, while privacy preservation limits the utility of IDS in the process of server model update. In this article, we have devised a knowledge distillation (KD)-based Convolutional Neural Network and Gated Recurrent Unit (CNN-GRU) model to improve the accuracy of multiple intrusion detection. In addition, the tradeoff between privacy and accuracy is achieved by denoising the adaptive parameter update mechanism to upgrade the optimizer of Differentially-Private (DP) Federated IDS. The results indicate high effectiveness and robustness of DP Federated KD-based IDS for third-party IoT systems of a smart airport.en_UK
dc.identifier.citationChen Y, Al-Rubaye S, Tsourdos A, et al., (2023) Differentially-private federated intrusion detection via knowledge distillation in third-party IoT systems of smart airports. In: ICC 2023 - IEEE International Conference on Communications, 28 May - 1 June 2023, Rome, Italyen_UK
dc.identifier.eisbn978-1-5386-7462-8
dc.identifier.isbn978-1-5386-7463-5
dc.identifier.issn1938-1883
dc.identifier.urihttps://doi.org/10.1109/ICC45041.2023.10279722
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20436
dc.language.isoenen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectFederated Learningen_UK
dc.subjectKD-based IDSen_UK
dc.subjectCNN-GRUen_UK
dc.subjectSmart Airporten_UK
dc.subjectICPSsen_UK
dc.subjectTrade-off between Privacy and Accuracyen_UK
dc.titleDifferentially-private federated intrusion detection via knowledge distillation in third-party IoT systems of smart airportsen_UK
dc.typeConference paper

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