A Study on Heuristic Algorithms Combined With LR on a DNN-Based IDS Model to Detect IoT Attacks

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dc.contributor.authorThanh Thuy, Tran Thi
dc.contributor.authorDuc Thuan, Luong
dc.contributor.authorHong Duc, Nguyen
dc.contributor.authorTrong Minh, Hoang
dc.coverage.issue1cs
dc.coverage.volume29cs
dc.date.accessioned2024-01-11T08:34:36Z
dc.date.available2024-01-11T08:34:36Z
dc.date.issued2023-06-30cs
dc.description.abstractCurrent security challenges are made more difficult by the complexity and difficulty of spotting cyberattacks due to the Internet of Things explosive growth in connected devices and apps. Therefore, various sophisticated attack detection techniques have been created to address these issues in recent years. Due to their effectiveness and scalability, machine learning-based intrusion detection systems (IDSs) have increased. However, several factors, such as the characteristics of the training dataset and the training model, affect how well these AI-based systems identify attacks. In particular, the heuristic algorithms (GA, PSO, CSO, FA) optimized by the logistic regression (LR) approach employ it to pick critical features of a dataset and deal with data imbalance problems. This study offers an intrusion detection system (IDS) based on a deep neural network and heuristic algorithms combined with LR to boost the accuracy of attack detections. Our proposed model has a high attack detection rate of up to 99% when testing on the IoT-23 dataset.en
dc.formattextcs
dc.format.extent62-70cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationMendel. 2023 vol. 29, č. 1, s. 62-70. ISSN 1803-3814cs
dc.identifier.doi10.13164/mendel.2023.1.062en
dc.identifier.issn2571-3701
dc.identifier.issn1803-3814
dc.identifier.urihttps://hdl.handle.net/11012/244242
dc.language.isoencs
dc.publisherInstitute of Automation and Computer Science, Brno University of Technologycs
dc.relation.ispartofMendelcs
dc.relation.urihttps://mendel-journal.org/index.php/mendel/article/view/227cs
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0en
dc.subjectIntrusion Detection Systemen
dc.subjectDeep Neuron Networken
dc.subjectHeuristic Algorithmsen
dc.subjectIoT-23 dataseten
dc.titleA Study on Heuristic Algorithms Combined With LR on a DNN-Based IDS Model to Detect IoT Attacksen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta strojního inženýrstvícs
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