Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning

A Master of Science thesis in Computer Engineering by Yara Kaddoura entitled, “Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning”, submitted in January 2023. Thesis advisors are Dr. Khaled El-Fakih and Dr. Imran Zualkernan. Soft copy is available (Thesis, Completion...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Kaddoura, Yara (author)
التنسيق: doctoralThesis
منشور في: 2023
الموضوعات:
الوصول للمادة أونلاين:http://hdl.handle.net/11073/25499
الوسوم: إضافة وسم
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author Kaddoura, Yara
author_facet Kaddoura, Yara
author_role author
dc.contributor.none.fl_str_mv El Fakih, Khaled
Zualkernan, Imran
dc.creator.none.fl_str_mv Kaddoura, Yara
dc.date.none.fl_str_mv 2023-01
2024-03-12T08:50:22Z
2024-03-12T08:50:22Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv 35.232-2023.80
http://hdl.handle.net/11073/25499
dc.language.none.fl_str_mv en_US
dc.subject.none.fl_str_mv Intrusion detection systems in IoT
Mutation testing
Formal modelling
Deep Learning
dc.title.none.fl_str_mv Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/doctoralThesis
description A Master of Science thesis in Computer Engineering by Yara Kaddoura entitled, “Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning”, submitted in January 2023. Thesis advisors are Dr. Khaled El-Fakih and Dr. Imran Zualkernan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
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network_acronym_str aus
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oai_identifier_str oai:repository.aus.edu:11073/25499
publishDate 2023
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repository.name.fl_str_mv
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spelling Fault Classification Using Formal Modeling and Mutation Testing with Deep LearningKaddoura, YaraIntrusion detection systems in IoTMutation testingFormal modellingDeep LearningA Master of Science thesis in Computer Engineering by Yara Kaddoura entitled, “Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning”, submitted in January 2023. Thesis advisors are Dr. Khaled El-Fakih and Dr. Imran Zualkernan. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Computer Science and EngineeringMaster of Science in Computer Engineering (MSCoE)El Fakih, KhaledZualkernan, Imran2024-03-12T08:50:22Z2024-03-12T08:50:22Z2023-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisapplication/pdf35.232-2023.80http://hdl.handle.net/11073/25499en_USoai:repository.aus.edu:11073/254992025-06-26T12:24:05Z
spellingShingle Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
Kaddoura, Yara
Intrusion detection systems in IoT
Mutation testing
Formal modelling
Deep Learning
status_str publishedVersion
title Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
title_full Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
title_fullStr Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
title_full_unstemmed Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
title_short Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
title_sort Fault Classification Using Formal Modeling and Mutation Testing with Deep Learning
topic Intrusion detection systems in IoT
Mutation testing
Formal modelling
Deep Learning
url http://hdl.handle.net/11073/25499