Skripsi

DETEKSI SERANGAN DDOS PADA SMARTHOME MENGGUNAKAN METODE NAÏVE BAYES

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Penilaian

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The rapid development of smart home technology presents new challenges in terms of cybersecurity, particularly against Distributed Denial of Service (DDoS) attacks. This study aims to detect DDoS attacks in smart home networks using the Naïve Bayes algorithm. The dataset used is the COMNETS SMARTHOME dataset in .pcap format, which was converted to .csv using CiCFlowMeter on a Windows environment. Due to the imbalanced nature of the dataset, the Synthetic Minority Oversampling Technique (SMOTE) was applied to balance the distribution between classes. The evaluation results show that the model achieved an accuracy of 91.41%, a precision of 94.10%, a recall of 89.79%, an F1-score of 91.81%, and a specificity of 93.33%. These findings indicate that the combination of Naïve Bayes and SMOTE provides strong performance in detecting DDoS attacks within smart home networks, highlighting the potential of machine learning approaches in cybersecurity systems.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2507005497	T183243	T1832432025	Central Library (Referensi)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1832432025

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2025

Collation

xvi, 125 hlm.; ilus.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

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Classification

004.07

Content Type

Text

Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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