Skripsi

KLASIFIKASI SERANGAN DDOS PADA JARINGAN IOT DENGAN MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (KNN)

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Penilaian

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In recent years, Internet of Things (IoT) sensors have become increasingly integrated into various devices and fields. Therefore, the security of IoT sensors is becoming more vulnerable to attacks. In this research, the K-Nearest Neighbors (KNN) algorithm is employed to classify attacks in the dataset. The dataset is obtained from interactions between DDos attacks and normal interactions, and it is balanced using the ADASYN oversampling technique. The best model achieves an accuracy of 89.29%. Comparing the parameters in KNN, the model consistently shows results with an average accuracy of 85.94%. These results indicate that the model exhibits consistent and reliable performance in the given classification task.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2407000503	T138543	T1385432024	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1385432024

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Uniersitas Sriwijaya., 2023

Collation

xiii, 44 hlm.; Ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

004.650 7

Content Type

Text

Media Type

unmediated

Carrier Type

-

Edition

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Subject(s)

Jaringan Komunikasi Komputer
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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