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SELEKSI FITUR UNTUK MENEMUKAN POLA FITUR TERBAIK PADA SISTEM PENDETEKSI SERANGAN DDOS DENGAN MENGGUNAKAN METODE K-NEAREST NEIGHBOR (K-NN)

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Penilaian

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DDoS attacks are one of the main threats to security issues on the internet today which have quite a severe impact. As for knowing the best DDoS attack detection, this study applies several selection features to find the best feature pattern in detecting DDoS attacks using the K-Nearest Neighbor method. In the application of selection using several selection features, namely Random Forest Classifier (RFC), Mutual Information Classifier (MIC), Correlation Based Selection (CBS), and Lasso Regularization Regression (LRR). Based on the results of the classification using the K-Nearest Neighbor method, the mutual information classifier and random forest classifier that get the highest accuracy and are also the best at reducing features and finding the most relevant feature variables for detecting DDoS attacks

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307001315	T90914	T909142023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T909142023

Publisher

Inderalaya : Jurusan Sistem Komputer, Fakultas Ilmu Komputer Universitas Sriwijaya., 2023

Collation

xii, 108 hlm.; ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

006.307

Content Type

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Media Type

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Carrier Type

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Edition

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Subject(s)

Sistem Pakar
Jurusan Sistem Komputer

Specific Detail Info

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Statement of Responsibility

SEPTA

Other version/related

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