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KLASIFIKASI SERANGAN SQL INJECTION MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

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Penilaian

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The problem in this research is that the number of attack data is much less than the number of non-attack samples, which results in a high error rate in attack detection. The use of Support Vector Machine (SVM) method in this research is to find hyperlane and maximize the distance between different data classes. The purpose of this research is to classify SQL Injection attack data using the Support Vector Machine method and also in research using Mutual Information Classification as feature Selection. In this study using the CIC-IDS-2017 dataset which provides network attacks and normal activities collected from various sources and malware. The results of this study show that the application of the SVM method for the classification of the 2017 cic-ids dataset using the RBF kernel results in an accuracy of 80% using Feature Selection Quality Info Clasiffication.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2307002832	T122566	T1225662023	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T1225662023

Publisher

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

Collation

xi, 56 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

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