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

PRASETYO, RENDI and Stiawan, Deris (2023) KLASIFIKASI SERANGAN SQL INJECTION MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM). Undergraduate thesis, Sriwijaya University.

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Abstract

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.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	SQL Injection, Support Vector Machine
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Rendi Prasetyo
Date Deposited:	27 Jul 2023 04:36
Last Modified:	27 Jul 2023 04:36
URI:	http://repository.unsri.ac.id/id/eprint/122566

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