SELEKSI FITUR UNTUK MENEMUKAN POLA FITUR TERBAIK PADA SISTEM PENDETEKSI SERANGAN DDoS DENGAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

VIRGO, SANDIKA and Heryanto, Ahmad and Septian, Tri Wanda (2022) SELEKSI FITUR UNTUK MENEMUKAN POLA FITUR TERBAIK PADA SISTEM PENDETEKSI SERANGAN DDoS DENGAN MENGGUNAKAN METODE SUPPORT VECTOR MACHINE. Undergraduate thesis, Sriwijaya University.

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Abstract

DDoS is one of many attacks used by hackes in carrying out cyber crimes. As for knowing attacks detectors, in presenting this research looking for parameters that play a major role ini the DDoS dataset, it is necessary to apply a feature selection. In the application of feature selection using several selection, namely Random Forest Classifier (RFC), Mutual Information Classifier (MIC), Correlation Based Selection (CBS) and Lasso Regularization Regression (LRR). Then the classification uses Support Vector Machine (SVM) method, to determine accuracy, precision, recall and F1-score using confusion matrix technique. In this study using the CIC-IDS2017 dataset, after the research was carried out the Random Forest Classifier (RFC) feature selection became the best feature selection

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	DDoS, Machine Learning, Support Vector Machine, Feature Selection
Subjects:	Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA76.9.E94 Computer system performance. Computer Communication Networks. Computer science. Logic design. Operating systems (Computers). T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101-6720 Telecommunication Including telegraphy, telephone, radio, radar, television > TK5105.5.S72 Computer networks
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Sandika Virgo
Date Deposited:	09 Jan 2023 07:15
Last Modified:	09 Jan 2023 07:15
URI:	http://repository.unsri.ac.id/id/eprint/85573

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