VISUALISASI SERANGAN MALWARE SPYWARE DENGAN MENGGUNAKAN METODE RANDOM FOREST

PRAMUDITA, AMELIA and Stiawan, Deris (2023) VISUALISASI SERANGAN MALWARE SPYWARE DENGAN MENGGUNAKAN METODE RANDOM FOREST. Undergraduate thesis, Sriwijaya University.

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Abstract

Spyware is a type of malware that aims to collect important information and data such as financial information and passwords without permission and send them to the attacker. Visualization techniques are needed to make it easier to analyze attack patterns and characteristics of spyware. This study used the Random Forest algorithm. The dataset is from CIC-MalMem2022 with benign data types and Spyware Gator in .csv form. In this study applied feature selection to find relevant features and reduce irrelevant features by using Correlation Based Feature Selection. This feature selection process produces 7 features, 16 features and 31 relevant features that will be visualized using parallel coordinates line diagrams. The validation results of the three different number of features using stratified k-fold produce the best accuracy for 7 features at 6-Fold is 99.94%. The best accuracy results for 16 features are found at 4-Fold that is 99.97% and the best accuracy results for 31 features are found at 9-Fold that is 99.98%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Spyware, Random Forest, Visualisasi, RandomizedSearchCV, Stratified K-Fold, Confusion Matrix
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Amelia Pramudita
Date Deposited:	19 Jun 2023 07:45
Last Modified:	19 Jun 2023 07:45
URI:	http://repository.unsri.ac.id/id/eprint/112083

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