Skripsi

KLASIFIKASI MALWARE BANKING PADA ANDROID MENGGUNAKAN ALGORITMA RANDOM FOREST

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Penilaian

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Android smartphones is widely used for banking transactions. Thus, it can be at risk of malware attacks. Malware classification is a method that serves to identify and distinguish types of data classified as malware or normal. Banking Malware is malware designed to gain access to user's online banking accounts by impersonating a real banking application or web banking interface. This study aims to obtain the best level of accuracy in the classification of Banking Malware using the random forest algorithm with a dataset originating from the University of New Brunswick, namely CICMALDROID2020. The extraction feature used is the CICFlowMeters tool to process a dataset from a PCAP file into a CSV file. This research also use feature selection boruta which functions to select the best features in the dataset. The classification results using the random forest algorithm are evaluated using a confusion matrix. The highest accuracy obtained in this study was 92.5%, with a precision value of 93.28% and a recall of 93.73%.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002419	T47743	T477432021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T477432021

Publisher

Inderalaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer Uniersitas Sriwijaya., 2021

Collation

xvi, 72 hlm,: ilus.; 29 cm

Language

Indonesia

ISBN/ISSN

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Classification

005.840 7

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)

Prodi Sistem Komputer
Malware,Virus android

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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