Skripsi

VISUALISASI SERANGAN MALWARE BOTNET MENGGUNAKAN METODE CLUSTERING K-MEANS

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Penilaian

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Malware Attack Visualization aims to make it easier to recognize the type of malware and normal data. Malware or malicious software is a code or program file that is usually sent over the internet, to steal, infect, or perform some other dangerous operating system. While the Botnet is a network of devices infected by malicious software and controlled by an external operator called a botmaster. The purpose of this study is to get the best level of accuracy in Botnet Malware Attack Visualization using clustering method K-Means by using dataset namely MedBIoT project. The extraction feature in this study uses CICFlowMeters tools from the University of New Brunswick (UNB). In this study also used feature selection extra-tree classifier that aims to choose the best feature. The visualization results using clustering method K-Means showed a fairly good result which is an accuracy value of 99.17% which indicates accuracy in visualizing botnet malware attacks in this study.

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Availability

Inventory Code	Barcode	Call Number	Location	Status
2107002189	T53005	T530052021	Central Library (Referens)	Available but not for loan - Not for Loan

Detail Information

Series Title

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Call Number

T530052021

Publisher

Inderalaya : Fakultas Ilmu komputer, Prodi Sistem Komputer., 2021

Collation

xi, 61 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)

Malware
Prodi Sistem Komputer

Specific Detail Info

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Statement of Responsibility

MURZ

Other version/related

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