CLUSTERING ANDROID MALWARE BERDASARKAN FREKUENSI SYSTEM CALL MENGGUNAKAN K-MEANS

BADRUS, MUHAMMAD ZUFAR and Heryanto, Ahmad (2022) CLUSTERING ANDROID MALWARE BERDASARKAN FREKUENSI SYSTEM CALL MENGGUNAKAN K-MEANS. Undergraduate thesis, Sriwijaya University.

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Abstract

In the security sector, malware that specifically attacks smartphones is growing faster and more sophisticated. Malware is becoming more and more powerful in carrying out criminal acts, such as stealing and destroying important data and information stored on mobile phones, thus demanding the creation of an anti-malware system that can prevent and detect when carrying out malware attacks on smart phones. From these results. Based on the research, it shows that the accuracy of the dataset without feature selection is 50% and the dataset with the feature selection method is 60%. Can Lock Feature selection can reduce the number of features that will be used for classification purposes, but does not significantly increase the accuracy of the results.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	K-Means, System Call
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Muhammad Zufar Badrus
Date Deposited:	28 Nov 2022 08:02
Last Modified:	28 Nov 2022 08:02
URI:	http://repository.unsri.ac.id/id/eprint/82861

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