DETEKSI SERANGAN MALWARE RANSOMWARE PADA BITCOIN MINING DENGAN METODE K-MEANS CLUSTERING

FITRIANI, FITRIANI and Stiawan, Deris and Heryanto, Ahmad (2021) DETEKSI SERANGAN MALWARE RANSOMWARE PADA BITCOIN MINING DENGAN METODE K-MEANS CLUSTERING. Undergraduate thesis, Sriwijaya University.

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Abstract

Attack detection is an activity to analyze data or files whether the data has an attack or not. Snort IDS (intrusion detection system) help in analyzing and detecting attacks on a network in the bitcoin mining process. Malware Ransomware attack is a very dangerous attack because it requires a fee to be able to access the desired file. Ransomware attacks usually attack bitcoin miners who are doing the mining. Bitcoin Mining is a process carried out by miners to get a profit whose profits are commonly called Bitcoin. K-Means can be used to detect attacks on the bitcoin mining dataset. Malware Ransomware attack patterns on mining bitcoin mining datasets can recognized by several parameters such as source port, destination port, TTL, and protocol. In this study, the results obtained were 99% accuracy, which indicates the accuracy in the classification of malware attacks in this study.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Deteksi Malware, Snort IDS, Malware ransomware, K-means clustering, Bitcoin mining.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineering. Computer hardware
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	fitriani fitriani
Date Deposited:	07 Jun 2021 04:22
Last Modified:	07 Jun 2021 04:22
URI:	http://repository.unsri.ac.id/id/eprint/47744

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