DETEKSI SERANGAN MAN IN THE MIDDLE (MITM) PADA SMART HOME MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM)

ANDREAS, DANNY and Stiawan, Deris and Exaudi, Kemahyanto (2024) DETEKSI SERANGAN MAN IN THE MIDDLE (MITM) PADA SMART HOME MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM). Undergraduate thesis, Sriwijaya University.

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Abstract

MITM attacks allow third parties to infiltrate between communicating devices to steal or modify data without being detected, increasing the security risk of smart home networks. This study aims to detect Man in the Middle (MITM) attacks on smart home networks using the Support Vector Machine (SVM) algorithm. The dataset used is COMNETS SMART HOME, which contains MITM attack data based on the ARP Poisoning technique, extracted from .pcap format to .csv using T-Shark. Random oversampling technique is applied to overcome class imbalance in the dataset to improve detection accuracy. The SVM model was tested with linear, polynomial, and Radial Basis Function (RBF) kernels, with a training and testing data ratio of 50:50 to 90:10. The best comparison was obtained at a ratio of 80:20 with a linear kernel, achieving an accuracy of 98.45%, a precision of 98.03%, a recall of 99.36%, and an F1 score of 98.69%. The results show that SVM with a linear kernel is effective in detecting MITM attacks on smart home networks.

Item Type:	Thesis (Undergraduate)
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Danny Andreas
Date Deposited:	14 Nov 2024 08:08
Last Modified:	14 Nov 2024 08:08
URI:	http://repository.unsri.ac.id/id/eprint/159363

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