DETEKSI SERANGAN MIRAI DENGAN MENGGUNAKAN METODE LONG SHORT-TERM MEMORY (LSTM) PADA JARINGAN IOT

PUTRI, THALIA and Stiawan, Deris and Afifah, Nurul (2024) DETEKSI SERANGAN MIRAI DENGAN MENGGUNAKAN METODE LONG SHORT-TERM MEMORY (LSTM) PADA JARINGAN IOT. Undergraduate thesis, Sriwijaya University.

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Abstract

Perkembangan jaringan Internet of Things (IoT) telah membawa dampak signifikan pada berbagai sektor, termasuk transportasi dan pelayanan kesehatan. Namun, lonjakan adopsi IoT juga memunculkan tantangan keamanan, terutama ancaman serangan siber seperti Mirai, yang menyerang perangkat IoT melalui Distributed Denial of Service (DDoS). Berbagai metode telah dikembangkan untuk mendeteksi serangan ini, seperti blockchain, K-Nearest Neighbors (KNN), dan Support Vector Machine (SVM), namun masing-masing memiliki keterbatasan. Long Short-Term Memory (LSTM) menjadi pilihan dalam penelitian ini karena kemampuannya dalam mengolah data sekuensial dengan tingkat akurasi tinggi dan mengatasi masalah vanishing gradient. Penelitian ini berfokus pada deteksi serangan Mirai menggunakan metode LSTM pada dataset CIC IoT 2023 untuk menghasilkan solusi yang efektif dan akurat dalam mengidentifikasi ancaman.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Internet of Things (IoT), Serangan Mirai, DDoS, Keamanan Siber, Long Short-Term Memory (LSTM), Deteksi Serangan.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Thalia Putri
Date Deposited:	17 Jan 2025 04:09
Last Modified:	17 Jan 2025 04:09
URI:	http://repository.unsri.ac.id/id/eprint/165157

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