SISTEM KLASIFIKASI SERANGAN DDOS HTTP FLOOD DENGAN METODE LONG SHORT TERM MEMORY (LSTM)

AFIDIN, AHMAD and Stiawan, Deris and Heryanto, Ahmad (2020) SISTEM KLASIFIKASI SERANGAN DDOS HTTP FLOOD DENGAN METODE LONG SHORT TERM MEMORY (LSTM). Undergraduate thesis, Sriwijaya University.

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Abstract

Distributed Denial of Service (DDoS) merupakan serangan yang dapat mengganggu lalu lintas sebuah jaringan dengan memanfaatkan mesin zombie yang dikendalikan oleh penyerang. Serangan HTTP Flood dilakukan dengan mengeksploitasi permintaan HTTP GET dan HTTP POST ke target yang diserang. Pada penelitian ini menggunakan dataset CSE-CIC-IDS 2018 yang berasal dari University Of New Brunswick (UNB). Digunakan algoritma seleksi fitur Correlation-based Feature Selection (CFS) untuk mendapatkan fitur penting pada proses klasifikasi. Selain itu, digunakan algoritma Long Short Term Memory (LSTM) untuk mengklasifikasikan serangan DDoS HTTP Flood. Hasil pada penelitian ini menunjukkan bahwa Long Short Term Memory (LSTM) dengan memanfaatkan algoritma fitur seleksi Correlation-based Feature Selection (CFS) dapat melakukan klasifikasi serangan DDoS HTTP Flood dengan cukup baik dengan hasil akurasi sebesar 99.97%, sensitivitas sebesar 99.96%, spesifitas sebesar 99.95%, presisi sebesar 99,91%, F1-Score sebesar 99.93%

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	DDoS Clasification, HTTP Flood, Correlation-based Feature Selection (CFS), Long Short Term Memory (LSTM)
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User:	Users 5592 not found.
Date Deposited:	29 Jul 2021 06:56
Last Modified:	29 Jul 2021 06:56
URI:	http://repository.unsri.ac.id/id/eprint/50944

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