Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website

Septian Dwi Chandra ; Hardian Oktavianto ; Ari Eko Wardoyo
JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (J... 📅 2024 Vol 2, No 2 🔗 DOI: 10.54066/jptis.v2i2.1931
Abstract
This study aims to develop a web-based malware detection system using Convolutional Neural Network (CNN) utilizing the IoT23 dataset. Malware is malicious software that can exploit security vulnerabilities in computer systems, steal data, and degrade performance. The implementation of this detection system involves CNN, capable of extracting important features from both visual and textual data, applied to malware classification. The IoT23 dataset comprises 23 scenarios of IoT network traffic, including traffic from malware-infected devices. The study results show that the developed web application can detect malware attacks with accuracy, precision, recall, and F1-score of 99% on separate data scenarios. This CNN-based detection system has proven effective in identifying and classifying malware attacks, contributing to the enhancement of network and device security.
 
Keywords
Malware; Convolutional Neural Network (CNN); IoT23 dataset; web-based malware detection; deep learning
How to Cite

Septian Dwi Chandra, et al. (2024). Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website. JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS), 2(2). https://doi.org/10.54066/jptis.v2i2.1931

Septian Dwi Chandra; Hardian Oktavianto; Ari Eko Wardoyo, "Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website," JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS), vol. 2, no. 2, 2024.

Septian Dwi Chandra; Hardian Oktavianto; Ari Eko Wardoyo. "Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website." JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS), vol. 2, no. 2, 2024.

Septian Dwi Chandra; Hardian Oktavianto; Ari Eko Wardoyo. "Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website." JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS) 2, no. 2 (2024).

Septian Dwi Chandra, et al. (2024) 'Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website', JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS), 2(2). doi: 10.54066/jptis.v2i2.1931.

Septian Dwi Chandra; Hardian Oktavianto; Ari Eko Wardoyo. Klasifikasi Malware Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Website. JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS). 2024;2(2).

Artikel Terkait

Perancangan Media Pembelajaran Gerbang Logika Menggunakan Markerless Berbasis Augmented Reality

Venus Selvita; Putri Mandarani; Eko Kurniawanto Putra; Ganda Yoga Swara; Eva Yulianti

Rancang Bangun Sistem Informasi Penjualan Mitra dan Pendapatan Secara Real-time Berbasis Web : Studi Kasus Es Teh Arjuna di Kota Tegal

Farchatul Hudayah; Slamet Wiyono; Zaenul Arif

Pengembangan Sistem Manajemen Inventaris Aset Berbasis Qr Code dengan Pendekatan Agile Development pada Diskominfo Kabupaten Tegal

Muzaqi, Achmad Fatich; Aang Alim Murtopo; Zaenul Arif

Rancang Bangun Sistem Informasi Pendaftaran Magang Berbasis Web di Diskominfo Kabupaten Tegal

Salma Nafisa Qurrotu’Aini; Slamet Wiyono; Zaenul Arif

Pengembangan Sistem Smart Home Berbasis IoT untuk Monitoring dan Pengendalian Penggunaan Energi Listrik secara Efisien

Rafael Ardian Fahrezi; Iman Saufik Suasana; Danang Danang

Klasifikasi Penyakit Daun Tomat Menggunakan MobileNetV3

Russel Wijaya; Nur Rachmat
Tren Sitasi Jurnal