Informasi Umum

Kode

25.05.743

Klasifikasi

000 - General Works

Jenis

Karya Ilmiah - Thesis (S2) - Reference

Subjek

Internet Of Things

Dilihat

29 kali

Informasi Lainnya

Abstraksi

The Internet of Things (IoT) is rapid growth in the current era of globalization, especially the IoT network which is the main target of cyber attacks. One of the<br /> attacks that occur on the IoT Network is a traffic attack. Traffic attack is an attack on excessive network traffic that aims to disrupt or paralyze a system. The excessive<br /> traffic is typically in the form of malware attacking IoT networks, is distributed Denial of Service (DDoS), Denial of Service (DoS), Recon, Web-based, Brute Force, and Spoofing or deliberately injected by malicious individuals or organizations. <br /> To counteract this traffic, one solution is to use an attack detection system, known as Intrusion Detection System (IDS). IDS is a model for analyzing and detecting attacks on traffic in IoT networks. This attack detection system can use the Convolutional Neural Networks (CNN) algorithm. In detecting traffic in IDS in IoT, the CNN algorithm can be used to predict the possibility of attack by utilizing patterns and features contained in networks traffic. So, Deep Learning such as the<br /> CNN algorithm can detect attack in traffic appropriately and is suitable for attack detection on IoT networks.<br /> The scenario result of this research can simulated and evaluated the system created. As a result, performance tests using the CNN Algorithm can produce model<br /> 80% accuracy. The classification results for F1-Score 82.0%, Precision 86.8%, Recall 80.2%, and processing time to evaluate or detection time is 29.54 second.

  • TTI6D3 - INTERNET OF THINGS
  • TTH613 - KEAMANAN UNTUK INTERNET OF THINGS (IOT)

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

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Pengarang

Nama RAUDHATUL RAFIQAH ASSYAHIDDINI
Jenis Perorangan
Penyunting Ida Wahidah Hamzah, Favian Dewanta
Penerjemah

Penerbit

Nama Universitas Telkom, S2 Teknik Elektro
Kota Bandung
Tahun 2025

Sirkulasi

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Denda harian IDR 0,00
Jenis Non-Sirkulasi