IMPLEMENTATION OF HYPERPARAMETER TUNING RANDOM FOREST ALGORITHM IN MACHINE LEARNING FOR SDN SECURITY: AN INNOVATIVE EXPLORATION OF DDOS ATTACK DETECTION - Dalam bentuk buku karya ilmiah
HIJRAH NISYA
Informasi Umum
Kode
24.05.496
Klasifikasi
006.31 - Machine Learning
Jenis
Karya Ilmiah - Thesis (S2) - Reference
Subjek
Machine Learning
Dilihat
111 kali
Informasi Lainnya
Abstraksi
Software Defined Network or SDN, is a new approach in network programming for designing, building, and managing computer networks by separating the control plane from the data plane to centralize the network to concentrate all settings at the control plane. SDN can dynamically monitor, modify, and manage network behavior through open interface software.<br /> Network development has frequently encountered issues related to network security and network attacks. In contrast with conventional networks, SDN has various advantages, one of which is that SDN can implement centralized control functions on the controller, which makes the controller the heart of SDN. The centralized nature of SDN makes it a target for attacks, one of which is a Distributed Denial of Service (DDoS) attack.<br /> Several approaches to detect attacks in SDN have been proposed, but few consider the security of the controller. Therefore, a security system is needed to overcome the problem of attacks that occur on SDN controllers. To addres
Koleksi & Sirkulasi
Tersedia 1 dari total 1 Koleksi
Anda harus log in untuk mengakses flippingbook
Pengarang
| Nama | HIJRAH NISYA |
| Jenis | Perorangan |
| Penyunting | Sofia Naning Hertiana, Yudha Purwanto |
| Penerjemah |
Penerbit
| Nama | Universitas Telkom, S2 Teknik Elektro |
| Kota | Bandung |
| Tahun | 2024 |
Sirkulasi
| Harga sewa | IDR 0,00 |
| Denda harian | IDR 0,00 |
| Jenis | Non-Sirkulasi |
