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

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82 kali
24.05.496
006.31
Karya Ilmiah - Thesis (S2) - Reference

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.
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.
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

Subjek

Machine Learning
 

Katalog

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
 
vi, 58p.: il,; pdf file
English

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Pengarang

HIJRAH NISYA
Perorangan
Sofia Naning Hertiana, Yudha Purwanto
 

Penerbit

Universitas Telkom, S2 Teknik Elektro
Bandung
2024

Koleksi

Kompetensi

 

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