Text

ANALISIS SISTEM DETEKSI SERANGAN DDOS ADAPTIF MENGGUNAKAN METODE RT-AMD PADA INFRASTRUKTUR CLOUD COMPUTING

---

Penilaian

---

Distributed Denial of Service (DDoS) is a major threat to cloud computing infrastructure, capable of causing service disruptions and significant losses. This study aims to develop an adaptive DDoS attack detection system using the RT-AMD (Real-Time Attack Monitoring and Detection) method, which combines four machine learning algorithms: Decision Tree, Random Forest, Naive Bayes, and K-Nearest Neighbors, to enhance detection accuracy and efficiency. The research utilizes the CICDDoS2019 dataset, focusing on SYN Flood and UDP Flood attacks. Evaluation results indicate that the Decision Tree method achieves an accuracy of 95.6%, Random Forest 98.4%, Naive Bayes 88.7%, and K-Nearest Neighbors 93.2%. The system demonstrates its effectiveness in adaptively detecting DDoS attacks, efficiently utilizing resources, and identifying attack patterns in real-time. Thus, this study significantly contributes to the development of smarter and more adaptive detection methods to improve the security of cloud computing networks while serving as a reference for future research in the field of cybersecurity.

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2507000175	T164380	T1643802024	Central Library (REFERENCE)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T1643802024

Publisher

Indralaya : Prodi Sistem Komputer, Fakultas Ilmu Komputer., 2024

Collation

xv, 150 hlm., ilus., tab.; 29 cm

Language

Indonesia

ISBN/ISSN

-

Classification

003.07

Content Type

-

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Sistem komputer

Specific Detail Info

-

Statement of Responsibility

EM

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment