DETECTION OF DISTRIBUTED DENIAL-OF-SERVICE (DDoS) ATTACK WITH HYPERPARAMETER TUNING BASED ON MACHINE LEARNING APPROACH

Aug 3, 2026

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Distributed Denial-of-Service (DDoS) attack represents a major cyber threat that targets networks by flooding Internet traffic to overwhelm a victim. Detection becomes increasingly difficult as attack techniques evolve, and distinguishing benign traffic from malicious traffic is challenging under heavy network load. Machine-learning limitations can also lead to misclassification when filtering is disrupted. This work selects five machine learning models and applies EDA and data preprocessing on a standard dataset to produce clean inputs, then evaluates detection performance using accuracy, precision, recall, F1-score, ROC-AUC, and confusion matrix.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages126

Reading Time5 h 18 min

AccessFree to download

Declarations

Open access and rights

Thesis content

Acknowledgements

Abstract

Machine learning models and evaluation

DETECTION OF DISTRIBUTED DENIAL-OF-SERVICE (DDoS) ATTACK WITH HYPERPARAMETER TUNING BASED ON MACHINE LEARNING APRROACH CHOO YONG HAN BACHELOR OF COMPUTER SCIENCE (COMPUTER SYSTEMS & NETWORKING) WITH HONOURS UNIVERSITI MALAYSIA PAHANG UNIVERSITI MALAYSIA PAHANG | DECLARATION OF THESIS AND COPYRIGHT
Author’s Full Name : CHOO YONG HAN
Date ofBirth
Title : DETECTION OF DISTRIBUTED DENIAL-OF-SERVICE
(DDoS) ATTACK WITH HYPERPARAMETER TUNING BASED ON MACHINE LEARNING APPROACH
Academic Session : SEMESTER 1 ACADEMIC SESSION 2022/2023
I declare that this thesis is classified as: | | | | --- | --- | --- | | 􀂅 CONFIDENTIAL
􀂅 RESTRICTED | (Contains confidential information under the Official Secret Act 1997)*
(Contains restricted information as specified by the | | | organization where research was done)*
􀀻 OPEN ACCESS I agree that my thesis to be published as online open access
(Full Text)
I acknowledge that Universiti Malaysia Pahang reserves the following rights:
1. The Thesis is the Property of Universiti Malaysia Pahang
2. The Library of Universiti Malaysia Pahang has the right to make copies of the thesis for the purpose of research only.
3. The Library has the right to make copies of the thesis for academic exchange. | | | | Certified by:
(Student’s Signature)
New IC/Passport Number
Date: 20/1/2023 | | (Supervisor’s Signature)
| NOTE : * If the thesis is CONFIDENTIAL or RESTRICTED, please attach a thesis declaration letter. SUPERVISOR’S DECLARATION I hereby declare that I have checked this thesis/project* and in my opinion, this thesis/project* is adequate in terms of scope and quality for the award of the degree of Bachelor of Computer Science (Computer Systems & Networking) with Honours. (Supervisor’s Signature) Full Name : Puan Wan Nurulsafawati Binti Wan Manan Position : Lecturer Date : 21/01/2023 STUDENT’S DECLARATION I hereby declare that the work in this thesis is based on my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously or concurrently submitted for any other degree at Universiti Malaysia Pahang or any other institutions. (Student’s Signature) Full Name : CHOO YONG HAN ID Number : CA19088 Date : 20 January 2023 DETECTION OF DISTRIBUTED DENIAL-OF-SERVICE (DDoS) ATTACK WITH HYPERPARAMETER TUNING BASED ON MACHINE LEARNING APPROACH CHOO YONG HAN Thesis submitted in fulfillment of the requirements for the award of the degree of Bachelor of Computer Science (Computer Systems & Networking) with Honours Faculty of Computing UNIVERSITI MALAYSIA PAHANG JANUARY 2023 ACKNOWLEDGEMENTS First and foremost, I want to express my gratitude to God for giving me the opportunity and blessing of finishing my Final Year Project (FYP) on schedule. My supervisor, Puan Wan Nurulsafawati Binti Wan Manan, has been a huge help to me during my FYP, thus I want to convey my sincere gratitude for her excitement, patience, insightful remarks and information and never-ending suggestions. My successful completion of the FYP is due to her vast knowledge, extensive experience and professional expertise in Data & Network Security. My FYP would not have been possible without her excellent help and direction. Moreover, I would also like to express my gratitude to Dr Ku Muhammad Na’im Ku Khalif and Dr Chuan Zun Liang for providing the necessary knowledge and skills information regarding the FYP. Besides, I would like to express my appreciation to my friends and colleagues who have always willingly to show their support and encouragement throughout the time of project period. Last but not least, I want to extend my heartiest thank to my parents Choo Ching Leong and Chong Lai Yong for always being a source of moral support for me. ABSTRAK Serangan Penafian-Perkhidmatan Teragih merupakan salah satu serangan siber yang dilancarkan di seluruh duniauntuk menganggu

FAQs

What problem does the thesis address?

It addresses detection of Distributed Denial-of-Service (DDoS) attacks under increasingly sophisticated attack techniques and heavy network traffic conditions.

Which models and evaluation metrics are used?

The study selects five machine learning models and evaluates them using accuracy, precision, recall, F1-score, ROC-AUC area, and the confusion matrix.

How is the dataset prepared for training and detection?

EDA and data preprocessing are performed to create a clean dataset, improving the accuracy of detection results.

Aug 3, 2026

Upload by Maeve