SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan

Mazlan, Muhammad Muhaimin Aiman (2018) SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan. Student Project. Faculty of Computer and Mathematical Sciences, Jasin. (Unpublished)

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Abstract

In the era of technology, Firewall have become an important component for protecting interconnection of the computer resource and network environment. Recently, one the most popular attack is denial of service (DoS) that attempt to be malicious pattern to compromise a server or a network resource. The current problem and issue regarding of existing project is cannot handle the attack by shutdown the connection between inbound and outbound network. Therefore, the aim of this project is to develop a firewall software called “FIREARMS” that can prevent one type of DDoS which is SYN-Flood attack. The core detection and prevention algorithm which is the support vector machine (SVM) were implemented in this project. The software will be trained by using NSL KDD Cup dataset in order to make it learns about the Neptune attack and as a result, it will be able to detect and prevent such attack. The significant of this project is it can be detect any of the SYN-Flood attack accurately and avoid many of false alarm rate. In a conclusion, the software would be able to prevent the computer from SYN-Flood attack by using FIREARMS software. This will help user to secure their network during the connection of their computer to the internet.

Item Type: Monograph (Student Project)
Creators:
CreatorsID Num.
Mazlan, Muhammad Muhaimin AimanUNSPECIFIED
Subjects: Q Science > QA Mathematics > Instruments and machines
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science

Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Artificial immune systems. Immunocomputers
Q Science > QA Mathematics > Instruments and machines > Electronic computers. Computer science > Artificial immune systems. Immunocomputers
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Item ID: 21337
Uncontrolled Keywords: Computer resource; Network environment; SYN-Flood attack; Technology
Last Modified: 24 Oct 2018 01:59
Depositing User: Perpustakaan UiTM Cawangan Melaka UiTM Cawangan Melaka
URI: http://ir.uitm.edu.my/id/eprint/21337

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