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Please use this identifier to cite or link to this item: http://repository.fuoye.edu.ng/handle/123456789/1453

Title: AN ADAPTIVE MODEL FOR DETECTING DDOS ATTACK ON IPV4 AND IPV6
Authors: Alabi, Samuel Towoju
Keywords: ADAPTIVE
MODEL
DETECTING
DDOS
ATTACK
IPV4
IPV6
Issue Date: 31-Oct-2018
Abstract: As the Internet is growing so is the vulnerability of the network. Denial of Service attacks (DDoS) are one of such kind of attacks. In this paper, one of the more popular DDoS attack is the TCP-SYN Flood attack. The SYN flooding attacks are launched by exploiting the TCP’s three-way handshake mechanism and its limitation in maintaining its half-opened connections on internet protocols IPv4 and IPv6. This study is aimed in the detection of DDOS attack with neuro-fuzzy algorithm combination of fuzzy logic and neural network (ANFIS). To simulate this project research MATLAB 2012a software which is a programming language and environment for scientific computing. The result of comparison showed that the ANFIS model to the ANFIS has more accuracy in detecting DDoS in Internet Protocol (IPv4 and IPv6).
Description: As the Internet is growing so is the vulnerability of the network. Denial of Service attacks (DDoS) are one of such kind of attacks. In this paper, one of the more popular DDoS attack is the TCP-SYN Flood attack. The SYN flooding attacks are launched by exploiting the TCP’s three-way handshake mechanism and its limitation in maintaining its half-opened connections on internet protocols IPv4 and IPv6. This study is aimed in the detection of DDOS attack with neuro-fuzzy algorithm combination of fuzzy logic and neural network (ANFIS). To simulate this project research MATLAB 2012a software which is a programming language and environment for scientific computing. The result of comparison showed that the ANFIS model to the ANFIS has more accuracy in detecting DDoS in Internet Protocol (IPv4 and IPv6).
URI: http://repository.fuoye.edu.ng/handle/123456789/1453
Appears in Collections:Computer Science Thesis

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