Denial of Service (DoS) Attacks using PART Rule and Decision Table Rule
Aladesote O Isaiah*, Johnson OV and Ganiyu Mutiu
Department of Computer Science, Federal Polytechnic, Ile – Oluji, Ondo State, Nigeria
- *Corresponding Author:
- Aladesote O Isaiah
Department of Computer Science
Federal Polytechnic, Ile – Oluji
Ondo State, Nigeria
E-mail: [email protected], [email protected]
Received Date: March 22, 2017; Accepted Date: April 24, 2017; Published Date: April 29, 2017
Citation: Isaiah AO, Johnson OV, Mutiu G (2017) Denial of Service (DoS) Attacks using PART Rule and Decision Table Rule. J Electr Electron Syst 6: 220. doi:10.4172/2332-0796.1000220
Copyright: © 2017 Isaiah, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Network Security has become a major and critical issue as a result of the vast growth in the field of Information Technology. This paper adopted the result of an existing extraction or attributes selection of KDD ’99 dataset. The dataset was run on data de-duplicated software developed using C# Programming Language and final mining analysis was carried out on Waikato Environment for Knowledge Analysis (WEKA) with the adoption of PART and Decision Table algorithms. The performance evaluation was carried out with some related existing works based on certain intrusion detection metrics. The Classification Rate of Decision Tree Rule, Part Rule and JRIP Rule are 98.14%, 99.4% and 99.1%, respectively. The False Alarm Rate of Decision Tree Rule, Part Rule and JRIP Rule are 0.86%, 0.43% and 0.55% respectively. The Sensitivity of Decision Tree Rule, Part Rule and JRIP Rule is 92.6%, 98.3% and 97.2% respectively while the Specificity of Decision Tree Rule, Part Rule and JRIP Rule is 99.1%, 99.6% and 99.4% respectively.