Denial of Service (DoS) Attacks using PART Rule and Decision Table Rule

Aladesote O Isaiah

Abstract

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.

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