| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6905758 | Applied Soft Computing | 2014 | 16 Pages |
Abstract
- A predictive fuzzy associative rule model to validate inputs to counter XML attacks.
- The model discovers fuzzy associative patterns to improve decision outcomes.
- The model is able to identify 18 interesting rules with at least 99% confidence.
- Determining frequently occurring features addresses the feature selection problem.
- Classification using random forests is 99% or more with near zero error measures.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Gaik-Yee Chan, Chien-Sing Lee, Swee-Huay Heng,