Abstract
Utilizing feature selection in intrusion detection can remove redundant features and improve the speed of the intrusion detection system efficiently on the basis of protecting the integrity of the original data. This paper proposes a new feature selection method that is based on KNN and Tabu search algorithm. The experiment result shows that this method can remove the redundant features, and reduce the time of feature selection. This method not only guarantees the accuracy of detection but also improves the detection speed efficiently.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 |
| Pages | 435-439 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 - Shanghai, China Duration: 6 Jan 2011 → 7 Jan 2011 |
Publication series
| Name | Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 |
|---|---|
| Volume | 1 |
Conference
| Conference | 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 |
|---|---|
| Country/Territory | China |
| City | Shanghai |
| Period | 6/01/11 → 7/01/11 |
Keywords
- Feature relevance
- Feature selection
- Intrusion detection
- Tabu search
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Wu, J. G., Tao, R., & Li, Z. Y. (2011). An improving Tabu search algorithm for intrusion detection. In Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011 (pp. 435-439). Article 5720813 (Proceedings - 3rd International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2011; Vol. 1). https://doi.org/10.1109/ICMTMA.2011.110