The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Performance analysis of NSL-KDD dataset using ANN
Abstract
Anomalous traffic detection on internet is a major issue of security as per the growth of smart devices and this technology. Several attacks are affecting the systems and deteriorate its computing performance. Intrusion detection system is one of the techniques, which helps to determine the system security, by alarming when intrusion is detected. In this paper performance of NSL-KDD dataset is evaluated using ANN. The result obtained for both binary class as well as five class classification (type of attack). Results are analyzed based on various performance measures and better accuracy was found. The detection rate obtained is 81.2% and 79.9% for intrusion detection and attack type classification task respectively for NSL-KDD dataset. The performance of the proposed scheme has been compared with existing scheme and higher detection rate is achieved in both binary class as well as five class classification problems.
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Cites
Toward Credible Evaluation of Anomaly-Based Intrusion-Detection Methods
Tavallaee, M., Stakhanova, N., & Ghorbani, A. A. (2010) · IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) · doi:10.1109/tsmcc.2010.2048428 · Cited by 280
Cited by
A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks
Yin, C., Zhu, Y., Fei, J., & He, X. (2017) · IEEE Access · doi:10.1109/access.2017.2762418 · Cited by 2,100
Decision Tree Based Intrusion Detection System for NSL-KDD Dataset
Ingre, B., Yadav, A., & Soni, A. K. (2018) · Smart Innovation, Systems and Technologies · doi:10.1007/978-3-319-63645-0_23 · Cited by 150
Self-citation
Metadata
- Authors
- Ingre, B., & Yadav, A.
- Venue
- 2015 International Conference on Signal Processing and Communication Engineering Systems
- Publisher
- IEEE
- Published
- 2015-01
- Pages
- 92-96
- OpenAlex
- W1995678176
- Cited by
- 374
- References
- 1
- FWCI
- 8.49
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Ingre, B., & Yadav, A. (2015). Performance analysis of NSL-KDD dataset using ANN. 2015 International Conference on Signal Processing and Communication Engineering Systems. https://doi.org/10.1109/spaces.2015.7058223
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