A Detailed Analysis on NSL-KDD Dataset Using Various Machine Learning Techniques for Intrusion Detection
By Sathyanarayanan Revathi, A. Malathi. 2013
490 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/633e8d65bbc7e11b66e99d01972d6c5cc0489b52
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Citations in the corpus
- Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model (2017, methodology): “A detailed NSL-KDD dataset analysis using different machine learning techniques was performed with the use of a WEKA tool and discussed in [37].”
- A survey of deep learning-based network anomaly detection (2017, methodology): “Section 2 provides an overview of anomaly detection methodologies and a group of deep learning techniques with the KDDCup 1999-class datasets [10,11] widely used for the network anomaly detection study.”
- An Adaptive Ensemble Machine Learning Model for Intrusion Detection (2019, methodology): “[6] S. Revathi andA.”
- A Survey of Machine Learning Techniques Applied to Software Defined Networking (SDN): Research Issues and Challenges (2019, background): “NSL-KDD is a modified version of KDD99 dataset and has solved many inherent problems of KDD99 dataset.”
- A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks (2017, methodology): “The NSL-KDD dataset [21], [22] generated in 2009 is widely used in intrusion detection experiments.”
- A Study on NSL-KDD Dataset for Intrusion Detection System Based on Classification Algorithms (2015, methodology): “A detailed analysis on the NSL-KDD data set using various machine learning techniques is done in [6] available in the WEKA tool.”
- BAT: Deep Learning Methods on Network Intrusion Detection Using NSL-KDD Dataset (2020, background): “out on a public dataset: the NSL-KDD dataset [46], [47].”