Machine learning and deep learning methods for intrusion detection systems: recent developments and challenges
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-021-05893-0.pdf
Reference162 articles.
1. Abdullah B, Abd-Alghafar I, Salama GI, Abd-Alhafez A (2009) Performance evaluation of a genetic algorithm based approach to network intrusion detection system. In: International conference on aerospace sciences and aviation technology. The Military Technical College, pp 1–17
2. Abubakar AI, Chiroma H, Muaz SA, Ila LB (2015) A review of the advances in cyber security benchmark datasets for evaluating data-driven based intrusion detection systems. In: SCSE, pp 221–227
3. Aburomman AA, Reaz MBI (2016) Ensemble of binary SVM classifiers based on pca and lda feature extraction for intrusion detection. In: 2016 IEEE advanced information management, communicates, electronic and automation control conference (IMCEC). IEEE, pp 636–640
4. Aghdam MH, Kabiri P (2016) Feature selection for intrusion detection system using ant colony optimization. IJ Netw Secur 18(3):420–432
5. Aissa NB, Guerroumi M (2016) Semi-supervised statistical approach for network anomaly detection. Procedia Comput Sci 83:1090–1095
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