An Ensemble Feature Selection Approach for Intrusion Detection Systems
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1961-7_27
Reference19 articles.
1. Anwer HM, Farouk M, Abdel-Hamid A (2018) A framework for efficient network anomaly intrusion detection with features selection. In: 2018 9th International Conference on Information and Communication Systems (ICICS), 157–162. IEEE
2. Belouch M, El Hadaj S, Idhammad M (2017) A two-stage classifier approach using a reptree algorithm for network intrusion detection. Int J Adv Comput Sci Appl 8(6):389–394
3. Bolón-Canedo V, Alonso-Betanzos A (2019) Ensembles for feature selection: a review and future trends. Information Fus 52:1–12
4. Hajisalem V, Babaie S (2018) A hybrid intrusion detection system based on the ABC-AFS algorithm for misuse and anomaly detection. Comput Netw 136:37–50
5. Rawat R et al (2021) Surveillance robot in cyber intelligence for vulnerability detection. In: Bianchini M, Simic M, Ghosh A, Shaw RN (eds) Machine learning for robotics applications. Studies in Computational Intelligence, vol 960. Springer, Singapore. https://doi.org/10.1007/978-981-16-0598-7_9
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