Staked deep ensemble model for intruder behaviour detection and classification in cloud
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17677-9.pdf
Reference36 articles.
1. Hajimirzaei B, Navimipour NJ (2018) Intrusion detection for cloud computing using neural networks and artificial bee colony optimization algorithm. ICT Express 5(1):5659. https://doi.org/10.1016/j.icte.2018.01.014
2. Wang W, Du X, Shan D, Qin R, Wang N (2020) Cloud intrusion detection method based on stacked contractive auto-encoder and support vector machine. IEEE transactions on cloud computing 10(3):1634–1646. https://doi.org/10.1109/TCC.2020.3001017
3. Wahab OA, Bentahar J, Otrok H, Mourad A (2019) Resource-aware detection and defense system against multi-type attacks in the cloud: Repeated bayesian stackelberg game. IEEE Trans Dependable Secure Comput 18(2):605–622. https://doi.org/10.1109/TDSC.2019.2907946
4. Alkadi O, Moustafa N, Turnbull B, Choo KR (2020) A deep blockchain framework-enabled collaborative intrusion detection for protecting IoT and cloud networks. IEEE Int Things J 8(12):9463–9472. https://doi.org/10.1109/JIOT.2020.2996590
5. Mishra P, Varadharajan V, Pilli E, Tupakula U (2018) VMGuard: A vmi-based security architecture for intrusion detection in cloud environment, in IEEE Trans Cloud Comput. https://doi.org/10.1109/TCC.2018.2829202
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