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Cognitive Computation
Erschienen in: Cognitive Computation 5/2023

16.05.2023 | Original Article

Enhanced Quantum-Secure Ensemble Intrusion Detection Techniques for Cloud Based on Deep Learning

verfasst von: Dilli Babu Salvakkam, Vijayalakshmi Saravanan, Praphula Kumar Jain, Rajendra Pamula

Erschienen in: Cognitive Computation | Ausgabe 5/2023

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Abstract

The increasing popularity of cloud computing systems has drawn significant attention from academics and businesses for several decades. However, cloud computing systems are plagued with several concerns, such as privacy, confidentiality, and availability, which can be detrimental to their performance. Intrusion detection has emerged as a critical issue, particularly in detecting new types of intrusions that can compromise the security of cloud systems. Preventive risk models have been developed to check the cloud for potential threats, and the rise of quantum computing attacks necessitates the deployment of an intrusion detection system (IDS) for cloud security risk assessment. This research proposes a unique method for detecting cloud computing intrusions by utilizing the KDDcup 1999, UNSW-NB15, and NSL-KDD datasets to address these concerns. This proposed system is designed to achieve two objectives. Firstly, it analyzes the disadvantages of existing IDS, and secondly, it presents an accuracy enhancement model of IDS. The proposed Ensemble Intrusion Detection Model for Cloud Computing Using Deep Learning (EICDL) is designed to detect intrusions effectively. The performance of the proposed model is compared to modern machine learning methods and existing IDS, and the experimental findings indicate that the EICDL ensemble technique improves detection and can identify subsequent attacks/intrusions with a recall rate of 92.14%. The proposed method EICDL ensemble technique significantly improves the accuracy and efficiency of intrusion detection in cloud systems.
Vorheriger Artikel Tensorized Anchor Graph Learning for Large-scale Multi-view Clustering
Nächster Artikel Cognitive Phenomenology Neuroscience and Computation

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Metadaten
Titel
Enhanced Quantum-Secure Ensemble Intrusion Detection Techniques for Cloud Based on Deep Learning
verfasst von
Dilli Babu Salvakkam
Vijayalakshmi Saravanan
Praphula Kumar Jain
Rajendra Pamula
Publikationsdatum
16.05.2023
Verlag
Springer US
Erschienen in
Cognitive Computation / Ausgabe 5/2023
Print ISSN: 1866-9956
Elektronische ISSN: 1866-9964
DOI
https://doi.org/10.1007/s12559-023-10139-2

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