FACVO-DNFN: Deep learning-based feature fusion and Distributed Denial of Service attack detection in cloud computing
- Title
- FACVO-DNFN: Deep learning-based feature fusion and Distributed Denial of Service attack detection in cloud computing
- Creator
- Emil Selvan G.S.R.; Ganeshan R.; Jingle I.D.J.; Ananth J.P.
- Description
- Cloud computing offers a broad range of resource pools for conserving a huge quantity of information. Due to the intrusion of attackers, the information that exists in the cloud is threatened. Distributed Denial of Service (DDoS) attack is the main reason for attacks in the cloud. In this study, a Fractional Anti Corona Virus Optimization-based Deep Neuro-Fuzzy Network (FACVO-based DNFN) is devised for detecting DDoS in the cloud. The production of log files, feature fusion, data augmentation, and DDoS attack detection is the processing stages involved in this phase of the DDoS attack detection process. The feature fusion is carried out by RV coefficient and Deep Quantum Neural Network (Deep QNN), and the data augmentation is performed. Then, the Anti Corona Virus Optimization (ACVO) method and Fractional Calculus (FC) are both incorporated to create the FACVO algorithm. The DNFN is trained by the created FACVO algorithm, which identifies the DDoS attack. The proposed approach achieved testing accuracy, TPR, TNR, and precision values of 0.9304, 0.9088, 0.9293, and 0.8745 for using the NSL-KDD dataset without attack, and 0.9200, 0.8991, 0.9015, and 0.8648 for using the BoT-IoT dataset without attack. 2022 Elsevier B.V.
- Source
- Knowledge-Based Systems, Vol-261
- Date
- 2023-01-01
- Publisher
- Elsevier B.V.
- Subject
- Anti Corona Virus Optimization; Deep neuro-fuzzy network; Deep Quantum Neural Network; Distributed denial of service; Fractional Calculus
- Coverage
- Emil Selvan G.S.R., Assistant Professor, Department of Computer Science and Engineering, Thiagarajar College of Engineering, Madurai, 625015, India; Ganeshan R., Assistant Professor Senior Grade - II, School of Computing Science And Engineering, VIT Bhopal University, Bhopal-Indore Highway, Kothrikalan, Madhya Pradesh, Sehore, 466114, India; Jingle I.D.J., Associate Professor, Department of CSE, School of Engineering and Technology, Christ University, Karnataka, Bangalore, India; Ananth J.P., Professor, Department of CSE, Sri Krishna College of Engineering and Technology, Tamil Nadu, Coimbatore, India
- Rights
- Restricted Access
- Relation
- ISSN: 9507051; CODEN: KNSYE
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Emil Selvan G.S.R.; Ganeshan R.; Jingle I.D.J.; Ananth J.P., “FACVO-DNFN: Deep learning-based feature fusion and Distributed Denial of Service attack detection in cloud computing,” CHRIST (Deemed To Be University) Institutional Repository, accessed April 21, 2025, https://archives.christuniversity.in/items/show/14385.