Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet
- Title
- Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet
- Creator
- Vatambeti R.; Venkatesh D.; Mamidisetti G.; Damera V.K.; Manohar M.; Yadav N.S.
- Description
- Integrating cutting-edge technology with conventional farming practices has been dubbed smart agriculture or the agricultural internet of things. Agriculture 4.0, made possible by the merging of Industry 4.0 and Intelligent Agriculture, is the next generation after industrial farming. Agriculture 4.0 introduces several additional risks, but thousands of IoT devices are left vulnerable after deployment. Security investigators are working in this area to ensure the safety of the agricultural apparatus, which may launch several DDoS attacks to render a service inaccessible and then insert bogus data to convince us that the agricultural apparatus is secure when, in fact, it has been stolen. In this paper, we provide an IDS for DDoS attacks that is built on one-dimensional convolutional neural networks (IDSNet). We employed prairie dog optimization (PDO) to fine-tune the IDSNet training settings. The proposed model's efficiency is compared to those already in use using two newly published real-world traffic datasets, CIC-DDoS attacks. 2023, Springer Nature Limited.
- Source
- Scientific Reports, Vol-13, No. 1
- Date
- 2023-01-01
- Publisher
- Nature Research
- Coverage
- Vatambeti R., School of Computer Science and Engineering, VIT-AP University, Vijayawada, India; Venkatesh D., Department of Computer Science and Engineering, GITAM School of Technology, GITAM University-Bengaluru Campus, Bengaluru, India; Mamidisetti G., Department of Computer Science and Engineering, Malla Reddy University, Hyderabad, India; Damera V.K., Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Hyderabad, India; Manohar M., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Yadav N.S., Department of Information Technology, Chaitanya Bharathi Institute of Technology, Hyderabad, 500075, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 20452322; PubMed ID: 37717114
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Vatambeti R.; Venkatesh D.; Mamidisetti G.; Damera V.K.; Manohar M.; Yadav N.S., “Prediction of DDoS attacks in agriculture 4.0 with the help of prairie dog optimization algorithm with IDSNet,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 27, 2025, https://archives.christuniversity.in/items/show/13925.