Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Intrusion Detection Model Based on Hybridization of S-ROA in Deep Learning Model for MANET Subject The topic of the resource Deep learning-based feature extraction; Fuzzy neural classifier; Internet of things; Intrusion detection systems; Spotted hyena-based rider optimization Description An account of the resource A kind of wireless network called a mobile ad hoc network (MANET) can transfer data without the aid of any infrastructure. Due to its short battery life, limited bandwidth, reliance on intermediaries or other nodes, distributed architecture, and self-organisation, the MANET node is vulnerable to many security-related attacks. The Internet of Things (IoT), a more modern networking pattern that can be seen as a superset of the paradigms discussed above, has recently come into existence. It is extremely difficult to secure these networks due to their scattered design and the few resources they have. A key function of intrusion detection systems (IDS) is the identification of hostile actions that impair network performance. It is extremely important that an IDS be able to adapt to such difficulties. As a result, the research creates a deep learning-based feature extraction to increase the machine learning technique's classification accuracy. The suggested model uses outstanding network-constructed feature extraction (RNBFE), which pulls structures from a deep residual network's many convolutional layers. Additionally, RNBFE's numerous parameters cause a lot of configuration issues because they require manual parameter adjustment. Therefore, the integration of the Rider Optimization Algorithm (ROA) and the Spotted Hyena Optimizer (SHO) to frame the new algorithm, Spotted Hyena-based Rider Optimization (S-ROA), is used to adjust the RNBFEs settings. Attack classification is performed on the resulting feature vectors using fuzzy neural classifiers (FNC). The experimental analysis uses two datasets that are publicly accessible. The Author(s), under exclusive licence to Shiraz University 2024. Creator An entity primarily responsible for making the resource Karthik M.G.; Sivaji U.; Manohar M.; Jayaram D.; Gopalachari M.V.; Vatambeti R. Source A related resource from which the described resource is derived Iranian Journal of Science and Technology - Transactions of Electrical Engineering, Vol-48, No. 2, pp. 719-730. Publisher An entity responsible for making the resource available Springer Nature Date A point or period of time associated with an event in the lifecycle of the resource 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s40998-024-00700-6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s40998-024-00700-6</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185130308&amp;doi=10.1007%2Fs40998-024-00700-6&amp;partnerID=40&amp;md5=d21bd92f31db308a5d2e5f674ab1846d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85185130308&amp;doi=10.1007%2fs40998-024-00700-6&amp;partnerID=40&amp;md5=d21bd92f31db308a5d2e5f674ab1846d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 22286179 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Karthik M.G., Department of Computer Science and Engineering, GITAM School of Technology, GITAM University-Bengaluru Campus, Bengaluru, India; Sivaji U., Department of Information Technology, Institute of Aeronautical Engineering, Hyderabad, India; Manohar M., Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, India; Jayaram D., Department of Information Technology, Chaitanya Bharathi Institute of Technology, Hyderabad, India; Gopalachari M.V., Department of Information Technology, Chaitanya Bharathi Institute of Technology, Hyderabad, India; Vatambeti R., School of Computer Science and Engineering, VIT-AP University, Vijayawada, India