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 Blocking intrusion logic using optimized multi-head convolution in wireless sensor network Subject The topic of the resource k-means clustering; multi-head convolutional neural network; Salp Swarm optimization; Wireless sensor nodes Description An account of the resource Wireless sensor nodes (WSN) combine sensing and communication capabilities in the smallest sensor network component. Sensor nodes have basic networking capabilities, such as wireless connection with other nodes, data storage, and a microcontroller to do basic processing. The intrusion detection problem is well analyzed and there exist numerous techniques to solve this issue but suffer will poor intrusion detection accuracy and a higher false alarm ratio. To overcome this challenge, a novel Intrusion Detection via Salp Swarm Optimization based Deep Learning Algorithm (ID-SODA) has been proposed which classifies intrusion node and non-intrusion node. The proposed ID-SODA technique uses the k-means clustering algorithm to perform clustering. The Salp Swarm Optimization (SSO) technique takes into residual energy, distance, and cost while choosing the cluster head selection (CHS). The CHS is given the input to a multi-head convolutional neural network (MHCNN), which will classify into intrusion node and non-intrusion node. The performance analysis of the suggested ID-SODA is evaluated based on the parameters like accuracy, precision, F1 score, detection rate, recall, false alarm rate, and false negative rate. The suggested ID-SODA achieves an accuracy range of 98.95%. The result shows that the suggested ID-SODA improves the overall accuracy better than 6.56%, 2.94%, and 2.95% in SMOTE, SLGBM, and GWOSVM-IDS respectively. 2023 - IOS Press. All rights reserved. Creator An entity primarily responsible for making the resource Prabhu S.; Mary Anita E.A.; Mohanageetha D. Source A related resource from which the described resource is derived Journal of Intelligent and Fuzzy Systems, Vol-45, No. 4, pp. 6897-6909. Publisher An entity responsible for making the resource available IOS Press BV Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.3233/JIFS-231756" target="_blank" rel="noreferrer noopener">https://doi.org/10.3233/JIFS-231756</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173900285&amp;doi=10.3233%2FJIFS-231756&amp;partnerID=40&amp;md5=fbd90c183cd9f237a7ab803adbd95cba" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173900285&amp;doi=10.3233%2fJIFS-231756&amp;partnerID=40&amp;md5=fbd90c183cd9f237a7ab803adbd95cba</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 10641246 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 Prabhu S., Department of Computer Science and Engineering, S.A. Engineering College, Tamil Nadu, Chennai, India; Mary Anita E.A., Department of Computer Science Engineering, Christ University, Karnataka, Bengaluru, India; Mohanageetha D., Department of Electronics and Communication Engineering, Sri Krishna College of Engineering and Technology, Tamil Nadu, Coimbatore, India