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 Multi-class SVM based network intrusion detection with attribute selection using infinite feature selection technique Subject The topic of the resource 15A06; 15A09; 17B10; 17B15; 18A10; 18C05; 18C10; 18D35; Anomaly detection; Infinity feature selection; Intrusion detection system; Machine learning; Multiclass support vector machine; Support vector machine Description An account of the resource An intrusion detection mechanism is a software program or a device that monitors the network and provides information about any suspicious activity. This paper proposes a multi-class support vector machine (SVM) based network intrusion detection using an infinite feature selection technique for identifying suspicious activity. Single and multiple classifiers generally have high complexity. To overcome all the limitations of single and multiple classifiers, we used a multi-class classifier using an infinite feature selection technique, which performed well with multiple classes and gave better results than other classifiers in terms of accuracy, precision, recall, and f_score. Infinite feature selection is a graph-based filtering approach that analyses subsets of features as routes in a graph. We used a standard dataset, namely the UNSW_NB15 data set generated by the IXIA perfect-storm tool in the Australian Centre for Cyber Security. This dataset has a total of nine types of attacks and 49 features. The comparative analysis of the manuscript work is done against eight different techniques, namely, hybrid intrusion detection system (HIDS), C5, one-class support vector machine, and others. The proposed work gave better simulation results using the 2015a Matlab simulator. 2021 Taru Publications. Creator An entity primarily responsible for making the resource Kaushik R.; Singh V.; Kumari R. Source A related resource from which the described resource is derived Journal of Discrete Mathematical Sciences and Cryptography, Vol-24, No. 8, pp. 2137-2153. Publisher An entity responsible for making the resource available Taylor and Francis Ltd. Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1080/09720529.2021.2009189" target="_blank" rel="noreferrer noopener">https://doi.org/10.1080/09720529.2021.2009189</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121849325&amp;doi=10.1080%2F09720529.2021.2009189&amp;partnerID=40&amp;md5=afc29c113f3a505b7496bd8acbb49e57" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121849325&amp;doi=10.1080%2f09720529.2021.2009189&amp;partnerID=40&amp;md5=afc29c113f3a505b7496bd8acbb49e57</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 9720529 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 Kaushik R., Amity Institute of Information Technology, Amity University Rajasthan, Rajasthan, Jaipur, 303002, India; Singh V., Department of Computer Science Engineering, Manipal University Jaipur, Rajasthan, Jaipur, 302002, India; Kumari R., Department of Computer Science, CHRIST (Deemed to be University), Karnataka, Bangalore, 560029, India