{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:43:36Z","timestamp":1775609016730,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T00:00:00Z","timestamp":1627257600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Rapid Internet use growth and applications of diverse military have managed researchers to develop smart systems to help applications and users achieve the facilities through the provision of required service quality in networks. Any smart technologies offer protection in interactions in dispersed locations such as, e-commerce, mobile networking, telecommunications and management of network. Furthermore, this article proposed on intelligent feature selection methods and intrusion detection (ISTID) organization in webs based on neuron-genetic algorithms, intelligent software agents, genetic algorithms, particulate swarm intelligence and neural networks, rough-set. These techniques were useful to identify and prevent network intrusion to provide Internet safety and improve service value and accuracy, performance and efficiency. Furthermore, new algorithms of intelligent rules-based attributes collection algorithm for efficient function and rules-based improved vector support computer, were proposed in this article, along with a survey into the current smart techniques for intrusion detection systems.<\/jats:p>","DOI":"10.3390\/a14080224","type":"journal-article","created":{"date-parts":[[2021,7,26]],"date-time":"2021-07-26T09:25:52Z","timestamp":1627291552000},"page":"224","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":110,"title":["Intelligent Network Intrusion Prevention Feature Collection and Classification Algorithms"],"prefix":"10.3390","volume":"14","author":[{"given":"Deepaa","family":"Selva","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering, Karpagam University, Coimbatore 641021, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Balakrishnan","family":"Nagaraj","sequence":"additional","affiliation":[{"name":"Rathinam Group of Institution, Rathinam Technical Campus, Coimbatore 641021, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Danil","family":"Pelusi","sequence":"additional","affiliation":[{"name":"Faculty of Communication Sciences, University of Teramo, 64100 Teramo, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajendran","family":"Arunkumar","sequence":"additional","affiliation":[{"name":"Rathinam Group of Institution, Rathinam Technical Campus, Coimbatore 641021, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ajay","family":"Nair","sequence":"additional","affiliation":[{"name":"Rathinam Group of Institution, Rathinam Technical Campus, Coimbatore 641021, Tamil Nadu, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1007\/s12083-017-0630-0","article-title":"Survey on SDN based network intrusion detection system using machine learning approaches","volume":"12","author":"Sultana","year":"2019","journal-title":"Peer Peer Netw. 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