{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T15:53:51Z","timestamp":1780502031284,"version":"3.54.1"},"reference-count":24,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T00:00:00Z","timestamp":1623801600000},"content-version":"vor","delay-in-days":166,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Given the growth of wireless networks and the increase of the advantages and applications of communication networks, especially mobile ad hoc networks (MANETs), this type of network has attracted the attention of users and researchers more than before. The benefit of these types of networks in various kinds of networks and environments is that MANET does not require to hardware infrastructure to communicate and send and receive data packets within the network. It is one of the main reasons for using these MANET in various fields. On the other hand, the increased popularity of these networks has led to many challenges, one of the most important of which is network security. In this regard, a lack of regulatory and security infrastructure in MANETs has caused some problems in sending and receiving data, where intrusion in the network has been recognized as one of the most important issues. In MANETs, wireless notes act as a link between the source and destination nodes and play the role of relays and routers in the network. Therefore, malicious node penetration and the destruction of information packages become feasible. Today, intrusion detection systems (IDSs) are used as a solution to deal with the problem through remote monitoring of the performance and behaviors of nodes existing in wireless sensor networks. In addition to detecting malicious nodes in the network, IDSs can predict the behavior of malicious nodes in the future in most cases. Therefore, the present study introduced a network IDS (NIDS) entitled MOPSO\u2010FLN by using a combination of multiobjective particle swarm optimization algorithm\u2010 (MOPSO\u2010) based feature subset selection (FSS) and fast\u2010learning network (FLN). In this work, we used the KDD Cup99 and dataset to select features, train the network, and test the model. According to the simulation results, this method was able to improve the performance of the IDS in terms of evaluation criteria, compared to other previous methods, by creating a balance between the objectives of the number of representative features and training errors based on the evolutionary power of MOPSO.<\/jats:p>","DOI":"10.1155\/2021\/6648351","type":"journal-article","created":{"date-parts":[[2021,6,16]],"date-time":"2021-06-16T23:35:11Z","timestamp":1623886511000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Network Intrusion Detection System Based on the Combination of Multiobjective Particle Swarm Algorithm\u2010Based Feature Selection and Fast\u2010Learning Network"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7923-5253","authenticated-orcid":false,"given":"Sajad","family":"Einy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9742-6021","authenticated-orcid":false,"given":"Cemil","family":"Oz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6486-7223","authenticated-orcid":false,"given":"Yahya Dorostkar","family":"Navaei","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2021,6,16]]},"reference":[{"key":"e_1_2_8_1_2","doi-asserted-by":"crossref","unstructured":"SaxenaA. K. SinhaS. andShuklaP. A review on intrusion detection system in mobile ad-hoc network 2017 International Conference on Recent Innovations in Signal processing and Embedded Systems (RISE) 2018 Bhopal India 549\u2013554 https:\/\/doi.org\/10.1109\/RISE.2017.8378216 2-s2.0-85049775082.","DOI":"10.1109\/RISE.2017.8378216"},{"key":"e_1_2_8_2_2","doi-asserted-by":"crossref","unstructured":"MuruganandamS. RenjitJ. A. andKumarR. S. A survey: comparative study of security methods and trust manage solutions in MANET 2019 Fifth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) 2019 Chennai India 125\u2013131 https:\/\/doi.org\/10.1109\/ICONSTEM.2019.8918697.","DOI":"10.1109\/ICONSTEM.2019.8918697"},{"key":"e_1_2_8_3_2","doi-asserted-by":"crossref","unstructured":"SinghV. SinghD. A. andHassanM. M. Survey: black hole attack detection in MANET Proceedings of 2nd International Conference on Advanced Computing and Software Engineering (ICACSE) 2019 Sultanpur UP India https:\/\/doi.org\/10.2139\/ssrn.3351016.","DOI":"10.2139\/ssrn.3351016"},{"key":"e_1_2_8_4_2","first-page":"1","article-title":"A survey on various applications and blackhole attack in mobile ad hoc network","volume":"5","author":"Gupta A.","year":"2018","journal-title":"Recent Trends in Parallel Computing"},{"key":"e_1_2_8_5_2","first-page":"37","article-title":"A comprehensive study on defence against wormhole attack methods in mobile ad hoc networks","volume":"2","author":"Fotohi R.","year":"2014","journal-title":"International journal of Computer Science & Network Solutions"},{"key":"e_1_2_8_6_2","first-page":"11","article-title":"Evaluation metrics for intrusion detection systems-a study","volume":"2","author":"Kumar Ahuja G.","year":"2014","journal-title":"Evaluation"},{"key":"e_1_2_8_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2016.04.005"},{"key":"e_1_2_8_8_2","doi-asserted-by":"crossref","unstructured":"SultanaA.andJabbarM. 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Intelligent network intrusion detection system using data mining techniques 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT) 2017 Bangalore India 329\u2013333 https:\/\/doi.org\/10.1109\/ICATCCT.2016.7912017 2-s2.0-85020168473.","DOI":"10.1109\/ICATCCT.2016.7912017"},{"key":"e_1_2_8_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-0184-5_27"},{"key":"e_1_2_8_10_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11390-016-1630-x"},{"key":"e_1_2_8_11_2","first-page":"99","article-title":"A survey of intrusion detection with higher malicious misbehavior detection in MANET","volume":"8","author":"Rajalakshmi D.","year":"2017","journal-title":"International journal of civil engineering and technology"},{"key":"e_1_2_8_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2820092"},{"key":"e_1_2_8_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2018.11.005"},{"key":"e_1_2_8_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2018.01.023"},{"key":"e_1_2_8_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113249"},{"key":"e_1_2_8_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107247"},{"key":"e_1_2_8_17_2","first-page":"746","article-title":"Intrusion detection system using fuzzy rough set feature selection and modified KNN classifier","volume":"16","author":"Senthilnayaki B.","year":"2019","journal-title":"The International Arab Journal of Information Technology"},{"key":"e_1_2_8_18_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-32-9990-0_9"},{"key":"e_1_2_8_19_2","doi-asserted-by":"crossref","unstructured":"Coello CoelloC. A.andLechugaM. S. MOPSO: a proposal for multiple objective particle swarm optimization 2 Proceedings of the 2002 Congress on Evolutionary Computation. CEC\u203202 (Cat. No. 02TH8600) 2002 Honolulu HI USA 1051\u20131056 https:\/\/doi.org\/10.1109\/CEC.2002.1004388 2-s2.0-84901438927.","DOI":"10.1109\/CEC.2002.1004388"},{"key":"e_1_2_8_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2014.09.078"},{"key":"e_1_2_8_21_2","unstructured":"KDD Cup Computer Network Intrusion Detection 1999 https:\/\/www.kdd.org\/kdd-cup\/view\/kdd-cup-1999."},{"key":"e_1_2_8_22_2","doi-asserted-by":"crossref","unstructured":"AlmseidinM. AlzubiM. KovacsS. andAlkasassbehM. 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