{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T02:59:35Z","timestamp":1763348375768,"version":"3.37.3"},"reference-count":35,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100003626","name":"Defense Acquisition Program Administration","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003626","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005073","name":"Agency for Defense Development","doi-asserted-by":"publisher","award":["UD2000014ED"],"award-info":[{"award-number":["UD2000014ED"]}],"id":[{"id":"10.13039\/501100005073","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3120839","type":"journal-article","created":{"date-parts":[[2021,10,15]],"date-time":"2021-10-15T23:44:30Z","timestamp":1634341470000},"page":"142348-142361","source":"Crossref","is-referenced-by-count":24,"title":["Study on Network Intrusion Detection Method Using Discrete Pre-Processing Method and Convolution Neural Network"],"prefix":"10.1109","volume":"9","author":[{"given":"Jihoon","family":"Yoo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Byeongjun","family":"Min","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangsoo","family":"Kim","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8621-715X","authenticated-orcid":false,"given":"Dongil","family":"Shin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2665-3339","authenticated-orcid":false,"given":"Dongkyoo","family":"Shin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3390\/s20051452"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/ICEEOT.2016.7755181"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/382912.382923"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-23502-4_12"},{"key":"ref34","first-page":"1133","article-title":"I-SiamIDS: An improved siam-IDS for handling class imbalance in network-based intrusion detection systems","volume":"51","author":"bedi","year":"2021","journal-title":"Int J Speech Technol"},{"key":"ref10","article-title":"Shallow and deep networks intrusion detection system—A taxonomy and survey","author":"hodo","year":"0","journal-title":"Cryptography and Security"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2868993"},{"key":"ref12","first-page":"569","article-title":"An improved CNN approach for network intrusion detection system","volume":"23","author":"hu","year":"2021","journal-title":"Int J Netw Secur"},{"key":"ref13","first-page":"50","article-title":"Learning intrusion detection: Supervised or unsupervised","author":"laskov","year":"2005","journal-title":"Proc Int Conf Image Anal Process"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CCECE.2003.1226084"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/11795131_78"},{"key":"ref16","first-page":"1790","article-title":"Feature reduction using principal component analysis for effective anomaly-based intrusion detection on NSL-KDD","volume":"2","author":"lakhina","year":"2010","journal-title":"Int J Eng Sci Technol"},{"key":"ref17","first-page":"184","article-title":"Feature selection for intrusion detection using NSL-KDD","volume":"20132","author":"chae","year":"2013","journal-title":"Recent Advances in Engineering and Computer Science"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ETFA.2016.7733515"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23204"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1080\/02664763.2019.1643829"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2019.2899085"},{"key":"ref27","first-page":"1","article-title":"Application of high-dimensional outlier mining based on the maximum frequent pattern factor in intrusion detection","volume":"2021","author":"shen","year":"2021","journal-title":"Math Problems Eng"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2020.102141"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2841987"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-69717-4_23"},{"key":"ref5","first-page":"1385","article-title":"Machine learning based intrusion detection systems for class imbalanced datasets","volume":"27","author":"cheong","year":"2017","journal-title":"J Korea Inst Inf Secur Cryptol"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CompComm.2017.8322749"},{"key":"ref7","first-page":"1157","article-title":"SMOTE-NCL: A re-sampling method with filter for network intrusion detection","author":"sun","year":"2016","journal-title":"Proc 2nd IEEE Int Conf Comput Commun (ICCC)"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2016.0108"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2015.12.006"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICETET.2008.252"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2019.106944"},{"journal-title":"A novel method for classification of tabular data using convolutional neural networks","year":"2020","author":"buturovi?","key":"ref22"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-47765-6"},{"key":"ref24","first-page":"1","article-title":"A hierarchical hybrid intrusion detection approach in IoT scenarios","author":"bovenzi","year":"2020","journal-title":"Proc IEEE Global Communications Conf GLOBECOM"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2019.112963"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-00930-8_19"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/S0888-613X(96)00074-6"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09576688.pdf?arnumber=9576688","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,21]],"date-time":"2022-02-21T22:24:32Z","timestamp":1645482272000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9576688\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":35,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3120839","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2021]]}}}