{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T13:40:07Z","timestamp":1755870007738,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":16,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,11,3]],"date-time":"2023-11-03T00:00:00Z","timestamp":1698969600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,3]]},"DOI":"10.1145\/3640115.3640189","type":"proceedings-article","created":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T12:10:58Z","timestamp":1711455058000},"page":"455-461","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Research on Network Security Technology Based on Machine Learning"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3495-5381","authenticated-orcid":false,"given":"Fei","family":"Han","sequence":"first","affiliation":[{"name":"School of Cyberspace Security, Qufu Normal University, China"}]}],"member":"320","published-online":{"date-parts":[[2024,3,26]]},"reference":[{"volume-title":"A survey of data mining and machine learning methods for cyber security intrusion detection[J]","year":"2015","key":"e_1_3_2_1_1_1","unstructured":"BUCZAK A L, GUVEN E. A survey of data mining and machine learning methods for cyber security intrusion detection[J]. IEEE Communications surveys & tutorials, 2015, 18(2): 1153-1176."},{"volume-title":"Anomaly detection for industry product quality inspection based on gaussian restricted boltzmann machine[C]\/\/2019 IEEE international conference on systems, man and cybernetics (SMC)","year":"2019","key":"e_1_3_2_1_2_1","unstructured":"ZHANG Y, PENG P, LIU C, Anomaly detection for industry product quality inspection based on gaussian restricted boltzmann machine[C]\/\/2019 IEEE international conference on systems, man and cybernetics (SMC). IEEE, 2019: 1-6."},{"volume-title":"Unsupervised anomaly detection using variational auto-encoder based feature extraction[C]\/\/2019 IEEE International Conference on Prognostics and Health Management (ICPHM)","year":"2019","key":"e_1_3_2_1_3_1","unstructured":"YAO R, LIU C, ZHANG L, Unsupervised anomaly detection using variational auto-encoder based feature extraction[C]\/\/2019 IEEE International Conference on Prognostics and Health Management (ICPHM). IEEE, 2019: 1-7."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"AGARAP A F M. A neural network architecture combining gated recurrent unit (gru) and support vector machine (svm) for intrusion detection in network traffic data[C]\/\/Proceedings of the 2018 10th international conference on machine learning and computing. 2018: 26-30.","DOI":"10.1145\/3195106.3195117"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2868993"},{"key":"e_1_3_2_1_6_1","unstructured":"LIN Z SHI Y XUE Z. Idsgan: Generative adversarial networks for attack generation against intrusion detection[A]. 2018: 12-18."},{"key":"e_1_3_2_1_7_1","first-page":"1","article-title":"Building combined intrusion detection model based on imbalanced learning and gated recurrent unit neural network[J]","volume":"2018","author":"La","year":"2018","unstructured":"YAN B, HAN G. La-gru: Building combined intrusion detection model based on imbalanced learning and gated recurrent unit neural network[J]. Security and Communication Networks, 2018, 2018: 1-13.","journal-title":"Security and Communication Networks"},{"key":"e_1_3_2_1_8_1","volume-title":"Shah S. A Comprehensive Survey of Machine Learning-Based Network Intrusion Detection: Proceedings of the Second International Conference on SCI","volume":"356","author":"Chapaneri R","year":"2018","unstructured":"Chapaneri R, Shah S. A Comprehensive Survey of Machine Learning-Based Network Intrusion Detection: Proceedings of the Second International Conference on SCI 2018, Volume 1[M]. 2019:345-356."},{"volume-title":"2020 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR). IEEE","author":"Sahu A","key":"e_1_3_2_1_9_1","unstructured":"Sahu A, Mao Z, Davis K, Data Processing and Model Selection for Machine Learning-based Network Intrusion Detection[C]\/\/ 2020 IEEE International Workshop Technical Committee on Communications Quality and Reliability (CQR). IEEE, 2020:1-6."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2020.3014929"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115782"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3101188"},{"key":"e_1_3_2_1_13_1","volume-title":"Machine learning based network intrusion detection[C]\/\/ 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)","author":"Lee C H","year":"2017","unstructured":"Lee C H, Su Y Y, Lin Y C, Machine learning based network intrusion detection[C]\/\/ 2017 2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA). IEEE, 2017:79-83."},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3051074"},{"key":"e_1_3_2_1_15_1","volume-title":"Network Intrusion Detection Based on Sparse Autoencoder and IGA-BP Network[J]. Wireless Communications and Mobile Computing","author":"Deng H","year":"2021","unstructured":"Deng H, Yang T. Network Intrusion Detection Based on Sparse Autoencoder and IGA-BP Network[J]. Wireless Communications and Mobile Computing, 2021: 9510858."},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2021.103266"}],"event":{"name":"ICITEE 2023: 6th International Conference on Information Technologies and Electrical Engineering","acronym":"ICITEE 2023","location":"Changde, Hunan China"},"container-title":["Proceedings of the 6th International Conference on Information Technologies and Electrical Engineering"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640115.3640189","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3640115.3640189","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T13:10:14Z","timestamp":1755868214000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3640115.3640189"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,3]]},"references-count":16,"alternative-id":["10.1145\/3640115.3640189","10.1145\/3640115"],"URL":"https:\/\/doi.org\/10.1145\/3640115.3640189","relation":{},"subject":[],"published":{"date-parts":[[2023,11,3]]},"assertion":[{"value":"2024-03-26","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}