{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T15:16:27Z","timestamp":1777389387852,"version":"3.51.4"},"reference-count":27,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31870532"],"award-info":[{"award-number":["31870532"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004735","name":"Natural Science Foundation of Hunan Province","doi-asserted-by":"publisher","award":["2021JJ31163"],"award-info":[{"award-number":["2021JJ31163"]}],"id":[{"id":"10.13039\/501100004735","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3334916","type":"journal-article","created":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T19:29:10Z","timestamp":1700508550000},"page":"136308-136317","source":"Crossref","is-referenced-by-count":39,"title":["CNN-AttBiLSTM Mechanism: A DDoS Attack Detection Method Based on Attention Mechanism and CNN-BiLSTM"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6800-4847","authenticated-orcid":false,"given":"Junjie","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Computer and Information, Central South University of Forestry and Technology, Changsha, China"}]},{"given":"Yongmin","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Central South University of Forestry and Technology, Changsha, China"}]},{"given":"Qianlei","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer and Information, Central South University of Forestry and Technology, Changsha, China"}]},{"given":"Xinying","family":"Zheng","sequence":"additional","affiliation":[{"name":"Business School, Hunan Normal University, Changsha, China"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"HUAWEI: Special Report on Botnets and DDoS Attacks in 2013","year":"2013"},{"issue":"10","key":"ref2","first-page":"3068","article-title":"DDoS attack detection method based on random forest","volume":"34","author":"Yu","year":"2017","journal-title":"Appl. Res. Comput."},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2805600"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2018.03.024"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2017.08.043"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/9804061"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICOIN.2018.8343104"},{"key":"ref8","article-title":"A DDoS attack behavior detection method based on deep learning","author":"Oena","year":"2016","journal-title":"arXiv:1601.04033"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2780250"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.32604\/cmc.2020.06177"},{"issue":"3","key":"ref11","first-page":"718","article-title":"Anomaly intrusion behavior detection based on fuzzy clustering and features selection","volume":"52","author":"Tang","year":"2015","journal-title":"Comput. Res. Develop."},{"issue":"4","key":"ref12","first-page":"802","article-title":"Intuitionistic fuzzy entropy feature selection algorithm based on adaptive neighborhood space rough set model","volume":"55","author":"Yao","year":"2018","journal-title":"Comput. Res. Develop."},{"issue":"8","key":"ref13","first-page":"1695","article-title":"An adaptive regression feature selection method for datasets with outliers","volume":"56","author":"Yaqing","year":"2019","journal-title":"Comput. Res. Develop."},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3369555.3369572"},{"issue":"12","key":"ref15","first-page":"7","article-title":"Network intrusion detection method integrating CNN and BiLSTM","volume":"45","author":"Yuefeng","year":"2019","journal-title":"Comput. Eng."},{"issue":"6","key":"ref16","first-page":"839","article-title":"End-to-end keyword search system based on attention mechanism and multitask learning","volume":"36","author":"Zhao","year":"2020","journal-title":"Signal Process."},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2016.7472618"},{"issue":"11","key":"ref18","first-page":"226","article-title":"Neural machine translation based on attentiom convolution","volume":"45","author":"Wang","year":"2018","journal-title":"Comput. Sci."},{"issue":"4","key":"ref19","first-page":"66","article-title":"Chinese part-of-speech tagging model using attention-based LSTM","volume":"45","author":"Si","year":"2018","journal-title":"Comput. Sci."},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2890394"},{"key":"ref21","volume-title":"An attentional mechanism text recognition method based on deep learning","author":"Yang","year":"2023"},{"key":"ref22","volume-title":"The CAIDA UCSD \u2018DDoS Attack 2007\u2019 Dataset"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/SMARTCOMP.2017.7946998"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/1192\/1\/012018"},{"key":"ref25","volume-title":"DDoS Evaluation Dataset (CIC-DDoS2019)","year":"2019"},{"key":"ref26","first-page":"13","article-title":"SVM algorithm based on RF and quantum particle swarm optimization","volume":"1","author":"Cui","year":"2021","journal-title":"Comput. Integr. Manuf. Syst."},{"key":"ref27","volume-title":"Deep learning for network traffic classification and anomaly detection","author":"Wang"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10323325.pdf?arnumber=10323325","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T01:13:44Z","timestamp":1705022024000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10323325\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3334916","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}