{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T01:25:17Z","timestamp":1740101117372,"version":"3.37.3"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T00:00:00Z","timestamp":1665273600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,10,9]],"date-time":"2022-10-09T00:00:00Z","timestamp":1665273600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,10,9]]},"DOI":"10.1109\/smc53654.2022.9945189","type":"proceedings-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T20:49:04Z","timestamp":1668804544000},"page":"544-549","source":"Crossref","is-referenced-by-count":1,"title":["A Hybrid Deep Learning Method for Network Attack Prediction"],"prefix":"10.1109","author":[{"given":"Jing","family":"Bi","sequence":"first","affiliation":[{"name":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"}]},{"given":"Kangyuan","family":"Xu","sequence":"additional","affiliation":[{"name":"Beijing University of Technology,Faculty of Information Technology,Beijing,China,100124"}]},{"given":"Haitao","family":"Yuan","sequence":"additional","affiliation":[{"name":"Beihang University,School of Automation Science and Electrical Engineering,Beijing,China,100191"}]},{"given":"MengChu","family":"Zhou","sequence":"additional","affiliation":[{"name":"New Jersey Institute of Technology,Department of Electrical and Computer Engineering,Newark,USA,07102"}]}],"member":"263","reference":[{"key":"ref10","first-page":"2986","article-title":"Traffic Flow Prediction with Long Short-term Memory Networks (LSTMs)","author":"shao","year":"2017","journal-title":"Proc IEEE Region 10 Annu Int Conf"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1021\/ac60214a047"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.18637\/jss.v022.i08"},{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1109\/TSUSC.2021.3124893"},{"key":"ref14","first-page":"1","article-title":"ARIMA Model for Network Traffic Prediction and Anomaly Detection","author":"moayedi","year":"2008","journal-title":"International Symposium on Information Technology 2008"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1016\/j.asoc.2019.105616"},{"doi-asserted-by":"publisher","key":"ref16","DOI":"10.1155\/2016\/5635673"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/ITOEC49072.2020.9141720"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.1109\/TASE.2021.3077537"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1016\/j.neucom.2020.11.011"},{"doi-asserted-by":"publisher","key":"ref4","DOI":"10.1109\/MNET.011.2000449"},{"doi-asserted-by":"publisher","key":"ref3","DOI":"10.1109\/TSIPN.2017.2749959"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1145\/3064814.3064831"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/TIE.2018.2798605"},{"key":"ref8","article-title":"An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling","author":"bai","year":"2018","journal-title":"arXiv 1803 01271"},{"key":"ref7","first-page":"1929","article-title":"Dropout: A Simple Way to Prevent Neural Networks from Overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"Journal of Machine Learning Research"},{"doi-asserted-by":"publisher","key":"ref2","DOI":"10.1093\/jigpal\/jzu038"},{"doi-asserted-by":"publisher","key":"ref1","DOI":"10.1109\/TIFS.2017.2771238"},{"key":"ref9","article-title":"Attention is All You Need","author":"aswani","year":"2017","journal-title":"Proc Conf Neural Inf Process Syst"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/ACCESS.2019.2948658"},{"key":"ref21","first-page":"1","article-title":"Adam: A Method for Stochastic Optimization","author":"kingma","year":"2015","journal-title":"Proc of the 3rd International Conference for Learning Representations"}],"event":{"name":"2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","start":{"date-parts":[[2022,10,9]]},"location":"Prague, Czech Republic","end":{"date-parts":[[2022,10,12]]}},"container-title":["2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9945068\/9945069\/09945189.pdf?arnumber=9945189","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:53:11Z","timestamp":1670874791000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9945189\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,9]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/smc53654.2022.9945189","relation":{},"subject":[],"published":{"date-parts":[[2022,10,9]]}}}