{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:08:02Z","timestamp":1755907682140,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"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":[[2024,3]]},"DOI":"10.1145\/3672919.3672920","type":"proceedings-article","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T12:39:43Z","timestamp":1721824783000},"page":"1-6","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["CTCRNN: A Hybrid CNN-BiLSTM Based Classification Method for Industrial IoT Encrypted Traffic Based on Spatiotemporal Features"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0856-560X","authenticated-orcid":false,"given":"Huiqi","family":"Zhao","sequence":"first","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4665-6173","authenticated-orcid":false,"given":"Shunfa","family":"Sun","sequence":"additional","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7099-0968","authenticated-orcid":false,"given":"Rui","family":"Wang","sequence":"additional","affiliation":[{"name":"State Grid Shandong Electric Power Research Institute, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8756-2887","authenticated-orcid":false,"given":"Fang","family":"Fan","sequence":"additional","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-8083-6379","authenticated-orcid":false,"given":"Lu","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Intelligent Equipment, Shandong University of Science and Technology, China"}]}],"member":"320","published-online":{"date-parts":[[2024,7,24]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Zaki F and Anuar N B","author":"Tahaei H","year":"2020","unstructured":"Tahaei H, Afifi F, Asemi A, Zaki F and Anuar N B 2020. The rise of traffic classification in IoT networks: A survey. J. Netw. Comput. Appl. 154 102538."},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-021-08435-x"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3121517"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1007\/s42979-021-00815-1"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2022.3193748"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2022.02.006"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2022.04.018"},{"key":"e_1_3_2_1_8_1","first-page":"76","volume":"57","author":"Rezaei S","year":"2018","unstructured":"Rezaei S and Liu X 2018. Deep Learning for Encrypted Traffic Classification: An Overview. J. IEEE. Commun. Mag. 57 76-81.","journal-title":"Deep Learning for Encrypted Traffic Classification: An Overview. J. IEEE. Commun. Mag."},{"key":"e_1_3_2_1_9_1","first-page":"43","article-title":"End-to-end encrypted traffic classification with one-dimensional convolution neural networks. In: 2017 IEEE International Conference on Intelligence and Security Informatics (ISI)","author":"Wang W","year":"2017","unstructured":"Wang W, Zhu M, Wang J, Zeng X and Yang Z 2017. End-to-end encrypted traffic classification with one-dimensional convolution neural networks. In: 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). Shenzhen. China 43-48.","journal-title":"Shenzhen. China"},{"key":"e_1_3_2_1_10_1","volume-title":"Mamun M S and Ghorbani A A","author":"Draper-Gil G","year":"2016","unstructured":"Draper-Gil G, Habibi Lashkari A, Mamun M S and Ghorbani A A 2016. Characterization of Encrypted and VPN Traffic using Time-related Features. In: ICISSP 2016 - Proceedings of the 2nd International Conference on Information Systems Security and Privacy. Rome. Italy. 407-414."},{"key":"e_1_3_2_1_11_1","first-page":"1","volume":"5518460","author":"Hu X","year":"2021","unstructured":"Hu X, Gu C and Wei F 2021. CLD-Net: A Network Combining CNN and LSTM for Internet Encrypted Traffic Classification. J. Secur. Commun. Networks. 5518460 1-15.","journal-title":"J. Secur. Commun. Networks."},{"key":"e_1_3_2_1_12_1","volume-title":"Xu X and Gao H","author":"Lin K","year":"2021","unstructured":"Lin K, Xu X and Gao H 2021. TSCRNN: A novel classification scheme of encrypted traffic based on flow spatiotemporal features for efficient management of IIoT. J. Comput. Networks. 190 107974."},{"key":"e_1_3_2_1_13_1","volume-title":"Lee J and Kweon I 2018","author":"Woo S","year":"1807","unstructured":"Woo S, Park J, Lee J and Kweon I 2018. CBAM: Convolutional Block Attention Module. J. ArXiv. abs\/1807.06521."},{"key":"e_1_3_2_1_14_1","volume-title":"Unterthiner T and Hochreiter S","author":"Clevert D","year":"2015","unstructured":"Clevert D, Unterthiner T and Hochreiter S 2015. Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs). In; 4th International Conference on Learning Representations. ICLR 2016 - Conference Track Proceedings. San Juan. Puerto rico."},{"key":"e_1_3_2_1_15_1","volume-title":"Sun F and Lee H","author":"Shih S","year":"2018","unstructured":"Shih S, Sun F and Lee H 2018. Temporal pattern attention for multivariate time series forecasting. J. Mach. Learn. 108 1421 \u2013 41."}],"event":{"name":"CSAIDE 2024: 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy","acronym":"CSAIDE 2024","location":"Nanjing China"},"container-title":["Proceedings of the 2024 3rd International Conference on Cyber Security, Artificial Intelligence and Digital Economy"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672919.3672920","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3672919.3672920","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T16:37:06Z","timestamp":1755880626000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3672919.3672920"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3]]},"references-count":15,"alternative-id":["10.1145\/3672919.3672920","10.1145\/3672919"],"URL":"https:\/\/doi.org\/10.1145\/3672919.3672920","relation":{},"subject":[],"published":{"date-parts":[[2024,3]]},"assertion":[{"value":"2024-07-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}