{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T10:54:01Z","timestamp":1761216841613,"version":"build-2065373602"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819712762"},{"type":"electronic","value":"9789819712779"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-1277-9_23","type":"book-chapter","created":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T02:01:41Z","timestamp":1712023301000},"page":"304-318","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Construction of\u00a0IoT Malicious Traffic Dataset and\u00a0Its Applications"],"prefix":"10.1007","author":[{"given":"Yiping","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yiyang","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jie","family":"Yin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yichen","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenwei","family":"Xie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guangjun","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lanping","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,3]]},"reference":[{"key":"23_CR1","doi-asserted-by":"publisher","unstructured":"Garcia, S., Parmisano, A., Erquiaga, M.J.: IoT-23: A labeled dataset with malicious and benign IoT network traffic (Version 1.0.0) [Data set], Zenodo (2020). https:\/\/doi.org\/10.5281\/zenodo.4743746","DOI":"10.5281\/zenodo.4743746"},{"key":"23_CR2","doi-asserted-by":"crossref","unstructured":"N. Moustafa, N.: A new distributed architecture for evaluating AI-based security systems at the edge: network TON-IoT datasets. Sustain. Cities Soc. 72, 102994 (2021)","DOI":"10.1016\/j.scs.2021.102994"},{"key":"23_CR3","doi-asserted-by":"crossref","unstructured":"Moore, A.: Internet traffic classification using bayesian analysis techniques. In: ACM Sigmetrics Performance Evaluation Review (2005)","DOI":"10.1145\/1064212.1064220"},{"key":"23_CR4","doi-asserted-by":"crossref","unstructured":"Gislason, p., Benediktsson, J., Sveinsson, J.: Random forests for land cover classification. Pattern Recognition Lett. 27(4), 294\u2013300 (2006)","DOI":"10.1016\/j.patrec.2005.08.011"},{"key":"23_CR5","doi-asserted-by":"crossref","unstructured":"Nelder, J., Wedderburn, R.: Generalized linear models. J. Roy. Stat. Soc. 135(3), 370\u2013384 (1972)","DOI":"10.2307\/2344614"},{"key":"23_CR6","doi-asserted-by":"crossref","unstructured":"Friedman, J.: Greedy function approximation: a gradient boosting machine. Annal. Stat. 29(5), 1189\u20131232 (2001)","DOI":"10.1214\/aos\/1013203451"},{"key":"23_CR7","doi-asserted-by":"crossref","unstructured":"Chen, T., Guestrin, C.: XGBoost: a scalable tree boosting system. In: 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2016)","DOI":"10.1145\/2939672.2939785"},{"key":"23_CR8","doi-asserted-by":"crossref","unstructured":"Bishop, C., et al.: Neural Network for Pattern Recognition (1995)","DOI":"10.1093\/oso\/9780198538493.001.0001"},{"key":"23_CR9","doi-asserted-by":"crossref","unstructured":"Patcha, A., Park, J.: An overview of anomaly detection techniques: existing solutions and latest technological trends. Comput. Netw. 51(12), 3448\u20133470 (2007)","DOI":"10.1016\/j.comnet.2007.02.001"},{"key":"23_CR10","doi-asserted-by":"crossref","unstructured":"Lawrence, S., Giles, C., Tsoi, A., et al.: Face Recognition: a convolutional neural network approach. IEEE Trans. Neural Netw. 8(1), 98\u2013113 (1997)","DOI":"10.1109\/72.554195"},{"key":"23_CR11","doi-asserted-by":"crossref","unstructured":"Williams, R., Zipser, D.: A learning algorithm for continually running fully recurrent neural networks. Neural Comput. 1(2), 270\u2013280 (1998)","DOI":"10.1162\/neco.1989.1.2.270"},{"key":"23_CR12","unstructured":"Wang, W.: Research on network traffic classification and anomaly detection based on deep learning. University of Science and Technology of China (2018)"},{"key":"23_CR13","doi-asserted-by":"crossref","unstructured":"Vinayakumar, R., Soman, K., Poornachandran, P.: Applying convolutional neural network for network intrusion detection, In: International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 1222\u20131228 (2017)","DOI":"10.1109\/ICACCI.2017.8126009"},{"key":"23_CR14","doi-asserted-by":"crossref","unstructured":"Thapa, K.K., Duraipandian, N.: Malicious traffic classification using long short-term memory (LSTM) model. Wirel. Pers. Commun. 119(3), 2707\u20132724 (2021)","DOI":"10.1007\/s11277-021-08359-6"},{"key":"23_CR15","doi-asserted-by":"crossref","unstructured":"Lu, X., Liu, p., and Lin, J.: Network traffic anomaly detection based on information gain and deep learning. In: Proceedings of the 2019 3rd International Conference on Information System and Data Mining, pp. 11\u201315 (2019)","DOI":"10.1145\/3325917.3325946"},{"key":"23_CR16","doi-asserted-by":"crossref","unstructured":"Liu, X., Liu, J.: Malicious traffic detection combined deep neural network with hierarchical attention mechanism. Sci. Rep. 11(1), 1\u201315 (2021)","DOI":"10.1038\/s41598-021-91805-z"},{"key":"23_CR17","doi-asserted-by":"crossref","unstructured":"Su, T., Sun, H., Zhu, J., et al.: BAT: deep learning methods on network intrusion detection using NSL-KDD dataset. IEEE Access 8, 29575\u201329585 (2020)","DOI":"10.1109\/ACCESS.2020.2972627"},{"key":"23_CR18","unstructured":"Cook, D.: Practical machine learning with H2O (2017)"},{"key":"23_CR19","unstructured":"Fan, Y.: Overview of Cross Validation Methods in Model Selection. Shanxi University (2013)"},{"key":"23_CR20","doi-asserted-by":"crossref","unstructured":"Blum, A., Kalai, A., Langford, J.: Beating the hold-out: bounds for K-fold and progressive cross-validation. In: Conference on Learning Theory (1999)","DOI":"10.1145\/307400.307439"},{"key":"23_CR21","doi-asserted-by":"crossref","unstructured":"Borkowf, C.: Computing the nonnull asymptotic variance and the asymptotic relative efficiency of Spearman\u2019s rank correlation. Comput. Stat. Data Anal. 39(3), 271\u2013286 (2002)","DOI":"10.1016\/S0167-9473(01)00081-0"}],"container-title":["Communications in Computer and Information Science","Artificial Intelligence and Machine Learning"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-1277-9_23","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T10:43:39Z","timestamp":1761216219000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-1277-9_23"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819712762","9789819712779"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-1277-9_23","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IAIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Artificial Intelligence Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iaic2023a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iaicconf.com\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}