{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T15:49:02Z","timestamp":1756309742359,"version":"3.37.3"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2017,7,5]],"date-time":"2017-07-05T00:00:00Z","timestamp":1499212800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1504602"],"award-info":[{"award-number":["U1504602"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002858","name":"China Postdoctoral Science Foundation","doi-asserted-by":"publisher","award":["2015M572141"],"award-info":[{"award-number":["2015M572141"]}],"id":[{"id":"10.13039\/501100002858","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2019,2]]},"DOI":"10.1007\/s00521-017-3081-x","type":"journal-article","created":{"date-parts":[[2017,7,5]],"date-time":"2017-07-05T00:57:04Z","timestamp":1499216224000},"page":"473-487","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Traffic identification method based on multiple probabilistic neural network model"],"prefix":"10.1007","volume":"31","author":[{"given":"Shi","family":"Dong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ruixuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,7,5]]},"reference":[{"key":"3081_CR1","doi-asserted-by":"crossref","unstructured":"Moore AW, Papagiannaki K (2005) Toward the accurate identification of network applications. In: Dovrolis C (eds) Passive and active network measurement. PAM 2005, Lecture notes in computer science, vol 3431. Springer, Berlin, pp 41\u201354","DOI":"10.1007\/978-3-540-31966-5_4"},{"issue":"1","key":"3081_CR2","doi-asserted-by":"publisher","first-page":"22","DOI":"10.4218\/etrij.05.0104.0040","volume":"27","author":"M-S Kim","year":"2005","unstructured":"Kim M-S, Won YJ, Hong JW-K (2005) Application-level traffic monitoring and an analysis on IP networks. ETRI J 27(1):22\u201342","journal-title":"ETRI J"},{"key":"3081_CR3","doi-asserted-by":"crossref","unstructured":"McGregor A, Hall M, Lorier P, Brunskill J (2004) Flow clustering using machine learning techniques. In: Barakat C, Pratt I (eds) Passive and active network measurement. PAM 2004, Lecture notes in computer science, vol 3015. Springer, Berlin, pp 205\u2013214","DOI":"10.1007\/978-3-540-24668-8_21"},{"key":"3081_CR4","doi-asserted-by":"crossref","unstructured":"Erman J, Arlitt M, Mahanti A (2006) Traffic classification using clustering algorithms. In: Proceedings of the 2006 SIGCOMM workshop on mining network data. ACM, pp 281\u2013286","DOI":"10.1145\/1162678.1162679"},{"key":"3081_CR5","doi-asserted-by":"crossref","unstructured":"Erman J, Mahanti A, Arlitt M (2006) Qrp05-4: internet traffic identification using machine learning. In: Global telecommunications conference. GLOBECOM\u201906. IEEE. IEEE, pp 1\u20136","DOI":"10.1109\/GLOCOM.2006.443"},{"key":"3081_CR6","doi-asserted-by":"crossref","unstructured":"Karagiannis T, Papagiannaki K, Faloutsos M (2005) Blinc: multilevel traffic classification in the dark. In: ACM SIGCOMM computer communication review, vol 35. ACM, Philadelphia, 21\u201326 Aug 2005, pp 229\u2013240","DOI":"10.1145\/1080091.1080119"},{"issue":"4","key":"3081_CR7","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1002\/nem.1865","volume":"24","author":"H Asai","year":"2014","unstructured":"Asai H, Fukuda K, Abry P, Borgnat P, Esaki H (2014) Network application profiling with traffic causality graphs. Int J Netw Manag 24(4):289\u2013303","journal-title":"Int J Netw Manag"},{"key":"3081_CR8","doi-asserted-by":"crossref","unstructured":"Li X, Qi F, Xu D, Qiu X-S (2011) An internet traffic classification method based on semi-supervised support vector machine. In: 2011 IEEE international conference on communications (ICC). IEEE, pp 1\u20135","DOI":"10.1109\/icc.2011.5962736"},{"key":"3081_CR9","doi-asserted-by":"crossref","unstructured":"Wang Y, Xiang Y, Zhang J, Yu S (2011) A novel semi-supervised approach for network traffic clustering. In: 2011 5th International conference on network and system security (NSS). IEEE, pp 169\u2013175","DOI":"10.1109\/ICNSS.2011.6059997"},{"issue":"2","key":"3081_CR10","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1109\/TNSM.2014.011714.130505","volume":"11","author":"L Grimaudo","year":"2014","unstructured":"Grimaudo L, Mellia M, Baralis E, Keralapura R (2014) Select: self-learning classifier for internet traffic. IEEE Trans Netw Serv Manag 11(2):144\u2013157","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"3081_CR11","doi-asserted-by":"crossref","unstructured":"Moore AW, Zuev D (2005) Internet traffic classification using Bayesian analysis techniques. In: ACM SIGMETRICS performance evaluation review, vol 33. ACM, Banff, 6\u201310 June 2005, pp 50\u201360","DOI":"10.1145\/1064212.1064220"},{"issue":"1","key":"3081_CR12","doi-asserted-by":"publisher","first-page":"223","DOI":"10.1109\/TNN.2006.883010","volume":"18","author":"T Auld","year":"2007","unstructured":"Auld T, Moore AW, Gull SF (2007) Bayesian neural networks for internet traffic classification. IEEE Trans Neural Netw 18(1):223\u2013239","journal-title":"IEEE Trans Neural Netw"},{"issue":"6","key":"3081_CR13","doi-asserted-by":"publisher","first-page":"790","DOI":"10.1016\/j.comnet.2008.11.016","volume":"53","author":"W Li","year":"2009","unstructured":"Li W, Canini M, Moore AW, Bolla R (2009) Efficient application identification and the temporal and spatial stability of classification schema. Comput Netw 53(6):790\u2013809","journal-title":"Comput Netw"},{"key":"3081_CR14","doi-asserted-by":"publisher","first-page":"752","DOI":"10.1016\/j.comnet.2015.09.011","volume":"91","author":"A Rizzi","year":"2015","unstructured":"Rizzi A, Iacovazzi A, Baiocchi A, Colabrese S (2015) A low complexity real-time internet traffic flows neuro-fuzzy classifier. Comput Netw 91:752\u2013771","journal-title":"Comput Netw"},{"key":"3081_CR15","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.comnet.2015.08.021","volume":"91","author":"DM Divakaran","year":"2015","unstructured":"Divakaran DM, Su L, Liau YS, Thing VL (2015) Slic: self-learning intelligent classifier for network traffic. Comput Netw 91:283\u2013297","journal-title":"Comput Netw"},{"issue":"11","key":"3081_CR16","first-page":"1994","volume":"98","author":"Y Sung-Ho","year":"2015","unstructured":"Sung-Ho Y, Jun-Sang P, Ji-Hyeok C, Youngjoon W, Myung-Sup K (2015) Http traffic classification based on hierarchical signature structure. IEICE Trans Inf Syst 98(11):1994\u20131997","journal-title":"IEICE Trans Inf Syst"},{"issue":"10","key":"3081_CR17","doi-asserted-by":"publisher","first-page":"1639","DOI":"10.1016\/j.comcom.2005.07.015","volume":"29","author":"M-S Kim","year":"2006","unstructured":"Kim M-S, Won YJ, Hong JW (2006) Characteristic analysis of internet traffic from the perspective of flows. Comput Commun 29(10):1639\u20131652","journal-title":"Comput Commun"},{"key":"3081_CR18","volume-title":"Neural networks: a classroom approach","author":"S Kumar","year":"2004","unstructured":"Kumar S (2004) Neural networks: a classroom approach. Tata McGraw-Hill Education, New York City"},{"key":"3081_CR19","volume-title":"Nonparametric functional estimation","author":"B Prakasa Rao","year":"1983","unstructured":"Prakasa Rao B (1983) Nonparametric functional estimation. Academic Press, New York"},{"key":"3081_CR20","volume-title":"Discriminators for use in flow-based classification","author":"A Moore","year":"2005","unstructured":"Moore A, Zuev D, Crogan M (2005) Discriminators for use in flow-based classification. Queen Mary and Westfield College, Department of Computer Science, London"},{"key":"3081_CR21","unstructured":"Levandoski J, Sommer E, Strait M L7-filter, application layer packet classifier for linux [Online]. Available: \n                    http:\/\/l7-filter.sourceforge.net\/\n                    \n                  . Accessed 7 Jan 2009"},{"key":"3081_CR22","volume-title":"Data mining: practical machine learning tools and techniques","author":"IH Witten","year":"2005","unstructured":"Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques. Morgan Kaufmann, Los Altos"},{"key":"3081_CR23","unstructured":"Hecht-Nielsen R (1987) Kolmogorovs mapping neural network existence theorem. In: Proceedings of the international conference on Neural Networks, vol 3. IEEE Press, New York, pp 11\u201314"},{"key":"3081_CR24","first-page":"20","volume":"55","author":"A-S Wafa\u2019S","year":"2009","unstructured":"Wafa\u2019S A-S, Naoum R (2009) Development of genetic-based machine learning for network intrusion detection. World Acad Sci Eng Technol 55:20\u201324","journal-title":"World Acad Sci Eng Technol"},{"key":"3081_CR25","doi-asserted-by":"crossref","unstructured":"Roughan M, Sen S, Spatscheck O, Duffield N (2004) Class-of-service mapping for qos: a statistical signature-based approach to IP traffic classification. In: Proceedings of the 4th ACM SIGCOMM conference on internet measurement. ACM, pp 135\u2013148","DOI":"10.1145\/1028788.1028805"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3081-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-017-3081-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-017-3081-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,3,2]],"date-time":"2019-03-02T01:10:00Z","timestamp":1551489000000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-017-3081-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,7,5]]},"references-count":25,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,2]]}},"alternative-id":["3081"],"URL":"https:\/\/doi.org\/10.1007\/s00521-017-3081-x","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2017,7,5]]},"assertion":[{"value":"19 May 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 June 2017","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 July 2017","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The authors of the paper immediately below certify that they have no affiliations with or involvement in any organization or entity with any financial interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}