{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T17:28:00Z","timestamp":1782926880407,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":32,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,12,9]],"date-time":"2019-12-09T00:00:00Z","timestamp":1575849600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"TELUS"},{"DOI":"10.13039\/501100002790","name":"Natural Sciences and Engineering Research Council of Canada","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002790","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,12,9]]},"DOI":"10.1145\/3359992.3366767","type":"proceedings-article","created":{"date-parts":[[2019,11,19]],"date-time":"2019-11-19T13:46:52Z","timestamp":1574171212000},"page":"29-34","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Explaining Class-of-Service Oriented Network Traffic Classification with Superfeatures"],"prefix":"10.1145","author":[{"given":"Sayantan","family":"Chowdhury","sequence":"first","affiliation":[{"name":"Dept. of Electrical and Computer Engineering, University of Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ben","family":"Liang","sequence":"additional","affiliation":[{"name":"Dept. of Electrical and Computer Engineering, University of Toronto, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Tizghadam","sequence":"additional","affiliation":[{"name":"Technology Strategy and Business Transformation, TELUS Communications, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,12,9]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2016. ISCX TOR-nonTOR. Available online: https:\/\/www.unb.ca\/cic\/datasets\/tor.html.  2016. ISCX TOR-nonTOR. Available online: https:\/\/www.unb.ca\/cic\/datasets\/tor.html."},{"key":"e_1_3_2_1_2_1","unstructured":"2016. ISCX VPN-nonVPN. Available online: https:\/\/www.unb.ca\/cic\/datasets\/vpn.html.  2016. ISCX VPN-nonVPN. Available online: https:\/\/www.unb.ca\/cic\/datasets\/vpn.html."},{"key":"e_1_3_2_1_3_1","volume-title":"Mobile Encrypted Traffic Classification Using Deep Learning. In the Network Traffic Measurement and Analysis Conference (TMA). 1--8.","author":"Aceto G.","unstructured":"G. Aceto , D. Ciuonzo , A. Montieri , and A. Pescap\u00e9 . 2018 . Mobile Encrypted Traffic Classification Using Deep Learning. In the Network Traffic Measurement and Analysis Conference (TMA). 1--8. G. Aceto, D. Ciuonzo, A. Montieri, and A. Pescap\u00e9. 2018. Mobile Encrypted Traffic Classification Using Deep Learning. In the Network Traffic Measurement and Analysis Conference (TMA). 1--8."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNN.2006.883010"},{"key":"e_1_3_2_1_5_1","first-page":"3","article-title":"Identification and Prediction of Internet Traffic Using Artificial Neural Networks","volume":"2","author":"Chabaa S.","year":"2010","unstructured":"S. Chabaa , A. Zeroual , and J. Antari . 2010 . Identification and Prediction of Internet Traffic Using Artificial Neural Networks . J. Intell. Learn. Syst. Appl. 2 , 3 (July 2010), 147--155. S. Chabaa, A. Zeroual, and J. Antari. 2010. Identification and Prediction of Internet Traffic Using Artificial Neural Networks. J. Intell. Learn. Syst. Appl. 2, 3 (July 2010), 147--155.","journal-title":"J. Intell. Learn. Syst. Appl."},{"key":"e_1_3_2_1_6_1","unstructured":"F. Doshi-Velez and B. Kim. 2017. Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608 (2017).  F. Doshi-Velez and B. Kim. 2017. Towards a rigorous science of interpretable machine learning. arXiv preprint arXiv:1702.08608 (2017)."},{"key":"e_1_3_2_1_7_1","volume-title":"the 2nd Int. Conf. on Inf. Sys. Security and Privacy. 407--414","author":"Draper-Gil G.","unstructured":"G. Draper-Gil , A. Lashkari , M. Mamun , and A. Ghorbani . 2016. Characterization of Encrypted and VPN Traffic using Time-related Features . In the 2nd Int. Conf. on Inf. Sys. Security and Privacy. 407--414 . G. Draper-Gil, A. Lashkari, M. Mamun, and A. Ghorbani. 2016. Characterization of Encrypted and VPN Traffic using Time-related Features. In the 2nd Int. Conf. on Inf. Sys. Security and Privacy. 407--414."},{"key":"e_1_3_2_1_8_1","volume-title":"Identifying and Discriminating Between Web and Peer-to-peer Traffic in the Network Core. In the 16th Int. Conf. on World Wide Web. 883--892","author":"Erman J.","unstructured":"J. Erman , A. Mahanti , M. Arlitt , and C. Williamson . 2007 . Identifying and Discriminating Between Web and Peer-to-peer Traffic in the Network Core. In the 16th Int. Conf. on World Wide Web. 883--892 . J. Erman, A. Mahanti, M. Arlitt, and C. Williamson. 2007. Identifying and Discriminating Between Web and Peer-to-peer Traffic in the Network Core. In the 16th Int. Conf. on World Wide Web. 883--892."},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2009.05.003"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2013.100613.00161"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2014.011714.130505"},{"key":"e_1_3_2_1_12_1","unstructured":"D. Hinkle W. Wiersma and S. Jurs. 2003. Applied statistics for the behavioral sciences (5th ed.).  D. Hinkle W. Wiersma and S. Jurs. 2003. Applied statistics for the behavioral sciences (5th ed.)."},{"key":"e_1_3_2_1_13_1","volume-title":"the 3rd Int. Conf. on Inf. Sys. Security and Privacy.","author":"Lashkari A.","unstructured":"A. Lashkari , G. Draper-Gil , M. Mamun , and A. Ghorbani . 2017. Characterization of Tor Traffic using Time based Features . In the 3rd Int. Conf. on Inf. Sys. Security and Privacy. A. Lashkari, G. Draper-Gil, M. Mamun, and A. Ghorbani. 2017. Characterization of Tor Traffic using Time based Features. In the 3rd Int. Conf. on Inf. Sys. Security and Privacy."},{"key":"e_1_3_2_1_14_1","volume-title":"FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. In the IEEE INFOCOM Conference on Computer Communications. 1171--1179","author":"Liu C.","unstructured":"C. Liu , L. He , G. Xiong , Z. Cao , and Z. Li . 2019 . FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. In the IEEE INFOCOM Conference on Computer Communications. 1171--1179 . C. Liu, L. He, G. Xiong, Z. Cao, and Z. Li. 2019. FS-Net: A Flow Sequence Network For Encrypted Traffic Classification. In the IEEE INFOCOM Conference on Computer Communications. 1171--1179."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2747560"},{"key":"e_1_3_2_1_16_1","unstructured":"S. Lundberg and S. Lee. 2017. A Unified Approach to Interpreting Model Predictions. In the 30th Advances in Neural Information Processing Systems (NIPS). 4765--4774.  S. Lundberg and S. Lee. 2017. A Unified Approach to Interpreting Model Predictions. In the 30th Advances in Neural Information Processing Systems (NIPS). 4765--4774."},{"key":"e_1_3_2_1_17_1","unstructured":"C. Molnar. 2019. Interpretable Machine Learning. https:\/\/christophm.github.io\/interpretable-ml-book\/.  C. Molnar. 2019. Interpretable Machine Learning. https:\/\/christophm.github.io\/interpretable-ml-book\/."},{"key":"e_1_3_2_1_18_1","volume-title":"Internet Traffic Classification Using Bayesian Analysis Techniques. In the ACM SIGMETRICS Int. Conf. on Measurement and Modeling of Computer Systems. 50--60","author":"Moore A.","year":"2005","unstructured":"A. Moore and D. Zuev . 2005 . Internet Traffic Classification Using Bayesian Analysis Techniques. In the ACM SIGMETRICS Int. Conf. on Measurement and Modeling of Computer Systems. 50--60 . A. Moore and D.Zuev. 2005. Internet Traffic Classification Using Bayesian Analysis Techniques. In the ACM SIGMETRICS Int. Conf. on Measurement and Modeling of Computer Systems. 50--60."},{"key":"e_1_3_2_1_19_1","unstructured":"A. Moore D. Zuev and M. Crogan. 2005. Discriminators for use in flow-based classification. Technical Report.  A. Moore D. Zuev and M. Crogan. 2005. Discriminators for use in flow-based classification. Technical Report."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2008.080406"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2012.2187305"},{"key":"e_1_3_2_1_22_1","first-page":"2825","article-title":"Scikit-learn: Machine Learning in Python","volume":"12","author":"F. Pedregosa","year":"2011","unstructured":"F. Pedregosa et. al. 2011 . Scikit-learn: Machine Learning in Python . Journal of Machine Learning Research 12 (2011), 2825 -- 2830 . F. Pedregosa et. al. 2011. Scikit-learn: Machine Learning in Python. Journal of Machine Learning Research 12 (2011), 2825--2830.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_23_1","volume-title":"the 22nd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining. 1135--1144","author":"Ribeiro M.","unstructured":"M. Ribeiro , S. Singh , and C. Guestrin . 2016. \"Why Should I Trust You?\": Explaining the Predictions of Any Classifier . In the 22nd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining. 1135--1144 . M. Ribeiro, S. Singh, and C. Guestrin. 2016. \"Why Should I Trust You?\": Explaining the Predictions of Any Classifier. In the 22nd ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining. 1135--1144."},{"key":"e_1_3_2_1_24_1","volume-title":"the 4th ACM SIGCOMM Conf. on Internet Measurement. 135--148","author":"Roughan M.","unstructured":"M. Roughan , S. Sen , O. Spatscheck , and N. Duffield . 2004. Class-of-service Mapping for QoS: A Statistical Signature-based Approach to IP Traffic Classification . In the 4th ACM SIGCOMM Conf. on Internet Measurement. 135--148 . M. Roughan, S. Sen, O. Spatscheck, and N. Duffield. 2004. Class-of-service Mapping for QoS: A Statistical Signature-based Approach to IP Traffic Classification. In the 4th ACM SIGCOMM Conf. on Internet Measurement. 135--148."},{"key":"e_1_3_2_1_25_1","volume-title":"A value for n-person games. Contributions to the Theory of Games (AM-28) 2","author":"Shapley L.","year":"1953","unstructured":"L. Shapley . 1953. A value for n-person games. Contributions to the Theory of Games (AM-28) 2 ( 1953 ), 307--318. L. Shapley. 1953. A value for n-person games. Contributions to the Theory of Games (AM-28) 2 (1953), 307--318."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-013-0679-x"},{"key":"e_1_3_2_1_27_1","volume-title":"the IEEE International Conference on Services Computing (SCC). 760--765","author":"Wang P.","unstructured":"P. Wang , S. Lin , and M. Luo . 2016. A Framework for QoS-aware Traffic Classification Using Semi-supervised Machine Learning in SDNs . In the IEEE International Conference on Services Computing (SCC). 760--765 . P. Wang, S. Lin, and M. Luo. 2016. A Framework for QoS-aware Traffic Classification Using Semi-supervised Machine Learning in SDNs. In the IEEE International Conference on Services Computing (SCC). 760--765."},{"key":"e_1_3_2_1_28_1","volume-title":"the IEEE Int. Conf. on Intelligence and Security Informatics (ISI). 43--48","author":"Wang W.","unstructured":"W. Wang , M. Zhu , J. Wang , X. Zeng , and Z. Yang . 2017. End-to-end encrypted traffic classification with one-dimensional convolution neural networks . In the IEEE Int. Conf. on Intelligence and Security Informatics (ISI). 43--48 . W. Wang, M. Zhu, J. Wang, X. Zeng, and Z. Yang. 2017. End-to-end encrypted traffic classification with one-dimensional convolution neural networks. In the IEEE Int. Conf. on Intelligence and Security Informatics (ISI). 43--48."},{"key":"e_1_3_2_1_29_1","first-page":"11","article-title":"Internet Traffic Classification Using Constrained Clustering","volume":"25","author":"Wang Y.","year":"2014","unstructured":"Y. Wang , Y. Xiang , J. Zhang , W. Zhou , G. Wei , and L. T. Yang . 2014 . Internet Traffic Classification Using Constrained Clustering . IEEE Trans. on Parallel and Distributed Sys. 25 , 11 (Nov 2014), 2932--2943. Y. Wang, Y. Xiang, J. Zhang, W. Zhou, G. Wei, and L. T. Yang. 2014. Internet Traffic Classification Using Constrained Clustering. IEEE Trans. on Parallel and Distributed Sys. 25, 11 (Nov 2014), 2932--2943.","journal-title":"IEEE Trans. on Parallel and Distributed Sys."},{"key":"e_1_3_2_1_30_1","volume-title":"the 30th IEEE Conference on Local Computer Networks (LCN). 250--257","author":"Zander S.","unstructured":"S. Zander , T. Nguyen , and G. Armitage . 2005. Automated traffic classification and application identification using machine learning . In the 30th IEEE Conference on Local Computer Networks (LCN). 250--257 . S. Zander, T. Nguyen, and G. Armitage. 2005. Automated traffic classification and application identification using machine learning. In the 30th IEEE Conference on Local Computer Networks (LCN). 250--257."},{"key":"e_1_3_2_1_31_1","first-page":"1","article-title":"Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions","volume":"8","author":"Zhang J.","year":"2013","unstructured":"J. Zhang , C. Chen , Y. Xiang , W. Zhou , and Y. Xiang . 2013 . Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions . IEEE Trans. on Inf. Forensics and Security 8 , 1 (Jan 2013), 5--15. J. Zhang, C. Chen, Y. Xiang, W. Zhou, and Y. Xiang. 2013. Internet Traffic Classification by Aggregating Correlated Naive Bayes Predictions. IEEE Trans. on Inf. Forensics and Security 8, 1 (Jan 2013), 5--15.","journal-title":"IEEE Trans. on Inf. Forensics and Security"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2014.2320577"}],"event":{"name":"CoNEXT '19: The 15th International Conference on emerging Networking EXperiments and Technologies","location":"Orlando FL USA","acronym":"CoNEXT '19","sponsor":["SIGCOMM ACM Special Interest Group on Data Communication"]},"container-title":["Proceedings of the 3rd ACM CoNEXT Workshop on Big DAta, Machine Learning and Artificial Intelligence for Data Communication Networks"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3359992.3366767","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3359992.3366767","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:13:28Z","timestamp":1750202008000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3359992.3366767"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,12,9]]},"references-count":32,"alternative-id":["10.1145\/3359992.3366767","10.1145\/3359992"],"URL":"https:\/\/doi.org\/10.1145\/3359992.3366767","relation":{},"subject":[],"published":{"date-parts":[[2019,12,9]]},"assertion":[{"value":"2019-12-09","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}