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Journal of Machine Learning Research 18 , 17 (2017), 1 -- 5 . http:\/\/jmlr.org\/papers\/v18\/16-365.html Guillaume Lema\u00eetre, Fernando Nogueira, and Christos K. Aridas. 2017. Imbalanced-learn: A Python Toolbox to Tackle the Curse of Imbalanced Datasets in Machine Learning. Journal of Machine Learning Research 18, 17 (2017), 1--5. http:\/\/jmlr.org\/papers\/v18\/16-365.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3236386.3241340"},{"key":"e_1_3_2_2_41_1","first-page":"I","article-title":"A Unified Approach to Interpreting Model Predictions","volume":"30","author":"Lundberg S. M","year":"2017","unstructured":"S. M Lundberg and S. Lee . 2017 . A Unified Approach to Interpreting Model Predictions . In Advances in Neural Information Processing Systems 30 , I . Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.). Curran Associates, Inc., 4765--4774. http:\/\/papers.nips.cc\/paper\/7062-a- unified-approach-to-interpreting-model-predictions.pdf S. M Lundberg and S. Lee. 2017. A Unified Approach to Interpreting Model Predictions. In Advances in Neural Information Processing Systems 30, I. Guyon, U. V. Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, and R. Garnett (Eds.). Curran Associates, Inc., 4765--4774. http:\/\/papers.nips.cc\/paper\/7062-a- unified-approach-to-interpreting-model-predictions.pdf","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_2_42_1","volume-title":"Proceedings of the Conference of the ACM Special Interest Group on Data Communication (SIGCOMM '17)","author":"Mao H.","unstructured":"H. Mao , R. Netravali , and M. Alizadeh . 2017. Neural Adaptive Video Streaming with Pensieve . In Proceedings of the Conference of the ACM Special Interest Group on Data Communication (SIGCOMM '17) . Association for Computing Machinery, New York, NY, USA, 197--210. https:\/\/doi.org\/10.1145\/3098822.3098843 Code available at GitHub repository at https:\/\/github.com\/hongzimao\/pensieve. 10.1145\/3098822.3098843 H. Mao, R. Netravali, and M. Alizadeh. 2017. Neural Adaptive Video Streaming with Pensieve. In Proceedings of the Conference of the ACM Special Interest Group on Data Communication (SIGCOMM '17). Association for Computing Machinery, New York, NY, USA, 197--210. https:\/\/doi.org\/10.1145\/3098822.3098843 Code available at GitHub repository at https:\/\/github.com\/hongzimao\/pensieve."},{"key":"e_1_3_2_2_43_1","volume-title":"Proceedings of the Annual Conference of the ACM SIGCOMM (SIGCOMM '20)","author":"Meng Z.","unstructured":"Z. Meng , M. Wang , J. Bai , M. Xu , H. Mao , and H. Hu . 2020. Interpreting Deep Learning-Based Networking Systems . In Proceedings of the Annual Conference of the ACM SIGCOMM (SIGCOMM '20) . Association for Computing Machinery, New York, NY, USA, 154--171. https:\/\/doi.org\/10.1145\/3387514.3405859 10.1145\/3387514.3405859 Z. Meng, M. Wang, J. Bai, M. Xu, H. Mao, and H. Hu. 2020. Interpreting Deep Learning-Based Networking Systems. In Proceedings of the Annual Conference of the ACM SIGCOMM (SIGCOMM '20). Association for Computing Machinery, New York, NY, USA, 154--171. https:\/\/doi.org\/10.1145\/3387514.3405859"},{"key":"e_1_3_2_2_44_1","volume-title":"Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection. In Network and Distributed System Security Symposium 2018 (NDSS?18)","author":"Mirsky Y.","year":"1802","unstructured":"Y. Mirsky , T. Doitshman , Y. Elovici , and A. Shabtai . 2018 . Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection. In Network and Distributed System Security Symposium 2018 (NDSS?18) . https:\/\/doi.org\/10.48550\/ARXIV. 1802 . 09089 10.48550\/ARXIV.1802 Y. Mirsky, T. Doitshman, Y. Elovici, and A. Shabtai. 2018. Kitsune: An Ensemble of Autoencoders for Online Network Intrusion Detection. In Network and Distributed System Security Symposium 2018 (NDSS?18). https:\/\/doi.org\/10.48550\/ARXIV.1802. 09089"},{"key":"e_1_3_2_2_45_1","unstructured":"C. Molnar G. K\u00f6nig J. Herbinger T. Freiesleben S. Dandl C. A. Scholbeck G. Casalicchio M. Grosse-Wentrup and B. Bischl. 2020. Pitfalls to Avoid when Interpreting Machine Learning Models. arXiv preprint arXiv:2007.04131 (2020). arXiv:stat.ML\/2007.04131  C. Molnar G. K\u00f6nig J. Herbinger T. Freiesleben S. Dandl C. A. Scholbeck G. Casalicchio M. Grosse-Wentrup and B. Bischl. 2020. Pitfalls to Avoid when Interpreting Machine Learning Models. arXiv preprint arXiv:2007.04131 (2020). arXiv:stat.ML\/2007.04131"},{"key":"e_1_3_2_2_46_1","volume-title":"Implications of Artificial Intelligence for Cybersecurity: Proceedings of a Workshop. The National Academies Press","author":"National Academies of Sciences Engineering and Medicine.","year":"2019","unstructured":"National Academies of Sciences Engineering and Medicine. 2019 . Implications of Artificial Intelligence for Cybersecurity: Proceedings of a Workshop. The National Academies Press , Washington, DC. https:\/\/doi.org\/10.17226\/25488 10.17226\/25488 National Academies of Sciences Engineering and Medicine. 2019. Implications of Artificial Intelligence for Cybersecurity: Proceedings of a Workshop. The National Academies Press, Washington, DC. https:\/\/doi.org\/10.17226\/25488"},{"key":"#cr-split#-e_1_3_2_2_47_1.1","unstructured":"B. A. Nosek G. Alter G. C. Banks etal 2015. Promoting an open research culture. Science 348 6242 (2015) 1422--1425. https:\/\/doi.org\/10.1126\/science.aab2374 arXiv:https:\/\/www.science.org\/doi\/pdf\/10.1126\/science.aab2374 10.1126\/science.aab2374"},{"key":"#cr-split#-e_1_3_2_2_47_1.2","doi-asserted-by":"crossref","unstructured":"B. A. Nosek G. Alter G. C. Banks et al. 2015. Promoting an open research culture. Science 348 6242 (2015) 1422--1425. https:\/\/doi.org\/10.1126\/science.aab2374 arXiv:https:\/\/www.science.org\/doi\/pdf\/10.1126\/science.aab2374","DOI":"10.1126\/science.aab2374"},{"key":"e_1_3_2_2_48_1","first-page":"16","volume-title":"Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations. Association for Computational Linguistics","author":"Ribeiro M.","year":"1865","unstructured":"M. Ribeiro , S. Singh , and C. Guestrin . 2016. \"\"Why Should I Trust You?\": Explaining the Predictions of Any Classifier . In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations. Association for Computational Linguistics , San Diego, California, 97--101. https: \/\/doi.org\/10. 1865 3\/v1\/N 16 - 3020 10.18653\/v1 M. Ribeiro, S. Singh, and C. Guestrin. 2016. \"\"Why Should I Trust You?\": Explaining the Predictions of Any Classifier. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations. Association for Computational Linguistics, San Diego, California, 97--101. https: \/\/doi.org\/10.18653\/v1\/N16-3020"},{"key":"e_1_3_2_2_49_1","volume-title":"Proceedings of the 4th ACM Multimedia Systems Conference. 114--118","author":"Riiser H.","unstructured":"H. Riiser , P. Vigmostad , C. Griwodz , and P. Halvorsen . 2013. Commute path bandwidth traces from 3G networks: analysis and applications . In Proceedings of the 4th ACM Multimedia Systems Conference. 114--118 . H. Riiser, P. Vigmostad, C. Griwodz, and P. Halvorsen. 2013. Commute path bandwidth traces from 3G networks: analysis and applications. In Proceedings of the 4th ACM Multimedia Systems Conference. 114--118."},{"key":"e_1_3_2_2_50_1","unstructured":"S. Ross G. J. Gordon and J. A. Bagnell. 2011. A Reduction of Imitation Learn- ing and Structured Prediction to No-Regret Online Learning. arXiv preprint arXiv:1011.0686 (2011). arXiv:cs.LG\/1011.0686  S. Ross G. J. Gordon and J. A. Bagnell. 2011. A Reduction of Imitation Learn- ing and Structured Prediction to No-Regret Online Learning. arXiv preprint arXiv:1011.0686 (2011). arXiv:cs.LG\/1011.0686"},{"key":"e_1_3_2_2_51_1","volume-title":"Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence 1, 5 (01","author":"Rudin C.","year":"2019","unstructured":"C. Rudin . 2019. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence 1, 5 (01 May 2019 ), 206--215. https:\/\/doi.org\/10.1038\/s42256-019-0048-x 10.1038\/s42256-019-0048-x C. Rudin. 2019. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature Machine Intelligence 1, 5 (01 May 2019), 206--215. https:\/\/doi.org\/10.1038\/s42256-019-0048-x"},{"key":"e_1_3_2_2_52_1","volume-title":"Artificial Intelligence: A Modern Approach","author":"Russell S.","year":"2020","unstructured":"S. Russell and P. Norvig . 2020 . Artificial Intelligence: A Modern Approach ( 4 rd ed.). Pearson , USA. S. Russell and P. Norvig. 2020. Artificial Intelligence: A Modern Approach (4rd ed.). Pearson, USA.","edition":"4"},{"key":"e_1_3_2_2_53_1","volume-title":"A Value for n-Person Games","author":"Shapley L. S.","year":"1970","unstructured":"L. S. Shapley . 2016. 17. A Value for n-Person Games . Princeton University Press , 307--318. https:\/\/doi.org\/doi:10.1515\/978140088 1970 -018 10.1515\/9781400881970-018 L. S. Shapley. 2016. 17. A Value for n-Person Games. Princeton University Press, 307--318. https:\/\/doi.org\/doi:10.1515\/9781400881970-018"},{"key":"e_1_3_2_2_54_1","volume-title":"Proceedings of the 4th International Conference on Information Systems Security and Privacy - ICISSP,. INSTICC, SciTePress, 108--116","author":"Sharafaldin I.","unstructured":"I. Sharafaldin ., A. H. Lashkari ., and A. A. Ghorbani . 2018. Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization . In Proceedings of the 4th International Conference on Information Systems Security and Privacy - ICISSP,. INSTICC, SciTePress, 108--116 . https:\/\/doi.org\/10.5220\/ 0006639801080116 I. Sharafaldin., A. H. Lashkari., and A. A. Ghorbani. 2018. Toward Generating a New Intrusion Detection Dataset and Intrusion Traffic Characterization. In Proceedings of the 4th International Conference on Information Systems Security and Privacy - ICISSP,. INSTICC, SciTePress, 108--116. https:\/\/doi.org\/10.5220\/ 0006639801080116"},{"key":"e_1_3_2_2_55_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3041951"},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2018.2866249"},{"key":"e_1_3_2_2_57_1","volume-title":"Weinberger (Eds.)","volume":"25","author":"Snoek J.","year":"2012","unstructured":"J. Snoek , H. Larochelle , and R. P. Adams . 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems, F. Pereira, C.J. Burges, L. Bottou, and K.Q . Weinberger (Eds.) , Vol. 25 . Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper\/ 2012 \/file\/ 05311655a15b75fab86956663e1819cd-Paper.pdf J. Snoek, H. Larochelle, and R. P. Adams. 2012. Practical Bayesian Optimization of Machine Learning Algorithms. In Advances in Neural Information Processing Systems, F. Pereira, C.J. Burges, L. Bottou, and K.Q. Weinberger (Eds.), Vol. 25. Curran Associates, Inc. https:\/\/proceedings.neurips.cc\/paper\/2012\/file\/ 05311655a15b75fab86956663e1819cd-Paper.pdf"},{"key":"e_1_3_2_2_58_1","volume-title":"Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. In 2010 IEEE Symposium on Security and Privacy. 305--316","author":"Sommer R.","year":"2010","unstructured":"R. Sommer and V. Paxson . 2010 . Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. In 2010 IEEE Symposium on Security and Privacy. 305--316 . https:\/\/doi.org\/10.1109\/SP. 2010 .25 10.1109\/SP.2010.25 R. Sommer and V. Paxson. 2010. Outside the Closed World: On Using Machine Learning for Network Intrusion Detection. In 2010 IEEE Symposium on Security and Privacy. 305--316. https:\/\/doi.org\/10.1109\/SP.2010.25"},{"key":"e_1_3_2_2_59_1","volume-title":"Accessed on May 25th","author":"Turek M.","year":"2016","unstructured":"M. Turek . 2016. (2016 ). https:\/\/www.darpa.mil\/program\/explainable-artificial- intelligence Available at https:\/\/www.darpa.mil\/program\/explainable-artificial-intelligence. Accessed on May 25th , 2021. M. Turek. 2016. (2016). https:\/\/www.darpa.mil\/program\/explainable-artificial- intelligence Available at https:\/\/www.darpa.mil\/program\/explainable-artificial-intelligence. Accessed on May 25th, 2021."},{"key":"e_1_3_2_2_60_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF00993473"},{"key":"e_1_3_2_2_61_1","volume-title":"2017 IEEE International Conference on Intelligence and Security Informatics (ISI). 43--48","author":"Wang W.","year":"2017","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 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). 43--48 . https:\/\/doi.org\/10.1109\/ISI. 2017 .8004872 Code available at GitHub repository https:\/\/github.com\/echowei\/DeepTraffic. 10.1109\/ISI.2017.8004872 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 2017 IEEE International Conference on Intelligence and Security Informatics (ISI). 43--48. https:\/\/doi.org\/10.1109\/ISI.2017.8004872 Code available at GitHub repository https:\/\/github.com\/echowei\/DeepTraffic."},{"key":"e_1_3_2_2_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2836950"},{"key":"e_1_3_2_2_63_1","volume-title":"Proceedings of the 18th ACM Workshop on Hot Topics in Networks (HotNets '19)","author":"Xiong Z.","unstructured":"Z. Xiong and N. Zilberman . 2019. 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Association for Computing Machinery, New York, NY, USA, 25--33. https:\/\/doi.org\/10.1145\/3365609.3365864"},{"key":"e_1_3_2_2_64_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107315"}],"event":{"name":"CCS '22: 2022 ACM SIGSAC Conference on Computer and Communications Security","location":"Los Angeles CA USA","acronym":"CCS '22","sponsor":["SIGSAC ACM Special Interest Group on Security, Audit, and Control"]},"container-title":["Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3548606.3560609","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3548606.3560609","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3548606.3560609","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:48:58Z","timestamp":1750182538000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3548606.3560609"}},"subtitle":["The Emperor has no Clothes"],"short-title":[],"issued":{"date-parts":[[2022,11,7]]},"references-count":68,"alternative-id":["10.1145\/3548606.3560609","10.1145\/3548606"],"URL":"https:\/\/doi.org\/10.1145\/3548606.3560609","relation":{},"subject":[],"published":{"date-parts":[[2022,11,7]]},"assertion":[{"value":"2022-11-07","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}