{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:05:19Z","timestamp":1778083519592,"version":"3.51.4"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031184086","type":"print"},{"value":"9783031184093","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,11,5]],"date-time":"2022-11-05T00:00:00Z","timestamp":1667606400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,11,5]],"date-time":"2022-11-05T00:00:00Z","timestamp":1667606400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-18409-3_19","type":"book-chapter","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T14:04:09Z","timestamp":1667570649000},"page":"192-201","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Deep Learning-Based Approach for\u00a0Mimicking Network Topologies: The Neris Botnet as\u00a0a\u00a0Case of\u00a0Study"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8462-0175","authenticated-orcid":false,"given":"Francisco","family":"\u00c1lvarez-Terribas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7744-7308","authenticated-orcid":false,"given":"Roberto","family":"Mag\u00e1n-Carri\u00f3n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9256-453X","authenticated-orcid":false,"given":"Gabriel","family":"Maci\u00e1-Fern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1603-9105","authenticated-orcid":false,"given":"Antonio M.","family":"Mora Garc\u00eda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,5]]},"reference":[{"key":"19_CR1","unstructured":"Abadi, M., et al.: TensorFlow: large-scale machine learning on heterogeneous systems (2015)"},{"issue":"6","key":"19_CR2","doi-asserted-by":"publisher","first-page":"1326","DOI":"10.1016\/j.comnet.2010.12.002","volume":"55","author":"R Alshammari","year":"2011","unstructured":"Alshammari, R., Zincir-Heywood, A.N.: Can encrypted traffic be identified without port numbers, IP addresses and payload inspection? Comput. Netw. 55(6), 1326\u20131350 (2011)","journal-title":"Comput. Netw."},{"key":"19_CR3","unstructured":"Bakker, B.: Reinforcement learning with long short-term memory. In: Dietterich, T., Becker, S., Ghahramani, Z. (eds.) Advances in Neural Information Processing Systems, vol. 14. MIT Press (2001)"},{"issue":"2","key":"19_CR4","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1109\/TKDE.2012.232","volume":"26","author":"S Barua","year":"2014","unstructured":"Barua, S., Islam, M.M., Yao, X., Murase, K.: MWMOTE-majority weighted minority oversampling technique for imbalanced data set learning. IEEE Trans. Knowl. Data Eng. 26(2), 405\u2013425 (2014)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"19_CR5","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: SMOTE: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","journal-title":"J. Artif. Intell. Res."},{"key":"19_CR6","unstructured":"Cisco: Cisco Annual Internet Report (2018\u20132023) White Paper (2020). https:\/\/bit.ly\/3jpAgNx"},{"key":"19_CR7","doi-asserted-by":"crossref","unstructured":"Dablain, D., Krawczyk, B., Chawla, N.V.: DeepSMOTE: fusing deep learning and smote for imbalanced data. IEEE Trans. Neural Netw. Learn. Syst. 1\u201315 (2022)","DOI":"10.1109\/TNNLS.2021.3136503"},{"key":"19_CR8","doi-asserted-by":"crossref","unstructured":"Engelmann, J., Lessmann, S.: Conditional Wasserstein GAN-based oversampling of tabular data for imbalanced learning. Expert Syst. Appl. 174, 114582 (2021)","DOI":"10.1016\/j.eswa.2021.114582"},{"key":"19_CR9","unstructured":"ENISA: ENISA Threat Landscape (2020) White Paper (2020). https:\/\/www.enisa.europa.eu\/news\/enisa-news\/enisa-threat-landscape-2020"},{"key":"19_CR10","doi-asserted-by":"crossref","unstructured":"Fajardo, V.A., et al.: On oversampling imbalanced data with deep conditional generative models. Expert Syst. Appl. 169, 114463 (2021)","DOI":"10.1016\/j.eswa.2020.114463"},{"key":"19_CR11","unstructured":"He, H., Bai, Y., Garcia, E.A., Li, S.: ADASYN: adaptive synthetic sampling approach for imbalanced learning. In: 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence), pp. 1322\u20131328 (2008)"},{"key":"19_CR12","unstructured":"Kingma, D.P., Welling, M.: Auto-encoding variational bayes. arXiv preprint arXiv:1312.6114 (2013)"},{"key":"19_CR13","unstructured":"Lab, S.: CTU-13 Dataset. Capture 42. Neris botnet (2011)"},{"key":"19_CR14","doi-asserted-by":"crossref","unstructured":"Lim, S.K., Loo, Y., Tran, N.T., Cheung, N.M., Roig, G., Elovici, Y.: Doping: generative data augmentation for unsupervised anomaly detection with GAN. In: 2018 IEEE International Conference on Data Mining (ICDM), pp. 1122\u20131127 (2018)","DOI":"10.1109\/ICDM.2018.00146"},{"key":"19_CR15","doi-asserted-by":"publisher","unstructured":"Maci\u00e1-Fern\u00e1ndez, G., Camacho, J., Mag\u00e1n-Carri\u00f3n, R., Garc\u00eda-Teodoro, P., Ther\u00f3n, R.: UGR\u201916: a new dataset for the evaluation of cyclostationarity-based network IDSs. Comput. Secur. 73, 411\u2013424 (2018). https:\/\/doi.org\/10.1016\/j.cose.2017.11.004","DOI":"10.1016\/j.cose.2017.11.004"},{"key":"19_CR16","doi-asserted-by":"crossref","unstructured":"Mag\u00e1n-Carri\u00f3n, R., Urda, D., Diaz-Cano, I., Dorronsoro, B.: Towards a reliable comparison and evaluation of network intrusion detection systems based on machine learning approaches. Appl. Sci. 10(5) (2020)","DOI":"10.3390\/app10051775"},{"key":"19_CR17","unstructured":"Medina, A., Lakhina, A., Matta, I., Byers, J.: Brite: an approach to universal topology generation. In: Proceedings Ninth International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, MASCOTS 2001, pp. 346\u2013353. IEEE (2001)"},{"issue":"2","key":"19_CR18","first-page":"705","volume":"52","author":"JP Sterbenz","year":"2013","unstructured":"Sterbenz, J.P., \u00c7etinkaya, E.K., Hameed, M.A., Jabbar, A., Qian, S., Rohrer, J.P.: Evaluation of network resilience, survivability, and disruption tolerance: analysis, topology generation, simulation, and experimentation. Telecommun. Syst. 52(2), 705\u2013736 (2013)","journal-title":"Telecommun. Syst."},{"key":"19_CR19","unstructured":"Vaswani, A., et al.: Attention is all you need. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"19_CR20","doi-asserted-by":"crossref","unstructured":"Vu, L., Bui, C.T., Nguyen, Q.U.: A deep learning based method for handling imbalanced problem in network traffic classification. In: Proceedings of the Eighth International Symposium on Information and Communication Technology, SoICT 2017, pp. 333\u2013339. Association for Computing Machinery, New York (2017)","DOI":"10.1145\/3155133.3155175"},{"key":"19_CR21","doi-asserted-by":"crossref","unstructured":"Xiong, P., Buffett, S., Iqbal, S., Lamontagne, P., Mamun, M., Molyneaux, H.: Towards a robust and trustworthy machine learning system development: an engineering perspective. J. Inf. Secur. Appl. 65, 103121 (2022)","DOI":"10.1016\/j.jisa.2022.103121"}],"container-title":["Lecture Notes in Networks and Systems","International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022)"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-18409-3_19","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T14:40:20Z","timestamp":1667572820000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-18409-3_19"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,5]]},"ISBN":["9783031184086","9783031184093"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-18409-3_19","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,5]]},"assertion":[{"value":"5 November 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CISIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Computational Intelligence in Security for Information Systems Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Salamanca","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cisis-spain2022a","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2022.cisisconference.eu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}