{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T06:31:21Z","timestamp":1743143481368,"version":"3.40.3"},"publisher-location":"Cham","reference-count":22,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030815226"},{"type":"electronic","value":"9783030815233"}],"license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"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":[[2022]]},"DOI":"10.1007\/978-3-030-81523-3_28","type":"book-chapter","created":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T17:12:29Z","timestamp":1629220349000},"page":"284-292","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Extending Machine Learning-Based Intrusion Detection with the Imputation Method"],"prefix":"10.1007","author":[{"given":"Miko\u0142aj","family":"Komisarek","sequence":"first","affiliation":[]},{"given":"Marek","family":"Pawlicki","sequence":"additional","affiliation":[]},{"given":"Piotr","family":"Sobo\u0144ski","sequence":"additional","affiliation":[]},{"given":"Aleksandra","family":"Pawlicka","sequence":"additional","affiliation":[]},{"given":"Rafa\u0142","family":"Kozik","sequence":"additional","affiliation":[]},{"given":"Micha\u0142","family":"Chora\u015b","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"28_CR1","unstructured":"Agustin, P., Sebastian, G., Maria Jose, E.: Stratosphere laboratory. A labeled dataset with malicious and benign IoT network traffic (2020). https:\/\/www.stratosphereips.org\/datasets-iot23"},{"key":"28_CR2","unstructured":"ApacheKafka: https:\/\/kafka.apache.org"},{"issue":"1","key":"28_CR3","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1002\/mpr.329","volume":"20","author":"MJ Azur","year":"2011","unstructured":"Azur, M.J., Stuart, E.A., Frangakis, C., Leaf, P.J.: Multiple imputation by chained equations: what is it and how does it work? IJMPR 20(1), 40\u201349 (2011). https:\/\/doi.org\/10.1002\/mpr.329","journal-title":"IJMPR"},{"key":"28_CR4","doi-asserted-by":"crossref","unstructured":"Baio, G., Leurent, B.: An introduction to handling missing data in health economic evaluations. In: Care at the End of Life (2016). tinyurl.com\/19hh58ba","DOI":"10.1007\/978-3-319-28267-1_6"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Chora\u015b, M., Pawlicki, M.: Intrusion detection approach based on optimised artificial neural network. Neurocomputing (2020)","DOI":"10.1016\/j.neucom.2020.07.138"},{"key":"28_CR6","unstructured":"Elasticsearch: elasticsearch\/elasticsearch (2015). https:\/\/tinyurl.com\/ltzbptc5"},{"key":"28_CR7","unstructured":"EU Science Hub: Cybersecurity (2021). https:\/\/tinyurl.com\/2c8telmz"},{"key":"28_CR8","unstructured":"European Council: Cybersecurity: How the EU tackles cyber threats (2021). https:\/\/www.consilium.europa.eu\/en\/policies\/cybersecurity\/"},{"key":"28_CR9","doi-asserted-by":"crossref","unstructured":"Fan, W., Geerts, F.: Foundations of data quality management. Synthesis Lect. Data Manage. 4(5), 1\u2013217 (2012). https:\/\/tinyurl.com\/183828pu","DOI":"10.2200\/S00439ED1V01Y201207DTM030"},{"key":"28_CR10","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4614-4018-5","volume-title":"Missing Data","author":"JW Graham","year":"2012","unstructured":"Graham, J.W.: Missing Data. Springer, New York (2012). https:\/\/doi.org\/10.1007\/978-1-4614-4018-5"},{"key":"28_CR11","unstructured":"Joint Communication to the European Parliament and the Council: The EU\u2019s Cybersecurity Strategy for the Digital Decade (2020)"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Ksieniewicz, P., Wo\u017aniak, M.: Imbalanced data classification based on feature selection techniques. In: IDEAL, pp. 296\u2013303. Springer (2018)","DOI":"10.1007\/978-3-030-03496-2_33"},{"key":"28_CR13","unstructured":"Nec: Why is cyber security important? \u2013 Why we need cyber security (2020). https:\/\/tinyurl.com\/3h52993g"},{"issue":"4","key":"28_CR14","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1109\/MTS.2020.3031848","volume":"39","author":"A Pawlicka","year":"2020","unstructured":"Pawlicka, A., Jaroszewska-Choras, D., Choras, M., Pawlicki, M.: Guidelines for stego\/malware detection tools: achieving GDPR compliance. IEEE Technol. Soc. Mag. 39(4), 60\u201370 (2020)","journal-title":"IEEE Technol. Soc. Mag."},{"key":"28_CR15","doi-asserted-by":"crossref","unstructured":"Pawlicki, M., Chora\u015b, M., Kozik, R., Ho\u0142ubowicz, W.: On the impact of network data balancing in cybersecurity applications. In: ICCS, pp. 196\u2013210. Springer (2020)","DOI":"10.1007\/978-3-030-50423-6_15"},{"key":"28_CR16","unstructured":"Scikit-learn. https:\/\/scikit-learn.org\/"},{"key":"28_CR17","unstructured":"StartSmarter: The Advantages and Disadvantages of Digitalisation (2019). https:\/\/startsmarter.co.uk\/the-advantages-and-disadvantages-of-digitalisation\/"},{"key":"28_CR18","doi-asserted-by":"crossref","unstructured":"Stekhoven, D.J., Buhlmann, P.: MissForest\u2013non-parametric missing value imputation for mixed-type data. Bioinformatics 28(1), 112\u2013118 (2012). https:\/\/tinyurl.com\/3h74tza2","DOI":"10.1093\/bioinformatics\/btr597"},{"key":"28_CR19","unstructured":"TensorFlow. https:\/\/www.tensorflow.org"},{"key":"28_CR20","doi-asserted-by":"publisher","unstructured":"Tripathi, A.K., Rathee, G., Saini, H.: Taxonomy of missing data along with their handling methods. In: ICIIP, pp. 463\u2013468 (2019). https:\/\/doi.org\/10.1109\/ICIIP47207.2019.8985715","DOI":"10.1109\/ICIIP47207.2019.8985715"},{"key":"28_CR21","doi-asserted-by":"publisher","unstructured":"Zeng, D., Xie, D., Liu, R., Li, X.: Missing value imputation methods for TCM medical data and its effect in the classifier accuracy. In: IEEE Healthcom, pp. 1\u20134 (2017). https:\/\/doi.org\/10.1109\/HealthCom.2017.8210844","DOI":"10.1109\/HealthCom.2017.8210844"},{"key":"28_CR22","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Kambhampati, C., Davis, D.N., Goode, K., Cleland, J.G.F.: A comparative study of missing value imputation with multiclass classification for clinical heart failure data. In: 2012 9th ICNC-FSKD, pp. 2840\u20132844 (2012). https:\/\/doi.org\/10.1109\/FSKD.2012.6233805","DOI":"10.1109\/FSKD.2012.6233805"}],"container-title":["Lecture Notes in Networks and Systems","Progress in Image Processing, Pattern Recognition and Communication Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-81523-3_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,17]],"date-time":"2021-08-17T17:19:18Z","timestamp":1629220758000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-81523-3_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,18]]},"ISBN":["9783030815226","9783030815233"],"references-count":22,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-81523-3_28","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2021,8,18]]},"assertion":[{"value":"18 August 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CORES","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computer Recognition Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 June 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"cores2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/cores.pwr.edu.pl","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}