{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T10:48:57Z","timestamp":1777632537104,"version":"3.51.4"},"reference-count":38,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T00:00:00Z","timestamp":1603238400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,21]]},"DOI":"10.1109\/csnet50428.2020.9265461","type":"proceedings-article","created":{"date-parts":[[2021,4,14]],"date-time":"2021-04-14T04:26:32Z","timestamp":1618374392000},"page":"1-8","source":"Crossref","is-referenced-by-count":42,"title":["Unsupervised Machine Learning Techniques for Network Intrusion Detection on Modern Data"],"prefix":"10.1109","author":[{"given":"Miel","family":"Verkerken","sequence":"first","affiliation":[{"name":"Ghent University - imec,IDLab,Department of Information Technology,Ghent,Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laurens","family":"D'hooge","sequence":"additional","affiliation":[{"name":"Ghent University - imec,IDLab,Department of Information Technology,Ghent,Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tim","family":"Wauters","sequence":"additional","affiliation":[{"name":"Ghent University - imec,IDLab,Department of Information Technology,Ghent,Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruno","family":"Volckaert","sequence":"additional","affiliation":[{"name":"Ghent University - imec,IDLab,Department of Information Technology,Ghent,Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Filip","family":"De Turck","sequence":"additional","affiliation":[{"name":"Ghent University - imec,IDLab,Department of Information Technology,Ghent,Belgium"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.jisa.2020.102564"},{"key":"ref33","first-page":"281","article-title":"Random search for hyper-parameter optimization","volume":"13","author":"bergstra","year":"2012","journal-title":"J Mach Learn Res"},{"key":"ref32","article-title":"TensorFlow: Large-scale machine learning on heterogeneous systems","author":"abadi","year":"2015","journal-title":"software available from tensorflow org"},{"key":"ref31","author":"chollet","year":"2015","journal-title":"Keras"},{"key":"ref30","article-title":"From principal subspaces to principal components with linear autoencoders","author":"plaut","year":"2018"},{"key":"ref37","author":"verkerken","year":"2020","journal-title":"Aurocearlystoppingprunecallback"},{"key":"ref36","first-page":"2546","article-title":"Algorithms for hyper-parameter optimization","author":"bergstra","year":"2011","journal-title":"Proceedings of the 24th International Conference on Neural Information Processing Systems ser NIPS’11"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330701"},{"key":"ref34","first-page":"i?115","article-title":"Making a science of model search: Hyperparameter optimization in hundreds of dimensions for vision architectures","author":"bergstra","year":"2013","journal-title":"Proceedings of the 30th International Conference on International Conference on Machine Learning - Volume 28 ser ICML’13"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.13052\/jsn2445-9739.2017.009"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.5220\/0006639801080116"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2019.06.005"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2013.052213.00046"},{"key":"ref14","article-title":"A pattern matching model for misuse intrusion detection","author":"kumar","year":"1994"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.08.066"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2008.08.003"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2007.02.001"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.5220\/0007724801250136"},{"key":"ref28","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref4","first-page":"1","article-title":"A taxonomy of network threats and the effect of current datasets on intrusion detection systems","volume":"pp","author":"hindy","year":"2020","journal-title":"IEEE Access"},{"key":"ref27","year":"0","journal-title":"CICFlowMeter"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/988672.988742"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2013.052213.00046"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/089976601750399335"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2015.2494502"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref7","article-title":"Kdd cup 1999 data","year":"1999"},{"key":"ref2","article-title":"Requirements and model for ides: a real-time intrusion detection system","author":"denning","year":"1985"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.5937\/vojtehg66-16670"},{"key":"ref1","author":"kelly bissell","year":"2019","journal-title":"Ninth annual cost of cyber-crime study"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/ICACT.2008.4493974"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.2298\/CSIS130415035A"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/IAW.2004.1437839"},{"key":"ref24","doi-asserted-by":"crossref","DOI":"10.1109\/GLOBECOM42002.2020.9348167","article-title":"A hierarchical hybrid intrusion detection approach in iot scenarios","author":"bovenzi","year":"2020"},{"key":"ref23","article-title":"Characterization of encrypted and vpn traffic using time-related features","author":"habibi lashkari","year":"2016"},{"key":"ref26","first-page":"383","article-title":"Semi-supervised deep learning for network anomaly detection","author":"sun","year":"2020","journal-title":"Algorithms and Architectures for Parallel Processing"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3001350"}],"event":{"name":"2020 4th Cyber Security in Networking Conference (CSNet)","location":"Lausanne, Switzerland","start":{"date-parts":[[2020,10,21]]},"end":{"date-parts":[[2020,10,23]]}},"container-title":["2020 4th Cyber Security in Networking Conference (CSNet)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9265454\/9265455\/09265461.pdf?arnumber=9265461","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,27]],"date-time":"2022-06-27T15:43:17Z","timestamp":1656344597000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9265461\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,21]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/csnet50428.2020.9265461","relation":{},"subject":[],"published":{"date-parts":[[2020,10,21]]}}}