{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T10:30:03Z","timestamp":1771065003659,"version":"3.50.1"},"reference-count":30,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,26]]},"DOI":"10.1109\/iccicc50026.2020.9450218","type":"proceedings-article","created":{"date-parts":[[2021,6,14]],"date-time":"2021-06-14T20:42:15Z","timestamp":1623703335000},"page":"1-6","source":"Crossref","is-referenced-by-count":4,"title":["Applying ML Algorithms to improve traffic classification in Intrusion Detection Systems"],"prefix":"10.1109","author":[{"given":"Laxmi Narsimha","family":"Reddy","sequence":"first","affiliation":[]},{"given":"Sergey","family":"Butakov","sequence":"additional","affiliation":[]},{"given":"Pavol","family":"Zavarsky","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref30","article-title":"10 Ways AI And Machine Learning Are Improving Endpoint Security","year":"2019","journal-title":"Forbes"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/STARTUP.2016.7583925"},{"key":"ref11","article-title":"Machine Learning Basics with the K-Nearest Neighbors Algorithm","author":"onel","year":"2018","journal-title":"Medium"},{"key":"ref12","article-title":"Supervised Machine Learning: A review of Classification Techniques","author":"breuker","year":"2007","journal-title":"Frontiers in Artificial Intelligence and Applications"},{"key":"ref13","article-title":"A Survey of Random Forest Based Methods for Intrusion Detection Systems","author":"angelo","year":"2018","journal-title":"ACM Computing Services"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/IRC.2019.00121"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23204"},{"key":"ref16","article-title":"Datasets","year":"2020","journal-title":"Univ New Brunswick"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3297156.3297230"},{"key":"ref18","article-title":"Learning Vector Quantization (LVQ) and k-Nearest Neighbor for Intrusion Classification","volume":"2","author":"naoum","year":"2012","journal-title":"World of Computer Science and Information Technology Journal (WCSIT)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-77465-5_19"},{"key":"ref28","article-title":"Ensemble methods: bagging, boosting and stacking","author":"rocca","year":"2019","journal-title":"Medium Towards Data Science"},{"key":"ref4","article-title":"Different types of Machine learning and their types","author":"sanjeevi","year":"2017","journal-title":"Towards Data Science"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2004.29"},{"key":"ref3","article-title":"Supervised Learning","author":"ryan","year":"2015","journal-title":"Analytics defined Science Direct"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/72.788645"},{"key":"ref29","article-title":"A review of supervised machine learning algorithms","author":"singh","year":"2016","journal-title":"3rd International Conference on Computing for Sustainable Global Development"},{"key":"ref5","article-title":"Gene Selection for Cancer Classification using Support Vector Machines","volume":"46","author":"vapnik","year":"2002","journal-title":"Machine Learning"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ECAI.2017.8166441"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CEEC.2017.8101615"},{"key":"ref2","year":"2020","journal-title":"NSL-KDD Dataset"},{"key":"ref9","article-title":"A Deep Learning Approach for Intrusion Detection Using Recurrent Neural Networks","author":"chuanlong","year":"2017","journal-title":"IEEE"},{"key":"ref1","article-title":"10 Ways AI And Machine Learning Are Improving Endpoint Security","author":"louis","year":"2019","journal-title":"Forbes"},{"key":"ref20","article-title":"Darknet and Deepnet Mining for Proactive","author":"nunes","year":"2016","journal-title":"IEEE Conference on Intelligence and Security Informatics (ISI)"},{"key":"ref22","article-title":"Hyperparameter Tuning Explained — Tuning Phases, Tuning Methods, Bayesian Optimization, and Sample Code!","year":"2019","journal-title":"Medium"},{"key":"ref21","year":"2020","journal-title":"Overview of hyperparameter tuning"},{"key":"ref24","article-title":"Algorithms for Hyper-Parameter Optimization","author":"bergstra","year":"2011","journal-title":"NIPS'11 Proceedings of the 24th International Conference on Neural Information Processing"},{"key":"ref23","author":"koehrsen","year":"0","journal-title":"Introduction Hyperparameter Tuning using Grid and Random Search"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/SIU.2018.8404601"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CONFLUENCE.2017.7943141"}],"event":{"name":"2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","location":"Beijing, China","start":{"date-parts":[[2020,9,26]]},"end":{"date-parts":[[2020,9,28]]}},"container-title":["2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9450047\/9450212\/09450218.pdf?arnumber=9450218","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,8,30]],"date-time":"2021-08-30T22:45:56Z","timestamp":1630363556000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9450218\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,26]]},"references-count":30,"URL":"https:\/\/doi.org\/10.1109\/iccicc50026.2020.9450218","relation":{},"subject":[],"published":{"date-parts":[[2020,9,26]]}}}