{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T18:57:29Z","timestamp":1783969049646,"version":"3.55.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T00:00:00Z","timestamp":1555545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2019,4,18]]},"DOI":"10.1145\/3299815.3314439","type":"proceedings-article","created":{"date-parts":[[2019,5,7]],"date-time":"2019-05-07T12:16:01Z","timestamp":1557231361000},"page":"86-93","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":179,"title":["Intrusion Detection Using Big Data and Deep Learning Techniques"],"prefix":"10.1145","author":[{"given":"Osama","family":"Faker","sequence":"first","affiliation":[{"name":"Cankaya University, Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Erdogan","family":"Dogdu","sequence":"additional","affiliation":[{"name":"Cankaya University, Georgia State University (adjunct), Ankara, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2019,4,18]]},"reference":[{"key":"e_1_3_2_1_1_1","first-page":"167","volume-title":"2017 International Conference on New Trends in Computing Sciences (ICTCS)","author":"Al-Zewairi M.","unstructured":"M. Al-Zewairi, S. Almajali, and A. Awajan. 2017. Experimental Evaluation of a Multi-layer Feed-Forward Artificial Neural Network Classifier for Network Intrusion Detection System. 2017 International Conference on New Trends in Computing Sciences (ICTCS), Amman, Jordan, pp. 167--172, IEEE"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.14569\/IJACSA.2017.080651"},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.01.091"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"e_1_3_2_1_6_1","volume-title":"European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning","author":"Coelho F.","unstructured":"F. Coelho, A. Braga, and M. Verleysen. 2012. Cluster Homogeneity as a Semi-supervised Principle for Feature Selection Using Mutual Information. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, Bruges, Belgium."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2018.05.169"},{"issue":"6","key":"e_1_3_2_1_8_1","first-page":"446","article-title":"A Study on NSL KDD Dataset for Intrusion Detection System based on Classification Algorithms","volume":"4","author":"Dhanabal L.","year":"2015","unstructured":"L. Dhanabal, and S. p.Shantharajah. 2015. A Study on NSL KDD Dataset for Intrusion Detection System based on Classification Algorithms. International Journal of Advanced Research in Computer and Communication Engineering, 4(6), pp. 446--452.","journal-title":"International Journal of Advanced Research in Computer and Communication Engineering"},{"key":"e_1_3_2_1_9_1","volume-title":"Intrusion Detection Systems. Springer Science & Business","volume":"38","author":"Di Pietro R.","unstructured":"R. Di Pietro and L. V. Mancini, eds. 2008. Intrusion Detection Systems. Springer Science & Business, vol. 38. Media."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-9473(01)00065-2"},{"key":"e_1_3_2_1_12_1","first-page":"139","volume-title":"Telecommunications (IST), 2016 8th International Symposium on. IEEE","author":"Gharaee H.","unstructured":"H. Gharaee and H. Hosseinvand. 2016. A New Feature Selection IDS based on Genetic Algorithm and SVM. Telecommunications (IST), 2016 8th International Symposium on. IEEE, pp. 139--144."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2016.07.238"},{"key":"e_1_3_2_1_14_1","first-page":"363","volume-title":"South Africa 2011 6th International Conference on","author":"Han J.","unstructured":"J. Han, E. Haihong, G. Le, and J. Du. 2011. Survey on NoSQL Databases. In Pervasive Computing and Applications (ICPCA), Port Elizabeth, South Africa 2011 6th International Conference on, pp. 363--366. IEEE."},{"key":"e_1_3_2_1_15_1","first-page":"253","volume-title":"The 3rd International Conference on Information Systems Security and Privacy","author":"Lashkari A.","unstructured":"A. Lashkari, G. Draper-Gil, M. Mamun, and A. Ghorbani. 2017. Characterization of Tor Traffic Using Time based Features. The 3rd International Conference on Information Systems Security and Privacy, pp. 253--262."},{"key":"e_1_3_2_1_16_1","first-page":"147","volume-title":"Random Forest Algorithm in Big Data Environment. Computer Modelling & New Technologies, 18(12A)","author":"Liu Y.","unstructured":"Y. Liu. 2014. Random Forest Algorithm in Big Data Environment. Computer Modelling & New Technologies, 18(12A), pp. 147--151."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1080\/19393555.2015.1125974"},{"key":"e_1_3_2_1_18_1","first-page":"1","volume-title":"Military Communications and Information Systems Conference (MilCIS)","author":"Moustafa N.","unstructured":"N. Moustafa and J. Slay. 2015. UNSW-NB15: A Comprehensive Data Set for Network Intrusion Detection Systems (UNSW-NB15 Network Data Set). Military Communications and Information Systems Conference (MilCIS), Canberra, Australia, pp. 1--6, IEEE."},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1080\/19393555.2015.1125974"},{"key":"e_1_3_2_1_20_1","first-page":"1","volume-title":"International Conference on, Palembang Sumatra Selatan","author":"Primartha R.","unstructured":"R. Primartha and B. Tama. 2017. Anomaly Detection Using Random Forest: A Performance Revisited. Data and Software Engineering (ICoDSE), International Conference on, Palembang Sumatra Selatan, Indonesia, pp. 1--6, IEEE."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"P. Resende and A. Drummond. 2018. Adaptive Anomaly-based Intrusion Detection System Using Genetic Algorithm and Profiling. Security and Privacy e36 pp. 1--13.","DOI":"10.1002\/spy2.36"},{"key":"e_1_3_2_1_22_1","first-page":"410","volume-title":"Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning(EMNLP-CoNLL)","author":"Rosenberg A.","unstructured":"A. Rosenberg and J. Hirschberg. 2007. V-measure: A Conditional Entropy-based External Cluster Evaluation Measure. Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning(EMNLP-CoNLL), pp. 410--420."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.5220\/0006639801080116"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.13052\/jsn2445-9739.2017.009"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSST.2010.5496972"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2017.09.031"},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/2627534.2627557"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.5555\/1736481.1736489"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687553.1687609"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-008-9229-6"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2018.04.010"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2934664"},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"C. Zhang and Y. Ma eds. 2012. Ensemble Machine Learning: Methods and Applications. Springer Science & Business Media Springer.","DOI":"10.1007\/978-1-4419-9326-7"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","unstructured":"P. Zikopoulos and C. Eaton. 2011. Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data. McGraw-Hill Osborne Media.","DOI":"10.5555\/2132803"},{"issue":"3","key":"e_1_3_2_1_36_1","first-page":"1","article-title":"Intrusion Detection and Big Heterogeneous Data: A Survey","volume":"2","author":"Zuech R.","year":"2015","unstructured":"R. Zuech, T. M. Khoshgoftaar, and R. Wald. 2015. Intrusion Detection and Big Heterogeneous Data: A Survey. Journal of Big Data, 2(3), pp. 1--41.","journal-title":"Journal of Big Data"}],"event":{"name":"ACM SE '19: 2019 ACM Southeast Conference","location":"Kennesaw GA USA","acronym":"ACM SE '19","sponsor":["ACM Association for Computing Machinery"]},"container-title":["Proceedings of the 2019 ACM Southeast Conference"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3299815.3314439","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3299815.3314439","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T00:26:13Z","timestamp":1750206373000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3299815.3314439"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,18]]},"references-count":35,"alternative-id":["10.1145\/3299815.3314439","10.1145\/3299815"],"URL":"https:\/\/doi.org\/10.1145\/3299815.3314439","relation":{},"subject":[],"published":{"date-parts":[[2019,4,18]]},"assertion":[{"value":"2019-04-18","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}