{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T04:09:08Z","timestamp":1750910948428,"version":"3.41.0"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811063848"},{"type":"electronic","value":"9789811063855"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-981-10-6385-5_17","type":"book-chapter","created":{"date-parts":[[2017,9,15]],"date-time":"2017-09-15T14:03:52Z","timestamp":1505484232000},"page":"192-206","source":"Crossref","is-referenced-by-count":3,"title":["A Cooperative Abnormal Behavior Detection Framework Based on Big Data Analytics"],"prefix":"10.1007","author":[{"given":"Naila","family":"Marir","sequence":"first","affiliation":[]},{"given":"Huiqiang","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,16]]},"reference":[{"issue":"10","key":"17_CR1","doi-asserted-by":"crossref","first-page":"11994","DOI":"10.1016\/j.eswa.2009.05.029","volume":"36","author":"CF Tsai","year":"2009","unstructured":"Tsai, C.F., Hsu, Y.F., Lin, C.Y., Lin, W.Y.: Intrusion detection by machine learning: a review. Expert Syst. Appl. 36(10), 11994\u201312000 (2009)","journal-title":"Expert Syst. Appl."},{"key":"17_CR2","unstructured":"Janssen, T., Grady, N.: Big data for combating cyber attacks. In: CEUR Workshop Proceedings, Fairfax, vol. 1097, pp. 151\u2013158 (2013)"},{"issue":"6","key":"17_CR3","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1109\/MSP.2013.138","volume":"11","author":"AA Cardenas","year":"2013","unstructured":"Cardenas, A.A., Manadhata, P.K., Rajan, S.P.: Big data analytics for security. IEEE Secur. Priv. 11(6), 74\u201376 (2013)","journal-title":"IEEE Secur. Priv."},{"key":"17_CR4","doi-asserted-by":"crossref","unstructured":"Scarfone, K.A., Mell, P.M.: Guide to intrusion detection and prevention systems (IDPS), Special Publication (NIST SP), pp. 800\u2013894 (2007)","DOI":"10.6028\/NIST.SP.800-94"},{"key":"17_CR5","unstructured":"Jones, A.K., Sielken, R.S.: Computer system intrusion detection: a survey. Technical report, Computer Science Department, University of Virginia (2000)"},{"key":"17_CR6","unstructured":"Zamani, M., Movahedi, M.: Machine learning techniques for intrusion detection (2013). arXiv preprint arXiv:1312-2177"},{"issue":"4","key":"17_CR7","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1145\/2627534.2627557","volume":"41","author":"S Suthaharan","year":"2014","unstructured":"Suthaharan, S.: Big data classification: problems and challenges in network intrusion prediction with machine learning. ACM SIGMETRICS Perform. Eval. Rev. 41(4), 70\u201373 (2014)","journal-title":"ACM SIGMETRICS Perform. Eval. Rev."},{"issue":"1","key":"17_CR8","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1145\/2427036.2427038","volume":"43","author":"Y Lee","year":"2012","unstructured":"Lee, Y., Lee, Y.: Toward scalable internet traffic measurement and analysis with Hadoop. SIGCOMM Comput. Commun. Rev. 43(1), 5\u201313 (2012)","journal-title":"SIGCOMM Comput. Commun. Rev."},{"key":"17_CR9","doi-asserted-by":"crossref","unstructured":"Ahn, S.H., Kim, N.U., Chung, T.M.: Big data analysis system concept for detecting unknown attacks. In: 16th International Conference on Advanced Communication Technology (ICACT), South Korea, pp. 16\u201319 (2014)","DOI":"10.1109\/ICACT.2014.6778962"},{"key":"17_CR10","doi-asserted-by":"crossref","unstructured":"Marchal, S., Jiang, X., State, R., Engel, T.: A big data architecture for large scale security monitoring. In: Proceedings of IEEE International Congress Big Data, Anchorage, pp. 56\u201363 (2010)","DOI":"10.1109\/BigData.Congress.2014.18"},{"issue":"9","key":"17_CR11","doi-asserted-by":"crossref","first-page":"3489","DOI":"10.1007\/s11227-015-1615-5","volume":"72","author":"MM Rathore","year":"2016","unstructured":"Rathore, M.M., Ahmad, A., Paul, A.: Real time intrusion detection system for ultra-high-speed big data environments. J. Supercomput. 72(9), 3489\u20133510 (2016)","journal-title":"J. Supercomput."},{"key":"17_CR12","unstructured":"Dos Santos, E.M.: Static and dynamic overproduction and selection of classifier ensembles with genetic algorithms. Ecole de Technologie Superieure, Canada (2008)"},{"key":"17_CR13","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.cose.2016.11.004","volume":"65","author":"AA Aburomman","year":"2017","unstructured":"Aburomman, A.A., Ibne Reaz, M.B.: A survey of intrusion detection systems based on ensemble and hybrid classifiers. Comput. Secur. 65, 135\u2013152 (2017)","journal-title":"Comput. Secur."},{"key":"17_CR14","doi-asserted-by":"crossref","unstructured":"Gaikwad, D.P., Thool, R.C.: Intrusion detection system using bagging ensemble method of machine learning. In: International Conference on Computing Communication Control and Automation, pp. 291\u2013295. IEEE (2015)","DOI":"10.1109\/ICCUBEA.2015.61"},{"key":"17_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1007\/978-3-319-16549-3_5","volume-title":"Applications of Evolutionary Computation","author":"G Folino","year":"2015","unstructured":"Folino, G., Pisani, F.S.: Combining ensemble of classifiers by using genetic programming for cyber security applications. In: Mora, A.M., Squillero, G. (eds.) EvoApplications 2015. LNCS, vol. 9028, pp. 54\u201366. Springer, Cham (2015). doi: 10.1007\/978-3-319-16549-3_5"},{"key":"17_CR16","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.asoc.2015.10.011","volume":"38","author":"AA Aburomman","year":"2016","unstructured":"Aburomman, A.A., Ibne Reaz, M.B.: A novel SVM-kNN-PSO ensemble method for intrusion detection system. Appl. Soft Comput. 38, 360\u2013372 (2016)","journal-title":"Appl. Soft Comput."},{"key":"17_CR17","volume-title":"Statistical Learning Theory","author":"V Vapnik","year":"1998","unstructured":"Vapnik, V.: Statistical Learning Theory. Wiley-Interscience, New York (1998)"}],"container-title":["Communications in Computer and Information Science","Data Science"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-10-6385-5_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T19:26:34Z","timestamp":1750879594000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-10-6385-5_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9789811063848","9789811063855"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-10-6385-5_17","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2017]]}}}