{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T15:01:02Z","timestamp":1777042862568,"version":"3.51.4"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2016,4,18]],"date-time":"2016-04-18T00:00:00Z","timestamp":1460937600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Front. Comput. Sci."],"published-print":{"date-parts":[[2016,8]]},"DOI":"10.1007\/s11704-015-5116-8","type":"journal-article","created":{"date-parts":[[2016,4,19]],"date-time":"2016-04-19T05:14:12Z","timestamp":1461042852000},"page":"755-766","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Local outlier factor and stronger one class classifier based hierarchical model for detection of attacks in network intrusion detection dataset"],"prefix":"10.1007","volume":"10","author":[{"given":"Alampallam Ramaswamy","family":"Vasudevan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Subramanian","family":"Selvakumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,4,18]]},"reference":[{"issue":"1","key":"5116_CR1","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.ins.2013.03.022","volume":"239","author":"I Corona","year":"2013","unstructured":"Corona I, Giacinto G, Roli F Adversarial attacks against intrusion detection systems: taxonomy, solutions and open issues. Information Sciences, 2013, 239 (1): 201\u2013225","journal-title":"Information Sciences"},{"issue":"1","key":"5116_CR2","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1080\/09700160903354450","volume":"34","author":"A Sharma","year":"2010","unstructured":"Sharma A. Cyber wars: a paradigm shift from means to ends. Strategic Analysis, 2010, 34 (1): 62\u201373","journal-title":"Strategic Analysis"},{"issue":"2","key":"5116_CR3","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1109\/TSE.1987.232894","volume":"13","author":"D E Denning","year":"1987","unstructured":"Denning D E. An intrusion-detection model. IEEE Transactions on Software Engineering, 1987, 13 (2): 222\u2013232","journal-title":"IEEE Transactions on Software Engineering"},{"issue":"1","key":"5116_CR4","doi-asserted-by":"crossref","first-page":"303","DOI":"10.1109\/SURV.2013.052213.00046","volume":"16","author":"M H Bhuyan","year":"2014","unstructured":"Bhuyan M H, Bhattacharyya D K, Kalita J K. Network anomaly detection: methods, systems and tools. IEEE Communications Surveys & Tutorials, 2014, 16(1): 303\u2013336","journal-title":"IEEE Communications Surveys & Tutorials"},{"issue":"6","key":"5116_CR5","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.cose.2011.05.008","volume":"30","author":"J J Davis","year":"2011","unstructured":"Davis J J, Clark A J. Data preprocessing for anomaly based network intrusion detection: a review. Computers & Security, 2011, 30(6): 353\u2013375","journal-title":"Computers & Security"},{"issue":"3","key":"5116_CR6","doi-asserted-by":"crossref","first-page":"5605","DOI":"10.1016\/j.eswa.2008.06.138","volume":"36","author":"S Y Wu","year":"2009","unstructured":"Wu S Y, Yen E. Data mining-based intrusion detectors. Expert Systems with Applications, 2009, 36(3): 5605\u20135612","journal-title":"Expert Systems with Applications"},{"issue":"7","key":"5116_CR7","doi-asserted-by":"crossref","first-page":"802","DOI":"10.1016\/j.patrec.2005.11.007","volume":"27","author":"S Y Jiang","year":"2006","unstructured":"Jiang S Y, Song X, Wang H, Han J J, Li QH. A clustering-based method for unsupervised intrusion detections. Pattern Recognition Letters, 2006, 27(7): 802\u2013810","journal-title":"Pattern Recognition Letters"},{"key":"5116_CR8","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1007\/978-90-481-3662-9_86","volume-title":"Novel Algorithms and Techniques in Telecommunications and Networking.Springer Netherlands","author":"R GM Helali","year":"2010","unstructured":"Helali R GM. Data mining based network intrusion detection system: a survey. In: Sobh T, Elleithy K, Mahmood A, eds. Novel Algorithms and Techniques in Telecommunications and Networking.Springer Netherlands, 2010, 501\u2013505"},{"key":"5116_CR9","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/1-4020-3675-2_25","volume-title":"Enterprise Information Systems VI","author":"S Mukkamala","year":"2006","unstructured":"Mukkamala S, Sung A H, Abraham A, Ramos, V. Intrusion detection systems using adaptive regression spines. In: Seruca I, Cordeiro J, Hammoudi S, Filipe J. Enterprise Information Systems VI, 2006, 211\u2013218"},{"issue":"2","key":"5116_CR10","doi-asserted-by":"crossref","first-page":"462","DOI":"10.1016\/j.asoc.2008.06.001","volume":"9","author":"A Tajbakhsh","year":"2009","unstructured":"Tajbakhsh A, Rahmati M, Mirzaei A. Intrusion detection using fuzzy association rules. Applied Soft Computing, 2009, 9(2): 462\u2013469","journal-title":"Applied Soft Computing"},{"issue":"5","key":"5116_CR11","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1016\/j.cose.2008.12.001","volume":"28","author":"M Y Su","year":"2009","unstructured":"Su M Y, Yu G J, Lin C Y. A real-time network intrusion detection system for large-scale attacks based on an incremental mining approach. Computers & Security, 2009, 28(5): 301\u2013309","journal-title":"Computers & Security"},{"issue":"18","key":"5116_CR12","doi-asserted-by":"crossref","first-page":"2227","DOI":"10.1016\/j.comcom.2011.07.001","volume":"34","author":"P Sangkatsanee","year":"2011","unstructured":"Sangkatsanee P, Wattanapongsakorn N, Charnsripinyo C. Practical real-time intrusion detection using machine learning approaches. Computer Communications, 2011, 34(18): 2227\u20132235","journal-title":"Computer Communications"},{"key":"5116_CR13","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1109\/CSAC.1999.816048","volume-title":"Proceedings of the 15th Annual Conference on Computer Security Applications","author":"C Sinclair","year":"1999","unstructured":"Sinclair C, Pierce L, Matzner S. An application of machine learning to network intrusion detection. In: Proceedings of the 15th Annual Conference on Computer Security Applications. 1999, 371\u2013377"},{"key":"5116_CR14","first-page":"305","volume-title":"Proceedings of IEEE Symposium on Security and Privacy","author":"R Sommer","year":"2010","unstructured":"Sommer R, Paxson V. Outside the closed world: on using machine learning for network intrusion detection. In: Proceedings of IEEE Symposium on Security and Privacy. 2010, 305\u2013316"},{"issue":"8","key":"5116_CR15","doi-asserted-by":"crossref","first-page":"651","DOI":"10.1016\/j.patrec.2009.09.011","volume":"31","author":"A K Jain","year":"2010","unstructured":"Jain A K. Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 2010, 31(8): 651\u2013666","journal-title":"Pattern Recognition Letters"},{"key":"5116_CR16","first-page":"1702","volume-title":"Proceedings of the 2002 International Joint Conference on Neural Networks","author":"S Mukkamala","year":"2002","unstructured":"Mukkamala S, Janoski G, Sung A. Intrusion detection using neural networks and support vector machines. In: Proceedings of the 2002 International Joint Conference on Neural Networks. 2002, 1702\u20131707"},{"key":"5116_CR17","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/978-94-007-4786-9_3","volume":"170","author":"H Altwaijry","year":"2012","unstructured":"Altwaijry H. Bayesian based intrusion detection system. Lecture Notes in Electrical Engineering, 2012, 170: 29\u201344","journal-title":"Lecture Notes in Electrical Engineering"},{"issue":"10","key":"5116_CR18","doi-asserted-by":"crossref","first-page":"1699","DOI":"10.1016\/j.jss.2006.12.546","volume":"80","author":"L C Wuu","year":"2007","unstructured":"Wuu L C, Hung C H, Chen S F. Building intrusion pattern miner for Snort network intrusion detection system. Journal of Systems and Software, 2007, 80(10): 1699\u20131715","journal-title":"Journal of Systems and Software"},{"key":"5116_CR19","volume-title":"Elsevier","author":"C Sanders","year":"2013","unstructured":"Sanders C, Smith J. Applied Network Security Monitoring Collection, Detection, and Analysis. Elsevier, 2013"},{"issue":"16","key":"5116_CR20","first-page":"1569","volume":"27","author":"J M Estevez-Tapiador","year":"2004","unstructured":"Estevez-Tapiador J M, Garcia-Teodoro P, Diaz-Verdejo J E. Anomaly detection methods in wired networks: a survey and taxonomy. Computer Networks, 2004, 27(16): 1569\u20131584","journal-title":"Computer Networks"},{"key":"5116_CR21","volume-title":"Data Mining: Challenges and Opportunities for Data Mining During the Next Decade","author":"R L Grossman","year":"1997","unstructured":"Grossman R L. Data Mining: Challenges and Opportunities for Data Mining During the Next Decade, http:\/\/www.lac.uic.edu, 1997"},{"issue":"1","key":"5116_CR22","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4108\/trans.sis.2013.01-03.e2","volume":"13","author":"J Zhang","year":"2013","unstructured":"Zhang J. Advancements of outlier detection: a survey. ICST Transactions on Scalable Information Systems, 2013, 13(1): 1\u201326","journal-title":"ICST Transactions on Scalable Information Systems"},{"key":"5116_CR23","volume-title":"Purves: Statistics","author":"D Freedman","year":"1978","unstructured":"Freedman D, Pisani R. R. Purves: Statistics. New York: Norton & Co., 1978"},{"issue":"1","key":"5116_CR24","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1109\/60.749142","volume":"14","author":"S E Gutt\u00f5rmsson","year":"1999","unstructured":"Gutt\u00f5rmsson S E, Marks R J, El-Sharkawi M A, Kerszenbaum I. Elliptical novelty grouping for on-line short-turn detection of excited running rotors. IEEE Transactions on Energy Conversion, 1999, 14(1): 16\u201322","journal-title":"IEEE Transactions on Energy Conversion"},{"key":"5116_CR25","volume-title":"Proceedings of the 2005 SIAM International Conference on Data Mining","author":"C C Aggarwal","year":"2005","unstructured":"Aggarwal C C. OnAbnormality Detection in Spuriously Populated Data Streams. In: Proceedings of the 2005 SIAM International Conference on Data Mining. 2005"},{"issue":"2","key":"5116_CR26","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1093\/biomet\/66.2.229","volume":"66","author":"B Abraham","year":"1979","unstructured":"Abraham B, Box G E P. Bayesian analysis of some outlier problems in time series. Biometrika, 1979, 66(2): 229\u2013236","journal-title":"Biometrika"},{"key":"5116_CR27","volume-title":"Menio Park, CA: SRI International, Computer Science Laboratory","author":"D Anderson","year":"1995","unstructured":"Anderson D, Frivold T, Valdes A. Next Generation Intrusion Detection Expert System (NIDES): A Summary. Menio Park, CA: SRI International, Computer Science Laboratory, 1995"},{"key":"5116_CR28","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1145\/312129.312195","volume-title":"Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","author":"T Fawcett","year":"1999","unstructured":"Fawcett T, Provost F. Activity monitoring: noticing interesting changes in behavior. In: Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 1999, 53\u201362"},{"issue":"4","key":"5116_CR29","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1049\/ip-vis:19941330","volume":"141","author":"C Bishop","year":"1994","unstructured":"Bishop C. Novelty detection and neural network validation. IEE Proceedings \u2014 Vision, Image and Signal Processing, 1994, 141(4): 217\u2013222","journal-title":"IEE Proceedings \u2014 Vision, Image and Signal Processing"},{"key":"5116_CR30","first-page":"385","volume-title":"Proceedings of the 16th International Conference on Pattern Recognition","author":"D Y Yeung","year":"2002","unstructured":"Yeung D Y, Chow C. Parzen-window network intrusion detectors. In: Proceedings of the 16th International Conference on Pattern Recognition. 2002, 385\u2013388"},{"key":"5116_CR31","first-page":"392","volume-title":"Proceedings of the 24th International Conference on Very Large Data Bases","author":"E M Knorr","year":"1998","unstructured":"Knorr E M, Ng R T. Algorithms for mining distancebased outliers in large datasets. In: Proceedings of the 24th International Conference on Very Large Data Bases. 1998, 392\u2013403"},{"key":"5116_CR32","first-page":"211","volume-title":"Proceedings of the 25th International Conference on Very Large Data Bases","author":"E M Knorr","year":"1999","unstructured":"Knorr E M, Ng R T. Finding Intentional Knowledge of Distance-based Outliers. In: Proceedings of the 25th International Conference on Very Large Data Bases. 1999, 211\u2013222"},{"issue":"3-4","key":"5116_CR33","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1007\/s007780050006","volume":"8","author":"E M Knorr","year":"2000","unstructured":"Knorr E M, Ng R T, Tucakov V. Distance-based outliers: algorithms and applications. The VLDB Journal \u2014 The International Journal on Very Large Data Bases, 2000, 8(3-4): 237\u2013253","journal-title":"The VLDB Journal \u2014 The International Journal on Very Large Data Bases"},{"issue":"2","key":"5116_CR34","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1145\/335191.335437","volume":"29","author":"S Ramaswamy","year":"2000","unstructured":"Ramaswamy S, Rastogi R, Shim K. Efficient algorithms for mining outliers from large data sets. ACM SIGMOD Record, 2000, 29(2): 427\u2013438","journal-title":"ACM SIGMOD Record"},{"issue":"2","key":"5116_CR35","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1145\/335191.335388","volume":"29","author":"MM Breunig","year":"2000","unstructured":"Breunig MM, Kriegel H P, Ng R T, Sander J. LOF: identifying densitybased local outliers. ACM SIGMOD Record, 2000, 29(2): 93\u2013104","journal-title":"ACM SIGMOD Record"},{"key":"5116_CR36","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1145\/1645953.1646195","volume-title":"Proceedings of the 18th ACM conference on Information and knowledge management","author":"H P Kriegel","year":"2009","unstructured":"Kriegel H P, Kr\u00f6ger P, Schubert E, Zimek A. LoOP: Local Outlier Probabilities. Proceedings of the 18th ACM conference on Information and knowledge management. 2009, 1649\u20131652"},{"key":"5116_CR37","first-page":"315","volume-title":"Proceedings of the 19th IEEE International Conference on Data Engineering","author":"S Papadimitriou","year":"2003","unstructured":"Papadimitriou S, Kitagawa H, Gibbons P B, Faloutsos C. LOCI: fast outlier detection using the local correlation integral. In: Proceedings of the 19th IEEE International Conference on Data Engineering. 2003, 315\u2013326"},{"key":"5116_CR38","doi-asserted-by":"crossref","DOI":"10.1002\/9780470316801","volume-title":"Finding Groups in Data: An Introduction to Cluster Analysis","author":"L Kaufman","year":"1990","unstructured":"Kaufman L, Rousseeuw P J. Finding Groups in Data: An Introduction to Cluster Analysis. New York: John Wiley & Sons, 1990"},{"key":"5116_CR39","first-page":"144","volume-title":"Proceedings of the 20th International Conference on Very Large Data Bases","author":"R T Ng","year":"1994","unstructured":"Ng R T, Han J. Efficient and effective clustering methods for spatial data mining. In: Proceedings of the 20th International Conference on Very Large Data Bases. 1994, pp. 144\u2013155"},{"key":"5116_CR40","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1145\/276304.276312","volume-title":"Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data","author":"S Guha","year":"1998","unstructured":"Guha S, Rastogi R, Shim K. CURE: an efficient clustering algorithm for large databases. In: Proceedings of the 1998 ACM SIGMOD International Conference on Management of Data. 1998, 73\u201384"},{"issue":"4","key":"5116_CR41","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1007\/s00778-006-0002-5","volume":"16","author":"L Khan","year":"2007","unstructured":"Khan L, Awad M, Thuraisingham B. A new intrusion detection system using support vector machines and hierarchical clustering. The VLDB Journal \u2014 The International Journal on Very Large Data Bases, 2007, 16(4): 507\u2013521","journal-title":"The VLDB Journal \u2014 The International Journal on Very Large Data Bases"},{"issue":"8","key":"5116_CR42","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1109\/2.781637","volume":"32","author":"G Karypis","year":"1999","unstructured":"Karypis G, Han E H, Kumar V. CHAMELEON: ahierarchical clustering algorithm using dynamic modeling. Computer, 1999, 32(8): 68\u201375","journal-title":"Computer"},{"issue":"3-4","key":"5116_CR43","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1007\/s007780050009","volume":"8","author":"G Sheikholeslami","year":"2000","unstructured":"Sheikholeslami G, Chatterjee S, Zhang A. WaveCluster: a waveletbased clustering approach for spatial data in very large databases. The VLDB Journal\u2014The International Journal on Very Large Data Bases, 2000, 8(3-4): 289\u2013304","journal-title":"The VLDB Journal\u2014The International Journal on Very Large Data Bases"},{"key":"5116_CR44","first-page":"186","volume-title":"Proceedings of the 23rd International Conference on Very Large Data Bases","author":"W Wang","year":"1997","unstructured":"Wang W, Yang J, Muntz R. STING: astatistical information grid approach to spatial data mining. In: Proceedings of the 23rd International Conference on Very Large Data Bases. 1997, 186\u2013195"},{"issue":"1","key":"5116_CR45","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10844-005-0265-0","volume":"24","author":"J Zhang","year":"2005","unstructured":"Zhang J, Hsu W, Lee M L. Clustering in dynamic spatial databases. Journal of Intelligent Information Systems, 2005, 24(1): 5\u201327","journal-title":"Journal of Intelligent Information Systems"},{"key":"5116_CR46","doi-asserted-by":"crossref","first-page":"74","DOI":"10.3115\/1705415.1705425","volume-title":"Proceedings of the Workshop on Geometrical Models of Natural Language Semantics","author":"A lachos","year":"2009","unstructured":"lachos A, Korhonen A, Ghahramani Z. Unsupervised and constrained Dirichlet process mixture models for verb clustering. In: Proceedings of the Workshop on Geometrical Models of Natural Language Semantics. 2009, 74\u201382"},{"key":"5116_CR47","doi-asserted-by":"crossref","first-page":"364","DOI":"10.1007\/978-3-642-41299-8_35","volume":"8171","author":"W Fan","year":"2013","unstructured":"Fan W, Bouguila N, Sallay H. Anomaly intrusion detection using incremental learning of an infinite mixture model with feature selection. Lecture Notes in Computer Science, 2013, 8171: 364\u2013373","journal-title":"Lecture Notes in Computer Science"},{"key":"5116_CR48","volume-title":"Technical Report","author":"A R Vasudevan","year":"2013","unstructured":"Vasudevan, A. R, Selvakumar S. Evolution of a hybrid model using Dirichlet process clustering technique and naive Bayes cassifier for an effective perimeter security device. Technical Report. 2013"},{"key":"5116_CR49","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1137\/1.9781611972733.3","volume-title":"Proceedings of the 2003 SIAM International Conference on Data Mining","author":"A Lazarevic","year":"2003","unstructured":"Lazarevic A, Ert\u00f6z L, Kumar V, Ozgur A, Srivastava J. A comparative study of anomaly detection schemes in network intrusion detection. In: Proceedings of the 2003 SIAM International Conference on Data Mining. 2003, 25\u201336"},{"issue":"1","key":"5116_CR50","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1145\/2594473.2594476","volume":"15","author":"A Zimek","year":"2013","unstructured":"Zimek A, Campello R J G B, Sander J. Ensembles for unsupervised outlier detection: challenges and research questions a position paper. ACM SIGKDD Explorations Newsletter, 2013, 15(1): 11\u201322","journal-title":"ACM SIGKDD Explorations Newsletter"},{"issue":"4","key":"5116_CR51","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TKDE.2012.35","volume":"25","author":"S Garcia","year":"2013","unstructured":"Garcia S, Luengo J, S\u00e1ez J A, L\u00f3pez V, Herrera F. A survey of discretization techniques: Taxonomy and empirical analysis in supervised learning. IEEE Transactions on Knowledge and Data Engineering, 2013, 25(4): 734\u2013750","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"key":"5116_CR52","first-page":"1022","volume-title":"Proceedings of the 13th International Joint Conference on Artificial Intelligence","author":"U M Fayyad","year":"1993","unstructured":"Fayyad U M, Irani K B. Multi-interval discretization of continuousvalued attributes for classification learning. In: Proceedings of the 13th International Joint Conference on Artificial Intelligence. 1993, 1022\u20131027"},{"key":"5116_CR53","first-page":"194","volume-title":"Proceedings of the 12th International Conference on Machine Learning","author":"J Dougherty","year":"1995","unstructured":"Dougherty J, Kohavi R, Sahami M. Supervised and unsupervised discretization of continuous features. In: Proceedings of the 12th International Conference on Machine Learning. 1995, 194\u2013202"},{"key":"5116_CR54","first-page":"797","volume-title":"Proceedings of World Congress on Neural Networks","author":"M M Moya","year":"1993","unstructured":"Moya M M, Koch M W, Hostetler L D. One-class classifier networks for target recognition applications. In: Proceedings of World Congress on Neural Networks, 1993, 797\u2013801"},{"key":"5116_CR55","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1007\/3-540-48219-9_30","volume":"2096","author":"DMJ Tax","year":"2001","unstructured":"Tax DMJ, Duin R P W. Combining one-class classifiers. Lecture Notes in Computer Science, 2001, 2096: 299\u2013308","journal-title":"Lecture Notes in Computer Science"},{"key":"5116_CR56","volume-title":"Dissertation for the Doctoral Degree. Delft: Delft University of Technology","author":"D M J Tax","year":"2001","unstructured":"Tax D M J. One-class classification, concept learning in the absence of counter examples. Dissertation for the Doctoral Degree. Delft: Delft University of Technology, 2001"},{"key":"5116_CR57","first-page":"29","volume":"36","author":"O Mazhelis","year":"2006","unstructured":"Mazhelis O. One-class classifiers: a review and analysis of suitability in the context of mobile-masquerader detection. South African Computer Journal, 2006, 36: 29\u201348","journal-title":"South African Computer Journal"},{"key":"5116_CR58","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1007\/978-3-540-87479-9_51","volume":"5211","author":"K Hempstalk","year":"2008","unstructured":"Hempstalk K, Frank E, Witten I H. One-class classification by combining density and class probability estimation. Lecture Notes in Computer Science, 2008, 5211: 505\u2013519","journal-title":"Lecture Notes in Computer Science"},{"issue":"1","key":"5116_CR59","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.inffus.2006.10.002","volume":"9","author":"G Giacinto","year":"2008","unstructured":"Giacinto G, Perdisci R, Del Rio M, Roli F. Intrusion detection in computer networks by a modular ensemble of one-class classifiers. Information Fusion, 2008, 9(1): 69\u201382","journal-title":"Information Fusion"},{"key":"5116_CR60","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/AHICI.2011.6113948","volume-title":"Proceedings of the 2nd IEEE Asian Himalayas International Conference on Internet (AH-ICI 2011)","author":"A R Vasudevan","year":"2011","unstructured":"Vasudevan A R, Harshini E, Selvakumar S. SSENet-2011: a network intrusion detection system dataset and its comparison with KDD CUP 99 dataset. In: Proceedings of the 2nd IEEE Asian Himalayas International Conference on Internet (AH-ICI 2011). 2011, 1\u20135"}],"container-title":["Frontiers of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-015-5116-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11704-015-5116-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-015-5116-8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,18]],"date-time":"2022-06-18T02:39:54Z","timestamp":1655519994000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11704-015-5116-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,4,18]]},"references-count":60,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2016,8]]}},"alternative-id":["5116"],"URL":"https:\/\/doi.org\/10.1007\/s11704-015-5116-8","relation":{},"ISSN":["2095-2228","2095-2236"],"issn-type":[{"value":"2095-2228","type":"print"},{"value":"2095-2236","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,4,18]]}}}