{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T13:42:32Z","timestamp":1773236552284,"version":"3.50.1"},"publisher-location":"Berlin, Heidelberg","reference-count":17,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"value":"9783540362975","type":"print"},{"value":"9783540362999","type":"electronic"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2006]]},"DOI":"10.1007\/11795131_78","type":"book-chapter","created":{"date-parts":[[2006,9,26]],"date-time":"2006-09-26T11:48:02Z","timestamp":1159271282000},"page":"538-543","source":"Crossref","is-referenced-by-count":35,"title":["An Enhanced Support Vector Machine Model for Intrusion Detection"],"prefix":"10.1007","author":[{"given":"JingTao","family":"Yao","sequence":"first","affiliation":[]},{"given":"Songlun","family":"Zhao","sequence":"additional","affiliation":[]},{"given":"Lisa","family":"Fan","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"78_CR1","doi-asserted-by":"crossref","unstructured":"Bace, R.G.: Intrusion Detection. Macmillan Technical Publishing (2000)","DOI":"10.6028\/NIST.SP.800-31"},{"key":"78_CR2","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1023\/A:1009715923555","volume":"2","author":"C. Burge","year":"1998","unstructured":"Burge, C.: A Tutorial on Support Vector Machines for Pattern Recognition. Data mining and knowledge discovery journal\u00a02, 121\u2013167 (1998)","journal-title":"Data mining and knowledge discovery journal"},{"key":"78_CR3","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1016\/j.inffus.2003.08.003","volume":"4","author":"B.V. Dasarathy","year":"2003","unstructured":"Dasarathy, B.V.: Intrusion detection. Information Fusion\u00a04, 243\u2013245 (2003)","journal-title":"Information Fusion"},{"key":"78_CR4","volume-title":"Information Retrieval: Data Structures and Algorithms","author":"W.B. Frakes","year":"1992","unstructured":"Frakes, W.B., Baeza-Yates, R., Ricardo, B.Y.: Information Retrieval: Data Structures and Algorithms. Prentice-Hall, Englewood Cliffs (1992)"},{"key":"78_CR5","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"214","DOI":"10.1007\/11548669_23","volume-title":"Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing","author":"J.C. Han","year":"2005","unstructured":"Han, J.C., Sanchez, R., Hu, X.H.: Feature Selection Based on Relative Attribute Dependency: An Experimental Study. In: \u015al\u0119zak, D., Wang, G., Szczuka, M., D\u00fcntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol.\u00a03641, pp. 214\u2013223. Springer, Heidelberg (2005)"},{"key":"78_CR6","first-page":"41","volume":"16","author":"K. Hu","year":"2003","unstructured":"Hu, K., Lu, Y., Shi, C.: Feature Ranking in Rough Sets. AI Communications\u00a016, 41\u201350 (2003)","journal-title":"AI Communications"},{"key":"78_CR7","volume-title":"Making large-Scale SVM Learning Practical, Advances in Kernel Methods - Support Vector Learning","author":"T. Joachims","year":"1999","unstructured":"Joachims, T.: Making large-Scale SVM Learning Practical, Advances in Kernel Methods - Support Vector Learning. MIT Press, Cambridge (1999)"},{"key":"78_CR8","doi-asserted-by":"crossref","unstructured":"John, G.H., Kohavi, R., Pfleger, K.: Irrelevant features and the subset selection problem. In: Proc. of the 11th Int. Conf. on Machine Learning, pp. 121\u2013129 (1994)","DOI":"10.1016\/B978-1-55860-335-6.50023-4"},{"key":"78_CR9","unstructured":"Lee, W., Stolfo, S.J.: Data Mining Approaches for Intrusion Detection. In: The 7th USENIX Security Symposium, pp. 79\u201394 (1998)"},{"key":"78_CR10","doi-asserted-by":"crossref","unstructured":"Mohajerani, M., Moeini, A., Kianie, M.: NFIDS: A Neuro-fuzzy Intrusion Detection System. In: Proc. of the 10th IEEE Int. Conf. on Electronics, Circuits and Systems, pp. 348\u2013351 (2003)","DOI":"10.1109\/ICECS.2003.1302048"},{"key":"78_CR11","first-page":"89","volume":"11","author":"Z. Pawlak","year":"1995","unstructured":"Pawlak, Z., Grzymala-Busse, J., Slowinski, R., Ziarko, W.: Rough Set. Communications of the ACM\u00a011, 89\u201395 (1995)","journal-title":"Communications of the ACM"},{"key":"78_CR12","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1049\/el:20020467","volume":"13","author":"Y. Qiao","year":"2002","unstructured":"Qiao, Y., Xin, X.W., Bin, Y., Ge, S.: Anomaly Intrusion Detection Method Based on HMM. Electronics Letters\u00a013, 663\u2013664 (2002)","journal-title":"Electronics Letters"},{"key":"78_CR13","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The Nature of Statistical Learning Theory","author":"V.N. Vapnik","year":"1995","unstructured":"Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Heidelberg (1995)"},{"key":"78_CR14","unstructured":"Wang, W.D., Bridges, S.: Genetic Algorithm Optimization of Membership Functions for Mining Fuzzy Association Rules. In: Proc. of the 7th Int. Conf. on Fuzzy Theory & Technology, pp. 131\u2013134 (2000)"},{"key":"78_CR15","doi-asserted-by":"crossref","unstructured":"Warrender, C., Forrest, S., Pearlmutter, B.: Detecting Intrusions Using System Calls: Alternative Data Models. In: Proc. of the IEEE Symposium on Security and Privacy, pp. 133\u2013145 (1999)","DOI":"10.1109\/SECPRI.1999.766910"},{"key":"78_CR16","series-title":"Lecture Notes in Artificial Intelligence","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1007\/11548669_22","volume-title":"Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing","author":"J.T. Yao","year":"2005","unstructured":"Yao, J.T., Zhang, M.: Feature Selection with Adjustable Criteria. In: \u015al\u0119zak, D., Wang, G., Szczuka, M., D\u00fcntsch, I., Yao, Y. (eds.) RSFDGrC 2005. LNCS (LNAI), vol.\u00a03641, pp. 204\u2013213. Springer, Heidelberg (2005)"},{"key":"78_CR17","doi-asserted-by":"crossref","unstructured":"Yao, J.T., Zhao, S.L., Saxton, L.V.: A study on Fuzzy Intrusion Detection. In: Proc. of Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security. SPIE, vol.\u00a05812, pp. 23\u201330 (2005)","DOI":"10.1117\/12.604465"}],"container-title":["Lecture Notes in Computer Science","Rough Sets and Knowledge Technology"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/11795131_78.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T15:10:41Z","timestamp":1605625841000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/11795131_78"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006]]},"ISBN":["9783540362975","9783540362999"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/11795131_78","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2006]]}}}