{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,12]],"date-time":"2025-11-12T13:41:25Z","timestamp":1762954885795},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2010,2,7]],"date-time":"2010-02-07T00:00:00Z","timestamp":1265500800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genet Program Evolvable Mach"],"published-print":{"date-parts":[[2010,6]]},"DOI":"10.1007\/s10710-010-9101-6","type":"journal-article","created":{"date-parts":[[2010,2,6]],"date-time":"2010-02-06T03:50:57Z","timestamp":1265428257000},"page":"131-146","source":"Crossref","is-referenced-by-count":26,"title":["An ensemble-based evolutionary framework for coping with distributed intrusion detection"],"prefix":"10.1007","volume":"11","author":[{"given":"Gianluigi","family":"Folino","sequence":"first","affiliation":[]},{"given":"Clara","family":"Pizzuti","sequence":"additional","affiliation":[]},{"given":"Giandomenico","family":"Spezzano","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2010,2,7]]},"reference":[{"issue":"3","key":"9101_CR2","first-page":"328","volume":"4","author":"A. Abraham","year":"2007","unstructured":"A. Abraham, C. Grosan, C. Martin-Vide, Evolutionary design of intrusion detection programs. Int. J. Netw. Secur. 4(3), 328\u2013339 (2007)","journal-title":"Int. J. Netw. Secur."},{"issue":"5","key":"9101_CR3","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1109\/TEVC.2002.800880","volume":"6","author":"E. Alba","year":"2002","unstructured":"E. Alba, M. Tomassini, Parallelism and evolutionary algorithms. IEEE Trans. Evol. Comput. 6(5), 443\u2013462 (2002)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"9101_CR4","doi-asserted-by":"crossref","unstructured":"D. Barbara, N. Wu, S. Jajodia, Detecting novel network intrusions using bayes estimator. In First SIAM Conference on Data Mining (2001)","DOI":"10.1137\/1.9781611972719.28"},{"issue":"7","key":"9101_CR5","doi-asserted-by":"crossref","first-page":"1145","DOI":"10.1016\/S0031-3203(96)00142-2","volume":"30","author":"A.P. Bradley","year":"1997","unstructured":"A.P. Bradley, The use of the area under the roc curve in the evaluation of machine learning algorithms. Pattern Recognit. 30(7), 1145\u20131159 (1997)","journal-title":"Pattern Recognit."},{"issue":"2","key":"9101_CR6","first-page":"123","volume":"24","author":"L. Breiman","year":"1996","unstructured":"L. Breiman, Bagging predictors. Mach. Learn. 24(2), 123\u2013140 (1996)","journal-title":"Mach. Learn."},{"key":"9101_CR7","unstructured":"M. Crosbie, G. Spafford, Applying genetic programming techniques to intrusion detection. In Proceedings of the AAAI Fall Symposium Series (AAAI Press, Nov 1995)"},{"key":"9101_CR8","unstructured":"N. Einwechter, An Introduction to Distributed Intrusion Detection Systems. in http:\/\/www.securityfocus.com\/infocus\/1532 (2002)"},{"key":"9101_CR9","doi-asserted-by":"crossref","unstructured":"E. Eskin, A. Arnold, M. Prerau, L. Portnoy, S. Stolfo, A geometric framework for unsupervised anomaly detection: Detecting intrusions in unlabeled data. In Applications of Data Mining in Computer Security (Kluwer, 2002)","DOI":"10.1007\/978-1-4615-0953-0_4"},{"issue":"1","key":"9101_CR10","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1142\/S1469026806001812","volume":"6","author":"K. Faraoun","year":"2006","unstructured":"K. Faraoun, A. Boukelif, Genetic programming approach for multi-category pattern classification applied to network intrusions detection. Int. J. Comput. Intell. Appl. 6(1), 77\u201399 (2006)","journal-title":"Int. J. Comput. Intell. Appl."},{"issue":"1","key":"9101_CR11","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1109\/TEVC.2002.806168","volume":"7","author":"G. Folino","year":"2003","unstructured":"G. Folino, C. Pizzuti, G. Spezzano, A scalable cellular implementation of parallel genetic programming. IEEE Trans. Evol. Comput. 7(1), 37\u201353 (2003)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"9101_CR12","doi-asserted-by":"crossref","unstructured":"G. Folino, C. Pizzuti, G. Spezzano, GP ensemble for distributed intrusion detection systems. In ICAPR 2005, Proceedings of the 3rd International Conference on Advanced in Pattern Recognition (2005), pp. 54\u201362","DOI":"10.1007\/11551188_6"},{"issue":"5","key":"9101_CR13","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1109\/TEVC.2005.863627","volume":"10","author":"G. Folino","year":"2006","unstructured":"G. Folino, C. Pizzuti, G. Spezzano, GP ensembles for large scale data classification. IEEE Trans. Evol. Comput. 10(5), 604\u2013616 (2006)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"9101_CR14","unstructured":"Y. Freund, R. Schapire, Experiments with a new boosting algorithm. In Proceedings of the 13th International Conference on Machine Learning (1996), pp. 148\u2013156"},{"issue":"4","key":"9101_CR15","doi-asserted-by":"crossref","first-page":"1362","DOI":"10.1016\/j.dss.2006.04.004","volume":"43","author":"J.V. Hansen","year":"2007","unstructured":"J.V. Hansen, P.B. Lowry, R.D. Meservy, D.M. McDonald, Genetic programming for prevention of cyberterrorism through dynamic and evolving intrusion detection. Decis. Support Syst. 43(4), 1362\u20131374 (2007)","journal-title":"Decis. Support Syst."},{"key":"9101_CR16","doi-asserted-by":"crossref","unstructured":"A. Lazarevic, L. Ertoz, V. Kumar, A. Ozgur, J. Srivastava, A comparative study of anomaly detection schemes in network intrusion detection. In Proceedings of the SIAM International Conference on Data Mining (SIAM-03) (2003)","DOI":"10.1137\/1.9781611972733.3"},{"key":"9101_CR17","unstructured":"W. Lee, S.J. Stolfo, Data mining approaches for intrusion detection. In Proceedings of the 1998 USENIX Security Symposium (1998), pp. 66\u201372"},{"key":"9101_CR18","unstructured":"R.P. Lippmann, D.J. Fried, I.Graf, J.W. Haines, K.R. Kendall, D. Mcclung, D. Weber, S.E. Webster, D. Wyschogrod, R.K. Cunningham, M.A. Zissman, Evaluating intrusion detection systems: The 1998 darpa off-line intrusion detection evaluation. In Proceedings of the 2000 DARPA Information Survivability Conference and Exposition (2000), pp. 12\u201326"},{"key":"9101_CR19","unstructured":"W. Lu, I. Traor\u00e9, Detecting new forms of network intrusion using genetic programming. In Proceedings of the Congress on Evolutionary Computation CEC\u20192003 (IEEE Press, 2003), pp. 2165\u20132173"},{"issue":"4","key":"9101_CR20","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1145\/382912.382923","volume":"3","author":"J. McHugh","year":"2000","unstructured":"J. McHugh, Testing intrusion detection systems: a critique of the 1988 and 1999 darpa intrusion detection system evaluations as performed by lincoln laboratory. ACM Trans. Inf. Syst. Secur. 3(4), 262\u2013294 (2000)","journal-title":"ACM Trans. Inf. Syst. Secur."},{"key":"9101_CR21","doi-asserted-by":"crossref","unstructured":"S. Mukkamala, A.H. Sung, A.Abraham, Modeling intrusion detection systems using linear genetic programming approach. In 17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA\/AIE 2004 (Ottawa, Canada, 2004), pp. 633\u2013642","DOI":"10.1007\/978-3-540-24677-0_65"},{"key":"9101_CR22","doi-asserted-by":"crossref","unstructured":"A. Orfila, J.M. Estevez-Tapiador, A. Ribagorda, Evolving high-speed, easy-to-understand network intrusion detection rules with genetic programming. In EvoWorkshops \u201909: Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing (Springer, Berlin, Heidelberg, 2009), pp. 93\u201398","DOI":"10.1007\/978-3-642-01129-0_11"},{"key":"9101_CR23","unstructured":"S. Peddabachigari, A. Abraham, C. Grosan, J. Thomas, Modeling intrusion detection system using hybrid intelligent systems. Int. J. Netw. Comput. Appl. 30, 114\u2013132 (2007)"},{"key":"9101_CR24","unstructured":"F. Provost, T. Fawcett, R. Kohavi, The case against accuracy estimation for comparing induction algorithms. In Proceedings of International Conference on Machine Learning (ICML\u201998) (1998)"},{"key":"9101_CR25","unstructured":"J.R. Quinlan, Bagging, boosting, and C4.5. In Proceedings of the 13th National Conference on Artificial Intelligence AAAI96 (Mit Press, 1996), pp. 725\u2013730"},{"issue":"2","key":"9101_CR26","first-page":"197","volume":"5","author":"R.E. Schapire","year":"1990","unstructured":"R.E. Schapire, The strength of weak learnability. Mach. Learn. 5(2), 197\u2013227 (1990)","journal-title":"Mach. Learn."},{"issue":"2","key":"9101_CR27","first-page":"256","volume":"121","author":"R.E. Schapire","year":"1996","unstructured":"R.E. Schapire, Boosting a weak learning by maiority. Inf. Comput. 121(2), 256\u2013285 (1996)","journal-title":"Inf. Comput."},{"key":"9101_CR28","doi-asserted-by":"crossref","unstructured":"D. Song, M.I. Heywood, A. Nur Zincir-Heywood, A linear genetic programming approach to intrusion detection. In Proceedings of the Genetic and Evolutionary Computation Conference GECCO 2003 (LNCS 2724, Springer, 2003), pp. 2325\u20132336","DOI":"10.1007\/3-540-45110-2_125"},{"issue":"3","key":"9101_CR29","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1109\/TEVC.2004.841683","volume":"9","author":"D. Song","year":"2005","unstructured":"D. Song, M.I. Heywood, A.N. Zincir-Heywood, Training genetic programming on half a millio patterns: An example from anomaly detection. IEEE Trans. Evol. Comput. 9(3), 225\u2013239 (2005)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"9101_CR1","unstructured":"The third international knowledge discovery and data mining tools competition dataset kdd99-cup, in http:\/\/www.kdd.ics.uci.edu\/databases\/kddcup99\/kddcup99.html (1999)"},{"key":"9101_CR30","volume-title":"Data Mining: Practical machine learning tools and techniques, 2nd edn","author":"I.H. Witten","year":"2005","unstructured":"I.H. Witten, E. Frank, Data Mining: Practical machine learning tools and techniques, 2nd edn. (Morgan Kaufmann, San Francisco, 2005)"}],"container-title":["Genetic Programming and Evolvable Machines"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10710-010-9101-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10710-010-9101-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10710-010-9101-6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T22:22:05Z","timestamp":1559254925000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10710-010-9101-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2010,2,7]]},"references-count":30,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2010,6]]}},"alternative-id":["9101"],"URL":"https:\/\/doi.org\/10.1007\/s10710-010-9101-6","relation":{},"ISSN":["1389-2576","1573-7632"],"issn-type":[{"value":"1389-2576","type":"print"},{"value":"1573-7632","type":"electronic"}],"subject":[],"published":{"date-parts":[[2010,2,7]]}}}