{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,28]],"date-time":"2025-09-28T04:21:22Z","timestamp":1759033282576,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030004330"},{"type":"electronic","value":"9783030004347"}],"license":[{"start":{"date-parts":[[2018,8,15]],"date-time":"2018-08-15T00:00:00Z","timestamp":1534291200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-319-98678-4_21","type":"book-chapter","created":{"date-parts":[[2018,8,14]],"date-time":"2018-08-14T09:25:31Z","timestamp":1534238731000},"page":"190-200","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intrusion Detection and Risk Evaluation in Online Transactions Using Partitioning Methods"],"prefix":"10.1007","author":[{"given":"Hossein","family":"Yazdani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazimierz","family":"Choro\u015b","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,8,15]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Edge, K., Raines, R., Grimaila, M., Baldwin, R., Bennington, R., Reuter, C.: The use of attack and protection trees to analyze security for an online banking system. In: Proceedings of the Annual Hawaii International Conference on System Sciences, p. 144b. IEEE (2007)","key":"21_CR1","DOI":"10.1109\/HICSS.2007.558"},{"unstructured":"Chio, C., Freeman, D.: Machine Learning and Security. O\u2019Reilly (2017)","key":"21_CR2"},{"issue":"2","key":"21_CR3","doi-asserted-by":"publisher","first-page":"1153","DOI":"10.1109\/COMST.2015.2494502","volume":"18","author":"AL Buczak","year":"2016","unstructured":"Buczak, A.L., Guven, E.: A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Commun. Surv. Tutorials 18(2), 1153\u20131176 (2016)","journal-title":"IEEE Commun. Surv. Tutorials"},{"unstructured":"Hoppner, F.: Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition. Wiley (1999)","key":"21_CR4"},{"issue":"2","key":"21_CR5","doi-asserted-by":"publisher","first-page":"248","DOI":"10.1109\/TPAMI.1986.4767778","volume":"PAMI\u20138","author":"RL Cannon","year":"1986","unstructured":"Cannon, R.L., Dave, J.V., Bazdek, J.C.: Efficient implementation of the fuzzy c-means clustering algorithms. IEEE Trans. Patt. Anal. Mach. Intell. PAMI\u20138(2), 248\u2013255 (1986)","journal-title":"IEEE Trans. Patt. Anal. Mach. Intell."},{"issue":"5","key":"21_CR6","doi-asserted-by":"publisher","first-page":"906","DOI":"10.1109\/TFUZZ.2010.2052258","volume":"18","author":"DT Anderson","year":"2010","unstructured":"Anderson, D.T., Bezdek, J.C., Popescu, M., Keller, J.M.: Comparing fuzzy, probabilistic, and possibilistic partitions. IEEE Trans. Fuzzy Syst. 18(5), 906\u2013918 (2010)","journal-title":"IEEE Trans. Fuzzy Syst."},{"doi-asserted-by":"crossref","unstructured":"Yazdani, H.: Fuzzy possibilistic on different search spaces. In: Proceedings of the International Symposium on Computational Intelligence and Informatics, pp. 283\u2013288. IEEE (2016)","key":"21_CR7","DOI":"10.1109\/CINTI.2016.7846419"},{"doi-asserted-by":"crossref","unstructured":"Cao, B., Fan, Q.: The infrastructure and security management of mobile banking system. In: IEEE International Conference on E-Service and E-Entertainment, pp. 1\u20133 (2010)","key":"21_CR8","DOI":"10.1109\/ICEEE.2010.5660994"},{"issue":"19","key":"21_CR9","first-page":"57","volume":"60","author":"S Paliwal","year":"2012","unstructured":"Paliwal, S., Gupta, R.: Denial-of-Service, probing and remote to user (R2L) attack detection using genetic algorithm. Int. J. Comput. Appl. 60(19), 57\u201362 (2012)","journal-title":"Int. J. Comput. Appl."},{"issue":"18","key":"21_CR10","doi-asserted-by":"publisher","first-page":"3799","DOI":"10.1016\/j.ins.2007.03.025","volume":"177","author":"T Shon","year":"2007","unstructured":"Shon, T., Moon, J.: A hybrid machine learning approach to network anomaly detection. J. Inf. Sci. 177(18), 3799\u20133821 (2007)","journal-title":"J. Inf. Sci."},{"issue":"10","key":"21_CR11","doi-asserted-by":"publisher","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":"21_CR12","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.jnca.2015.11.016","volume":"60","author":"M Ahmed","year":"2016","unstructured":"Ahmed, M., Mahmood, A., Hu, J.: A survey of network anomaly detection techniques. J. Netw. Comput. Appl. 60, 19\u201331 (2016)","journal-title":"J. Netw. Comput. Appl."},{"key":"21_CR13","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1016\/j.ins.2016.04.019","volume":"378","author":"R Aamir","year":"2017","unstructured":"Aamir, R., Ashfaq, R., Wang, X.Z., Huang, J.Z., Abbas, H., He, Y.L.: Fuzziness based semi-supervised learning approach for intrusion detection system. J. Inf. Sci. 378, 484\u2013497 (2017)","journal-title":"J. Inf. Sci."},{"issue":"6","key":"21_CR14","doi-asserted-by":"publisher","first-page":"1443","DOI":"10.1109\/TFUZZ.2013.2294205","volume":"22","author":"J Zhou","year":"2014","unstructured":"Zhou, J., Chen, C.L.P., Chen, L., Li, H.X.: A collaborative fuzzy clustering algorithm in distributed network environments. IEEE Trans. Fuzzy Syst. 22(6), 1443\u20131456 (2014)","journal-title":"IEEE Trans. Fuzzy Syst."},{"doi-asserted-by":"crossref","unstructured":"Masduki, B.W., Ramli, K., Saputra, F.A., Sugiarto, D.: Study on implementation of machine learning methods combination for improving attacks detection accuracy on intrusion detection systems (IDS). In: International Conference on Quality in Research, pp. 56\u201364. IEEE (2015)","key":"21_CR15","DOI":"10.1109\/QiR.2015.7374895"},{"issue":"21","key":"21_CR16","first-page":"28","volume":"45","author":"PG Jeya","year":"2012","unstructured":"Jeya, P.G., Ravichandran, M., Ravichandran, C.S.: Efficient classifier for R2L and U2R attacks. Int. J. Comput. Appl. 45(21), 28\u201332 (2012)","journal-title":"Int. J. Comput. Appl."},{"doi-asserted-by":"crossref","unstructured":"Kiljan, S., Eekelen, M.V., Vranken, H.: Towards a virtual bank for evaluating security aspects with focus on user behavior. In: SAI Computing Conference, pp. 1068\u20131075. IEEE (2016)","key":"21_CR17","DOI":"10.1109\/SAI.2016.7556110"},{"doi-asserted-by":"crossref","unstructured":"Yazdani, H., Ortiz-Arroyo, D., Choro\u015b, K., Kwa\u015bnicka, H.: Applying bounded fuzzy possibilistic method on critical objects. In: Proceedings of the International Symposium on Computational Intelligence and Informatics, pp. 271\u2013276. IEEE (2016)","key":"21_CR18","DOI":"10.1109\/CINTI.2016.7846417"},{"doi-asserted-by":"crossref","unstructured":"Yazdani, H., Kwa\u015bnicka, H.: Fuzzy classification method in credit risk. In: Proceedings of the International Conference on Computational Collective Intelligence. Lecture Notes in Computer Science, vol. 7653, pp. 495\u2013505. Springer (2012)","key":"21_CR19","DOI":"10.1007\/978-3-642-34630-9_51"},{"doi-asserted-by":"crossref","unstructured":"Yazdani, H., Ortiz-Arroyo, D., Choro\u015b, K., Kwa\u015bnicka, H.: On high dimensional searching space and learning methods. In: Data Science and Big Data: An Environment of Computational Intelligence, pp. 29\u201348. Springer (2016)","key":"21_CR20","DOI":"10.1007\/978-3-319-53474-9_2"}],"container-title":["Lecture Notes in Computer Science","Cryptology and Network Security"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-98678-4_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,22]],"date-time":"2019-10-22T04:45:14Z","timestamp":1571719514000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-98678-4_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,8,15]]},"ISBN":["9783030004330","9783030004347"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-98678-4_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018,8,15]]}}}