{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T22:19:40Z","timestamp":1769725180704,"version":"3.49.0"},"publisher-location":"Cham","reference-count":10,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030493417","type":"print"},{"value":"9783030493424","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,8,15]],"date-time":"2020-08-15T00:00:00Z","timestamp":1597449600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,8,15]],"date-time":"2020-08-15T00:00:00Z","timestamp":1597449600000},"content-version":"vor","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":[[2021]]},"DOI":"10.1007\/978-3-030-49342-4_3","type":"book-chapter","created":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T11:49:30Z","timestamp":1597405770000},"page":"24-34","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Dataset for Intrusion Detection in Mobile Ad-Hoc Networks"],"prefix":"10.1007","author":[{"given":"Rahma","family":"Meddeb","sequence":"first","affiliation":[]},{"given":"Bayrem","family":"Triki","sequence":"additional","affiliation":[]},{"given":"Farah","family":"Jemili","sequence":"additional","affiliation":[]},{"given":"Ouajdi","family":"Korbaa","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,8,15]]},"reference":[{"key":"3_CR1","doi-asserted-by":"crossref","unstructured":"Meddeb, R., Triki, B., Jemili, F., Korbaa, O.: A survey of attacks in mobile ad hoc networks. In: ICEMIS2017, pp. 1\u20136, Monastir (2017)","DOI":"10.1109\/ICEMIS.2017.8273007"},{"key":"3_CR2","doi-asserted-by":"crossref","unstructured":"Gaied, I., Jemili, F., Korbaa, O.: Intrusion detection based on neuro-fuzzy classification. In: 2015 IEEE\/ACS 12th International Conference of Computer Systems and Applications (AICCSA), pp. 1\u20138. IEEE (2015)","DOI":"10.1109\/AICCSA.2015.7507112"},{"key":"3_CR3","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.cose.2019.06.005","volume":"86","author":"M Ring","year":"2019","unstructured":"Ring, M., Wunderlich, S., Scheuring, D., Landes, D., Hotho, A.: A survey of networkbased intrusion detection data sets. Comput. Secur. 86, 147\u2013167 (2019)","journal-title":"Comput. Secur."},{"key":"3_CR4","doi-asserted-by":"crossref","unstructured":"Jyothsna, V., Prasad, K.M.: Anomaly-based intrusion detection system. In: Computer and Network Security, IntechOpen (2019)","DOI":"10.5772\/intechopen.82287"},{"key":"3_CR5","unstructured":"Ma lowidzki, M., Berezinski, P., Mazur, M.: Network intrusion detection: half a kingdom for a good dataset. In: NATO STO SAS-139 Workshop, Portugal (2015)"},{"key":"3_CR6","unstructured":"Glass-Vanderlan, T.R., Iannacone, M.D., Vincent, M.S., Bridges, R.A., et al.: A survey of intrusion detection systems leveraging host data. arXiv preprint \narXiv:1805.06070\n\n (2018)"},{"key":"3_CR7","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.jnca.2017.03.018","volume":"87","author":"W Haider","year":"2017","unstructured":"Haider, W., Hu, J., Slay, J., Turnbull, B.P., Xie, Y.: Generating realistic intrusion detection system dataset based on fuzzy qualitative modeling. J. Netw. Comput. Appl. 87, 185\u2013192 (2017)","journal-title":"J. Netw. Comput. Appl."},{"key":"3_CR8","doi-asserted-by":"crossref","unstructured":"Meddeb, R., Triki, B., Jemili, F., Korbaa, O.: An effective IDS against routing attacks on mobile ad-hoc networks. In: New Trends in Intelligent Software Methodologies, Tools and Techniques, vol. 297, pp. 201-214. IOS Press (2018)","DOI":"10.1109\/ICEMIS.2017.8273007"},{"key":"3_CR9","doi-asserted-by":"crossref","unstructured":"Verma, N.K., Singh, V., Rajurkar, S., Aqib, M.: Fuzzy inference network with Mamdani fuzzy inference system. In: Computational Intelligence: Theories, Applications and Future Directions, vol. I, pp. 375\u2013388. Springer (2019)","DOI":"10.1007\/978-981-13-1132-1_29"},{"key":"3_CR10","unstructured":"Swathi, D., Lakshmi, D.S.: Network intrusion detection using fast k-nearest neighbor classifier. In: UGC Sponsored National Seminar On Cyber Security With Special Focus On Cyber Crimes & Cyber Laws (NSCS-2014) (2014)"}],"container-title":["Advances in Intelligent Systems and Computing","Intelligent Systems Design and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-49342-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T11:52:07Z","timestamp":1597405927000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-49342-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,15]]},"ISBN":["9783030493417","9783030493424"],"references-count":10,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-49342-4_3","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"value":"2194-5357","type":"print"},{"value":"2194-5365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,8,15]]},"assertion":[{"value":"15 August 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ISDA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Systems Design and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Auburn, WA","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"19","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"isda2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.mirlabs.net\/isda19\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}