{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:54:53Z","timestamp":1775145293907,"version":"3.50.1"},"publisher-location":"Cham","reference-count":30,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031290558","type":"print"},{"value":"9783031290565","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-29056-5_39","type":"book-chapter","created":{"date-parts":[[2023,3,19]],"date-time":"2023-03-19T15:02:23Z","timestamp":1679238143000},"page":"446-459","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Micro IDS: On-Line Recognition of\u00a0Denial-of-Service Attacks on\u00a0IoT Networks"],"prefix":"10.1007","author":[{"given":"Henrique Fell","family":"Lautert","sequence":"first","affiliation":[]},{"given":"Douglas D. J. de","family":"Macedo","sequence":"additional","affiliation":[]},{"given":"La\u00e9rcio","family":"Pioli","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,3,20]]},"reference":[{"key":"39_CR1","unstructured":"Hasan, M.: State of IoT 2022: Number of connected IoT devices growing 18% to 14.4 billion globally (2022). https:\/\/iot-analytics.com\/number-connected-iot-devices\/. (Accessed 13 Sep 2022)"},{"issue":"4","key":"39_CR2","doi-asserted-by":"publisher","first-page":"2347","DOI":"10.1109\/COMST.2015.2444095","volume":"17","author":"A Al-Fuqaha","year":"2015","unstructured":"Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Commun. Surv. Tutorials 17(4), 2347\u20132376 (2015)","journal-title":"IEEE Commun. Surv. Tutorials"},{"issue":"7","key":"39_CR3","doi-asserted-by":"publisher","first-page":"6481","DOI":"10.1109\/JIOT.2019.2958185","volume":"7","author":"AA Cook","year":"2019","unstructured":"Cook, A.A., M\u0131s\u0131rl\u0131, G., Fan, Z.: Anomaly detection for IoT time-series data: A survey. IEEE Internet Things J. 7(7), 6481\u20136494 (2019)","journal-title":"IEEE Internet Things J."},{"key":"39_CR4","unstructured":"Perlroth, N.: Hackers Used New Weapons to Disrupt Major Websites Across U.S (2016). https:\/\/www.nytimes.com\/2016\/10\/22\/business\/internet-problems-attack.html. (Accessed 13 Sep 2022)"},{"key":"39_CR5","unstructured":"Porter, J.: Amazon says it mitigated the largest DDoS attack ever recorded. https:\/\/www.theverge.com\/2020\/6\/18\/21295337\/amazon-aws-biggest-ddos-attack-ever-2-3-tbps-shield-github-netscout-arbor. (Accessed 13 Sep 2022)"},{"key":"39_CR6","doi-asserted-by":"crossref","unstructured":"Balaban, I.: Denial-of-service attack. Int\u2019l J. Info. Sec. Cybercrime 10, 59 (2021)","DOI":"10.19107\/IJISC.2021.01.06"},{"key":"39_CR7","doi-asserted-by":"crossref","unstructured":"Mergendahl, S., Li, J.: Rapid: Robust and adaptive detection of distributed denial-of-service traffic from the internet of things. In 2020 IEEE Conference on Communications and Network Security (CNS), pp. 1\u20139. IEEE (June 2020)","DOI":"10.1109\/CNS48642.2020.9162278"},{"key":"39_CR8","doi-asserted-by":"crossref","unstructured":"Saghezchi, F.B., Mantas, G., Violas, M.A., de Oliveira Duarte, A.M., Rodriguez, J.: Machine learning for DDoS attack detection in industry 4.0 CPPSs. Electronics 11(4), 602 (2022)","DOI":"10.3390\/electronics11040602"},{"key":"39_CR9","doi-asserted-by":"crossref","unstructured":"Sharma, D.K., et al.: Anomaly detection framework to prevent DDoS attack in fog empowered IoT networks. Ad Hoc Netw. 121, 102603 (2021)","DOI":"10.1016\/j.adhoc.2021.102603"},{"issue":"4","key":"39_CR10","doi-asserted-by":"publisher","first-page":"6396","DOI":"10.1109\/JIOT.2019.2897063","volume":"6","author":"F Li","year":"2019","unstructured":"Li, F., Shinde, A., Shi, Y., Ye, J., Li, X.Y., Song, W.: System statistics learning-based IoT security: Feasibility and suitability. IEEE Internet of Things J. 6(4), 6396\u20136403 (2019)","journal-title":"IEEE Internet of Things J."},{"key":"39_CR11","doi-asserted-by":"crossref","unstructured":"Sahoo, K.S., Puthal, D.: SDN-assisted DDoS defense framework for the internet of multimedia things. ACM Trans. Multimedia Comput. Commun. Appli. (TOMM) 16(3s), 1\u201318 (2020)","DOI":"10.1145\/3394956"},{"issue":"1","key":"39_CR12","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1109\/TNSE.2020.3026961","volume":"8","author":"Y Wan","year":"2020","unstructured":"Wan, Y., Xu, K., Wang, F., Xue, G.: Characterizing and mining traffic patterns of IoT devices in edge networks. IEEE Trans. Netw. Sci. Eng. 8(1), 89\u2013101 (2020)","journal-title":"IEEE Trans. Netw. Sci. Eng."},{"key":"39_CR13","unstructured":"Cisa. Understanding Denial-of-Service Attacks (2022). https:\/\/www.cisa.gov\/uscert\/ncas\/tips\/ST04-015. (Accessed 13 Sep 2022)"},{"key":"39_CR14","doi-asserted-by":"crossref","unstructured":"Sousa, B.F.L.M., Abdelouahab, Z., Lopes, D.C.P., Soeiro, N.C., Ribeiro, W.F.: An intrusion detection system for denial of service attack detection in internet of things. In: Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing, pp. 1\u20138 (March 2017)","DOI":"10.1145\/3018896.3018962"},{"key":"39_CR15","doi-asserted-by":"crossref","unstructured":"Doshi, R., Apthorpe, N., Feamster, N.: Machine learning ddos detection for consumer internet of things devices. In: 2018 IEEE Security and Privacy Workshops (SPW), pp. 29\u201335. IEEE (May 2018)","DOI":"10.1109\/SPW.2018.00013"},{"issue":"1","key":"39_CR16","doi-asserted-by":"publisher","first-page":"627","DOI":"10.1109\/TNSM.2021.3088326","volume":"19","author":"MA Salahuddin","year":"2021","unstructured":"Salahuddin, M.A., Pourahmadi, V., Alameddine, H.A., Bari, M.F., Boutaba, R.: Chronos: Ddos attack detection using time-based autoencoder. IEEE Trans. Netw. Serv. Manage. 19(1), 627\u2013641 (2021)","journal-title":"IEEE Trans. Netw. Serv. Manage."},{"key":"39_CR17","doi-asserted-by":"crossref","unstructured":"Tann, W.J.W., Tan, J.J.W., Purba, J., Chang, E.C.: Filtering DDoS attacks from unlabeled network traffic data using online deep learning. In Proceedings of the 2021 ACM Asia Conference on Computer and Communications Security, pp. 432\u2013446 (May 2021)","DOI":"10.1145\/3433210.3453083"},{"key":"39_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1007\/978-3-030-86517-7_2","volume-title":"Machine Learning and Knowledge Discovery in Databases. Applied Data Science Track","author":"B Sudharsan","year":"2021","unstructured":"Sudharsan, B., Patel, P., Breslin, J.G., Ali, M.I.: Enabling machine learning on the edge using sram conserving efficient neural networks execution approach. In: Dong, Y., Kourtellis, N., Hammer, B., Lozano, J.A. (eds.) ECML PKDD 2021. LNCS (LNAI), vol. 12979, pp. 20\u201335. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-86517-7_2"},{"issue":"16","key":"39_CR19","doi-asserted-by":"publisher","first-page":"8294","DOI":"10.3390\/app12168294","volume":"12","author":"MA Alzahrani","year":"2022","unstructured":"Alzahrani, M.A., Alzahrani, A.M., Siddiqui, M.S.: Detecting DDoS attacks in iot-based networks using matrix profile. Appl. Sci. 12(16), 8294 (2022)","journal-title":"Appl. Sci."},{"key":"39_CR20","doi-asserted-by":"crossref","unstructured":"Santoyo-Gonz\u00e1lez, A., Cervell\u00f3-Pastor, C., Pezaros, D.P.: High-performance, platform-independent DDoS detection for IoT ecosystems. In: 2019 IEEE 44th Conference on Local Computer Networks (LCN), pp. 69\u201375. IEEE (October 2019)","DOI":"10.1109\/LCN44214.2019.8990862"},{"key":"39_CR21","doi-asserted-by":"crossref","unstructured":"Jouet, S., Pezaros, D.P.: Bpfabric: Data plane programmability for software defined networks. In: 2017 ACM\/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS), pp. 38\u201348. IEEE (May 2017)","DOI":"10.1109\/ANCS.2017.14"},{"issue":"22","key":"39_CR22","doi-asserted-by":"publisher","first-page":"6578","DOI":"10.3390\/s20226578","volume":"20","author":"I Vaccari","year":"2020","unstructured":"Vaccari, I., Chiola, G., Aiello, M., Mongelli, M., Cambiaso, E.: MQTTset, a new dataset for machine learning techniques on MQTT. Sensors 20(22), 6578 (2020)","journal-title":"Sensors"},{"key":"39_CR23","doi-asserted-by":"crossref","unstructured":"Hamza, A., Gharakheili, H.H., Benson, T.A., Sivaraman, V.: Detecting volumetric attacks on lot devices via sdn-based monitoring of mud activity. In: Proceedings of the 2019 ACM Symposium on SDN Research, pp. 36\u201348 (April 2019)","DOI":"10.1145\/3314148.3314352"},{"key":"39_CR24","unstructured":"WireShark (2022). https:\/\/www.wireshark.org\/index.html#download. (Accessed 29 Oct 2022)"},{"key":"39_CR25","unstructured":"Daemonlogger (2022). https:\/\/talosintelligence.com\/daemon. (Accessed 29 Oct 2022)"},{"key":"39_CR26","doi-asserted-by":"crossref","unstructured":"Lee, C.H., Lin, C.R., Chen, M.S.: Sliding-window filtering: an efficient algorithm for incremental mining. In Proceedings of The Tenth International Conference On Information And Knowledge Management, pp. 263\u2013270 (October 2001)","DOI":"10.1145\/502585.502630"},{"key":"39_CR27","unstructured":"Lautert, H.: Multiple Moving Avarages to Anomaly Detection in IoT networks (2022). https:\/\/github.com\/hflautert\/AnomalyDetection. (Accessed 29 Oct 2022)"},{"key":"39_CR28","unstructured":"Dean, W.: Computational Complexity Theory, The Stanford Encyclopedia of Philosophy (Fall 2021 Edition), Edward N. Zalta (ed.). https:\/\/plato.stanford.edu\/archives\/fall2021\/entries\/computational-complexity\/. (Accessed 29 Oct 2022)"},{"key":"39_CR29","doi-asserted-by":"crossref","unstructured":"Pioli, L., Dorneles, C.F., de Macedo, D.D., Dantas, M.A.: An overview of data reduction solutions at the edge of IoT systems: a systematic mapping of the literature. Computing, 1\u201323 (2022)","DOI":"10.1007\/s00607-022-01073-6"},{"key":"39_CR30","unstructured":"Di Vita, L.: Protocols Counter (2019). https:\/\/github.com\/lucadivit\/Protocols_Counter. (Accessed 31 Oct 2022)"}],"container-title":["Lecture Notes in Networks and Systems","Advanced Information Networking and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-29056-5_39","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,19]],"date-time":"2023-03-19T15:07:27Z","timestamp":1679238447000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-29056-5_39"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031290558","9783031290565"],"references-count":30,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-29056-5_39","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"value":"2367-3370","type":"print"},{"value":"2367-3389","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"20 March 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AINA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Networking and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Juiz de Fora","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazil","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 March 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31 March 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"37","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"aina2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/voyager.ce.fit.ac.jp\/conf\/aina\/2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}