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Cyber-Typhon: An Online Multi-task Anomaly Detection Framework
dc.creator | Demertzis K., Iliadis L., Kikiras P., Tziritas N. | en |
dc.date.accessioned | 2023-01-31T07:53:23Z | |
dc.date.available | 2023-01-31T07:53:23Z | |
dc.date.issued | 2019 | |
dc.identifier | 10.1007/978-3-030-19823-7_2 | |
dc.identifier.isbn | 9783030198220 | |
dc.identifier.issn | 18684238 | |
dc.identifier.uri | http://hdl.handle.net/11615/73202 | |
dc.description.abstract | According to the Greek mythology, Typhon was a gigantic monster with one hundred dragon heads, bigger than all mountains. His open hands were extending from East to West, his head could reach the sky and flames were coming out of his mouth. His body below the waste consisted of curled snakes. This research effort introduces the “Cyber-Typhon” (CYTY) an Online Multi-Task Anomaly Detection Framework. It aims to fully upgrade old passive infrastructure through an intelligent mechanism, using advanced Computational Intelligence (COIN) algorithms. More specifically, it proposes an intelligent Multi-Task Learning framework, which combines On-Line Sequential Extreme Learning Machines (OS-ELM) and Restricted Boltzmann Machines (RBMs) in order to control data flows. The final target of this model is the intelligent classification of Critical Infrastructures’ network flow, resulting in Anomaly Detection due to Advanced Persistent Threat (APT) attacks. © 2019, IFIP International Federation for Information Processing. | en |
dc.language.iso | en | en |
dc.source | IFIP Advances in Information and Communication Technology | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065902707&doi=10.1007%2f978-3-030-19823-7_2&partnerID=40&md5=a038f6411580a687cba0963b4a78cbb5 | |
dc.subject | Artificial intelligence | en |
dc.subject | Critical infrastructures | en |
dc.subject | Learning systems | en |
dc.subject | Public works | en |
dc.subject | Content inspections | en |
dc.subject | Critical infrastructure protection | en |
dc.subject | Multitask learning | en |
dc.subject | Online learning | en |
dc.subject | Restricted boltzmann machine | en |
dc.subject | Anomaly detection | en |
dc.subject | Springer New York LLC | en |
dc.title | Cyber-Typhon: An Online Multi-task Anomaly Detection Framework | en |
dc.type | conferenceItem | en |
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