Afficher la notice abrégée

dc.creatorDemertzis, K.en
dc.creatorIliadis, L.en
dc.creatorKikiras, P.en
dc.creatorTziritas, N.en
dc.date.accessioned2022-11-03T16:27:41Z
dc.date.available2022-11-03T16:27:41Z
dc.date.issued2019
dc.identifier10.1007/978-3-030-19823-7_2
dc.identifier.isbn978-3-030-19823-7
dc.identifier.issn1868-4238
dc.identifier.issn1868-422X
dc.identifier.urihttp://hdl.handle.net/11615/60212
dc.description.abstractAccording 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.en
dc.sourceArtificial Intelligence Applications and Innovationsen
dc.subjectDeep content inspectionen
dc.subjectAnomaly detectionen
dc.subjectMulti-task learningen
dc.subjectOnline learningen
dc.subjectRestricted Boltzmann Machineen
dc.subjectCritical Infrastructure Protectionen
dc.titleCyber-Typhon: An Online Multi-task Anomaly Detection Frameworken
dc.typejournalArticleen
dc.identifier.bibliographicCitationDemertzis, K., Iliadis, L., Kikiras, P., Tziritas, N. (2019). Cyber-Typhon: An Online Multi-task Anomaly Detection Framework. In: MacIntyre, J., Maglogiannis, I., Iliadis, L., Pimenidis, E. (eds) Artificial Intelligence Applications and Innovations. AIAI 2019. IFIP Advances in Information and Communication Technology, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-030-19823-7_2en


Fichier(s) constituant ce document

FichiersTailleFormatVue

Il n'y a pas de fichiers associés à ce document.

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée