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2019 | OriginalPaper | Buchkapitel

Cyber-Typhon: An Online Multi-task Anomaly Detection Framework

verfasst von : Konstantinos Demertzis, Lazaros Iliadis, Panayiotis Kikiras, Nikos Tziritas

Erschienen in: Artificial Intelligence Applications and Innovations

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel The Power of the “Pursuit” Learning Paradigm in the Partitioning of Data

Nächstes Kapitel Investigating the Benefits of Exploiting Incremental Learners Under Active Learning Scheme

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Titel: Cyber-Typhon: An Online Multi-task Anomaly Detection Framework
verfasst von: Konstantinos Demertzis
Lazaros Iliadis
Panayiotis Kikiras
Nikos Tziritas
Verlag: Springer International Publishing
Buch: Artificial Intelligence Applications and Innovations
Print ISBN: 978-3-030-19822-0

Electronic ISBN: 978-3-030-19823-7

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-19823-7_2

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