Cyber-Typhon: An Online Multi-task Anomaly Detection Framework - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2019

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

Konstantinos Demertzis
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Lazaros Iliadis
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Panayiotis Kikiras
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Nikos Tziritas
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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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hal-02331349 , version 1 (24-10-2019)

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Konstantinos Demertzis, Lazaros Iliadis, Panayiotis Kikiras, Nikos Tziritas. Cyber-Typhon: An Online Multi-task Anomaly Detection Framework. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.19-36, ⟨10.1007/978-3-030-19823-7_2⟩. ⟨hal-02331349⟩
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