Title:

IS-4 Artificial Immune Ecosystems: the role of expert-based learning in artificial cognition

Publication: ICAROB2018
Volume: 23
Pages: 28-32
ISSN: 2188-7829
DOI: 10.5954/ICAROB.2018.IS-4
Author(s): Pierre Parrend, Fabio Guigou, Julio Navarro, Aline Deruyver, Pierre Collet
Publication Date: February 2, 2018
Keywords: Artificial Immune Systems, Cybersecurity, Immunity, Computational Ecosystem, Anomaly detection
Abstract: The rapid evolution of IT ecosystems significantly challenges the security models our infrastructures rely on. Beyond the old dichotomy between open and closed systems, it is now necessary to handle securely the interaction between heterogeneous devices building dynamic ecosystems. To this regard, bio-inspired approaches provide a rich set of conceptual tools, but they have failed to lay the basis for robust and efficient solutions. Our research effort intends to revisit the contribution of artificial immune system research to bring immune properties: security, resilience, distribution, memory, into IT infrastructures. Artificial immune ecosystems support a comprehensive model for anomaly detection and characterization, but their cognitive capacity are limited by the state of the art in machine learning and the rapid evolution of cybersecurity threats so far. We therefore propose to enrich the cognitive process with expert-based learning for reinforcement, classification and investigation. Application to system supervision using system logs and supervision time series confirms the relevance and performance of this model.
PDF File: https://alife-robotics.co.jp/members2018/icarob/data/html/data/IS_pdf/IS-4.pdf
Copyright: © The authors.
This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
See for details: https://creativecommons.org/licenses/by-nc/4.0/

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