Authors
Pierre Parrend, Fabio Guigou, Julio Navarro, Aline Deruyver, Pierre Collet
Corresponding Author
Pierre Parrend
Available Online 31 March 2018.
DOI
https://doi.org/10.2991/jrnal.2018.4.4.10How to use a DOI?
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.

Copyright
© 2018, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).