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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 10, 2020.
Abstract: The objective of this research work is to propose a new model of intrusion detection system for a fleet of UAVs deployed with an ad hoc communication architecture. The security of a drone fleet is rarely addressed by the scientific community, and most research has focused on routing protocols and battery autonomy, while ignoring the security aspect. The multi-agent paradigm is considered the most adequate and appropriate solution to model an effective intrusion detection system capable of detecting intrusions targeting a drone fleet. Multi-agent systems can perfectly address the security problem of a drone fleet, given the mobility, autonomy, cooperation and distribution characteristics present in the network linking the different nodes of the fleet. The proposed model consists of a set of cooperative, autonomous, communicating, learning and intelligent agents that collaborate with each other to carry out intrusion and suspicious activity detection missions that can target the network of a fleet of drones. Our system is autonomous and can detect known and unknown cyber attacks in real time without the need for human experts, who generally design the signatures of known attacks for conventional intrusion detection systems.
Said OUIAZZANE, Fatimazahra BARRAMOU and Malika ADDOU, “Towards a Multi-Agent based Network Intrusion Detection System for a Fleet of Drones” International Journal of Advanced Computer Science and Applications(IJACSA), 11(10), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111044
@article{OUIAZZANE2020,
title = {Towards a Multi-Agent based Network Intrusion Detection System for a Fleet of Drones},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111044},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111044},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {10},
author = {Said OUIAZZANE and Fatimazahra BARRAMOU and Malika ADDOU}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.