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- W4376606340 abstract "As aviation industry has progressed in recent years, the entire industry has become more and more relying on digital network connectivity and electronic data exchange. While these changes bring efficiency, they also provide opportunities for hackers and malware to threaten flight safety. For example, in 2022, the Canadian airline Sunwing experienced flight delays due to cyber attacks. In many cases, if proper defense strategies are used early, the damage caused by the threat can be greatly reduced. However, due to dynamic, heterogeneous and huge structural characteristics of aviation systems, managers are unable to assess the current system security status in a real-time and accurate way, which affects the decision-making process and leads to expose the whole system under the risk. Therefore, aviation networks need a situational awareness mechanism to help managers adjust their strategies and limit the impact of threats in a timely and accurate manner. There has been a lot of current research in network security situational awareness, but there are some problems when these studies are directly applied to aviation networks. In order to establish a situation awareness mechanism applicable to aviation networks, this paper proposes a situation awareness method based on game theory, particle swarm optimization algorithm and neural network by analyzing the strategy gain of attackers and defenders under network attack and defense, particle swarm optimization algorithm and long short-term memory networks. The innovative works of this paper are as follows. Firstly, the situation assessment model is established based on the classification of attackers; secondly, the method of situation prediction with improved particle swarm optimization algorithm and long short-term memory networks is proposed. Simulation experiment shows that the method in this paper has the advantages of high evaluation efficiency and low error rate of prediction results, which can reason about the attacker class and help managers to make reasonable decisions." @default.
- W4376606340 created "2023-05-17" @default.
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- W4376606340 date "2023-03-04" @default.
- W4376606340 modified "2023-09-23" @default.
- W4376606340 title "Aviation Network Security Situation Awareness Based on Game Theory" @default.
- W4376606340 doi "https://doi.org/10.1109/aero55745.2023.10115582" @default.
- W4376606340 hasPublicationYear "2023" @default.
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