Abstract
Aspects of human behavior in cyber security allow more natural security to the user. This research focuses the appearance of anticipating cyber threats and their abstraction hierarchy levels on the mental picture levels of human. The study concerns the modeling of the behaviors of mental states of an individual under cyber attacks. The mental state of agents being not observable, we propose a non-stationary hidden Markov chain approach to model the agent mental behaviors. A renewal process based on a nonparametric estimation is also considered to investigate the spending time in a given mental state. In these approaches, the effects of the complexity of the cyber attacks are taken into account in the models.
Highlights
Cyber security provides protection and prevention for a network system
The cyber security relating to the human behavior and the cognitive Figure 8
A non-stationary hidden Markov model was applied to the detection of the mental states of the agent
Summary
Cyber security provides protection and prevention for a network system. security technology is sometime perceived as an obstacle [1]. In a degraded situation of work, the agents have to implement a concrete solution after analyzing the problem In cognitive terms, they go down in the abstraction hierarchy level of the environment [3] [4] [5]. At the high level of abstraction hierarchy, the agents can manage the defense against a cyber attack on the system more efficiency [4]. This means that they have a more global and abstract mental representation of the cyber attack and its consequences.
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