4.2. Malware Diffusion Behavior and Modeling via Queuing Techniques
4.2.1. Basic Assumptions
An important key observation regarding malware diffusion dynamics, in general, is that the time spent by attacked and infected legitimate nodes in the states defined by the corresponding malware infection model, i.e. susceptible (S), infected (I), recovering (R), dead (D) state, is inherently characterized by a stochastic nature, because it is influenced by random events. Indeed, legitimate users remain in each state until the arrival of a certain event triggers a transition to another state. For instance, an infection signifies a transition from the susceptible to the infected state and a recovery a transition from the recovering to the susceptible state ...
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