We present a self-organised method for quickly obtaining the epidemic threshold of infective processes on net- works. Starting from simple percolation models, we introduce the possibility that the effective infection probability is affected by the perception of the risk of being infected, given by the fraction of infected neighbours. We then extend the model to multiplex networks considering that agents (computer) can be infected by contacts on the physical network, while the information about the infection level may come from a partially different network. Finally, we consider more complex infection processes, with non- linear interactions among agents.

Risk Perception and Epidemics in Complex Computer Networks / Bagnoli, Franco; Bellini, Emanuele; Massaro, Emanuele. - STAMPA. - (2018), pp. 1-5. (Intervento presentato al convegno 2018 IEEE Workshop on Complexity in Engineering, COMPENG 2018 tenutosi a ita nel 2018) [10.1109/CompEng.2018.8536247].

Risk Perception and Epidemics in Complex Computer Networks

Bagnoli, Franco;Bellini, Emanuele;Massaro, Emanuele
2018

Abstract

We present a self-organised method for quickly obtaining the epidemic threshold of infective processes on net- works. Starting from simple percolation models, we introduce the possibility that the effective infection probability is affected by the perception of the risk of being infected, given by the fraction of infected neighbours. We then extend the model to multiplex networks considering that agents (computer) can be infected by contacts on the physical network, while the information about the infection level may come from a partially different network. Finally, we consider more complex infection processes, with non- linear interactions among agents.
2018
2018 IEEE Workshop on Complexity in Engineering, COMPENG 2018
2018 IEEE Workshop on Complexity in Engineering, COMPENG 2018
ita
2018
Bagnoli, Franco; Bellini, Emanuele; Massaro, Emanuele
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1157278
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