A Human-Centred model for cyber attacks analysis

Computer networks are ubiquitous and growing exponentially, with a predicted 50 billion devices connected by 2050. This tremendous growth dramatically increases the attack surface of both private and public networks. These attacks often influence the behaviour of the system, leading to the detection of the attack. In this manuscript we model the path of an attack through the network by graphs. The model developed aims to better integer attackers intentions. Using the data produced by 5 honeypots, we apply our model. The preliminary results show that the approach is useful to rapidly detect anomalies in the experiment dataset