# A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks
## 2 Related work
A SEIR model to simulate the propagation of computer virus through a computer network was introduced in Reference [27]. The mathematical tool used was cellular automata on graphs. In this model, the parameters that are considered are related to the life cycle of a computer virus, countermeasures implemented in the hosts, and the behaviour of the users. It is also an individual, discrete and deterministic model. A SIRD model based on two-dimensional 2D cellular automata CA has been proposed in Reference [11]. This model has considered three aspects (infection, immunity and mortality rates) in two different types of nodes (cluster-head and terminal nodes) to analyze the propagation of malware in WSN. Besides, a multi-player evolutionary game model has been built to find the optimal evolutionary and stable strategy. It is also an individual, discrete and deterministic model. This novel model has been developed based on the ABM paradigm that allows assigning characteristics and actions to each autonomous individual and establishing the interaction between individuals within an environment. The characteristics that have frequently been considered in related studies are the type of sensor and malware. Some more recent studies have included the topology and the environment. In addition to these particularities, the proposed model includes other individual characteristics of the sensors, for example, computational capacity, information transmission and reception capacity, duty cycle and data collection methods. On the other hand, human action and external and computational devices have been introduced as agents influencing the spread of malware. The ABM paradigm has been also considered for designing models to simulate not only biological agents spread (see References [28; 29; 30]) but also malware propagation (see Reference [31; 32]). In Reference [31] the authors introduce a novel agent-based emulation framework for studying complex malware. It considers different applications, network structures, network coordination and devices mobility. Specifically, the attention is focus in (1) malware spreading among the users of a cellular network considering as transmission vector the Bluetooth connections, and (2) hybrid computer worm whose transmission vector is e-mail connection and file sharing. On the other hand, in Reference [32] an ABM model for malware propagation based on the rumor diffusion process is proposed. This considers a set of heterogenous agents (devices) and interactions between them. It is based on a networked model whose dynamics is governed by means of a system of ordinary differential equations. Any of them are devoted to analyze the propagation on a wireless sensor network. Consequently, this model has an adequate number of features to efficiently evaluate the behaviour of the WSN and its components when the network has been infected by malware. Main advantages of this proposed model are based on the predictive capacity--it has been improved with respect not only to the traditional approaches to malware spreading based on differential equations, but also to these proposals related with ABM paradigm. Specifically, our work considers a more detailed description and classification of agents and not only devices are considered but also another such as the own malicious code, the network topology, the phenomenon of interest, the human action, and so forth. Furthermore, in this case, the individual characteristics of essential components of the network have been included. Consequently, the most vulnerable topologies and environments have been identified where the spread of malware can most easily take place. Finally, the real-time display of the compartment states of node at each step of time \(t\). However, the most significant disadvantage has been that no real data have been obtained from a network to analyze other features that may influence the results.