Wireless Sensor Networks (WSNs) are a set of sensor devices deployed in a given area that form a network without a pre-established architecture. Recently, malware has increased as a potential vulnerability for the Internet of Things, and consequently for these networks. The spread of malware on wireless sensor networks has been studied from different perspectives, excluding individual characteristics in most of the models proposed. The primary goal of this work is to introduce an Agent-Based Model for analysing malware propagation on these networks, and its agents, coefficients and transition rules are detailed. Finally, some simulations of the proposed model are included.

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In the past few years, the use of several medical devices is increasing. This paper will pay attention to a device developed to get measures of the temperature of diabetic foot. These wearables usually do not have cryptographic protocols to guarantee data security. This study analyzes the existing security in these devices, and simulate malware propagation taking into account the vulnerabilities and lack of security in these highly-constrained interconnected devices. A simulation of malware spreading in a network made by 10 and 15 individuals with 6 and 34 sensors each one, respectively, is included in this study. To avoid such attacks, a lightweight cryptographic protocol could be a satisfactory solution. Considering the quick development of quantum computers, several current cryptographic protocols have been compromised.

The main goal of this work is to propose a new framework to design a novel family of mathematical models to simulate malware spreading in wireless sensor networks (WSNs). An analysis of the proposed models in the scientific literature reveals that the great majority are global models based on systems of ordinary differential equations such that they do not consider the individual characteristics of the sensors and their local interactions. This is a major drawback when WSNs are considered. Taking into account the main characteristics of WSNs (elements and topologies of network, life cycle of the nodes, etc.) it is shown that individual-based models are more suitable for this purpose than global ones. The main features of this new type of malware propagation models for WSNs are stated.