Cellular automata malware propagation model for WSN based on multi‐player evolutionary game

Wang, Yilin; Li, Donghui; Dong, Nianguo

doi:10.1049/iet-net.2017.0070

Cited by 22 publications

(9 citation statements)

References 17 publications

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“…In this model, the parameters considered are related to the life cycle of the computer virus, the countermeasures implemented on the host, and the user’s behavior. Wang et al [ 40 ] proposed a SIRD model based on two-dimensional 2D cellular automata CA. This model considered three aspects (infection, immunity, and mortality rates) in two different types of nodes (cluster-head and terminal nodes) to analyze malware propagation in WSN.…”

Section: Related Workmentioning

confidence: 99%

A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Zhang

et al. 2021

Sensors

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A wireless sensor network (WSN) is a group of sensors connected with a wireless communications infrastructure designed to monitor and send collected data to the primary server. The WSN is the cornerstone of the Internet of Things (IoT) and Industry 4.0. Robustness is an essential characteristic of WSN that enables reliable functionalities to end customers. However, existing approaches primarily focus on component reliability and malware propagation, while the robustness and security of cascading failures between the physical domain and the information domain are usually ignored. This paper proposes a cross-domain agent-based model to analyze the connectivity robustness of a system in the malware propagation process. The agent characteristics and transition rules are also described in detail. To verify the practicality of the model, three scenarios based on different network topologies are proposed. Finally, the robustness of the scenarios and the topologies are discussed.

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Section: Related Workmentioning

confidence: 99%

A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Zhang

et al. 2021

Sensors

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“…In the second scenario, the attacker’s goal is to defend the weakest node in the previous round of attack. Wang, Li & Dong (2018) proposed an improved two-dimensional (2D) cellular automata model and a multi-role evolutionary game model to describe the process of malware propagation. Based on the existing 2D cellular automata malware model, the epidemiological propagation mechanism is improved, and the dynamic equation of strategy evolution is given.…”

Section: Related Workmentioning

confidence: 99%

Malware propagation model for cluster-based wireless sensor networks using epidemiological theory

Zhu

Huang

2021

PeerJ Computer Science

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Due to limited resources, wireless sensor network (WSN) nodes generally possess weak defense capabilities and are often the target of malware attacks. Attackers can capture or infect specific sensor nodes and propagate malware to other sensor nodes in WSNs through node communication. This can eventually infect an entire network system and even cause paralysis. Based on epidemiological theory, the present study proposes a malware propagation model suitable for cluster-based WSNs to analyze the propagation dynamic of malware. The model focuses on the data-transmission characteristics between different nodes in a cluster-based network and considers the actual application parameters of WSNs, such as node communication radius, node distributed density, and node death rate. In addition, an attack and defense game between malware and defending systems is also established, and the infection and recovery rates of malware propagation under the mixed strategy Nash equilibrium condition are given. In particular, the basic reproductive number, equilibrium point, and stability of the model are derived. These studies revealed that a basic reproductive number of less than 1 leads to eventual disappearance of malware, which provides significant insight into the design of defense strategies against malware threats. Numerical experiments were conducted to validate the theory proposed, and the influence of WSN parameters on malware propagation was examined.

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“…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.…”

Section: Related Workmentioning

confidence: 99%

“…These models only consider the connection topology, but do not consider the particular characteristics of the other components of the WSN. These drawbacks can be overcome using individual-based models since this paradigm takes into account the individual connections and characteristics of the nodes, for example, the modified SEIR-V [10] and SIRD [11] epidemic propagation models, where other considered states are exposed (E), vaccinated (V) and dead (D).…”

Section: Introductionmentioning

confidence: 99%

A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks

2020

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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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Cellular automata malware propagation model for WSN based on multi‐player evolutionary game

Cited by 22 publications

References 17 publications

A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

A Novel Multi-Agent Model for Robustness with Component Failure and Malware Propagation in Wireless Sensor Networks

Malware propagation model for cluster-based wireless sensor networks using epidemiological theory

A New Individual-Based Model to Simulate Malware Propagation in Wireless Sensor Networks

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