A Cellular Automata Model for Mobile Worm Propagation

Rey, Ángel Martín del; Encinas, Ascensión Hernández; Vaquero, Juan Pablo Aparicio; Dios, Araceli Queiruga; Sánchez, Gerardo Rodríguez

doi:10.1007/978-3-319-18833-1_12

Cited by 3 publications

References 7 publications

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Bluetooth Worm Propagation in Smartphones: Modeling and Analyzing Spatio-Temporal Dynamics

et al. 2021

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The use of smartphones has become an inherent part of daily human life. It allows users to keep personal information, emails, pictures, social media accounts, and financial data in one place. Consequently, smartphones are an attractive target for malware developers to spread malicious content, aiming at extracting information without the user's knowledge. Therefore, understanding malware propagation characteristics could provide a means to evaluate how they behave in order to plan security solutions accordingly. Bluetooth antennas are a channel for spreading malware through smartphones, where the probability of infection, similar to biological viruses, depends mainly on the attacker's physical proximity. This work presents a model based on cellular automata and epidemiological compartmental models for studying the spatial and temporal propagation of Bluetooth worms in smartphones. The proposed model incorporates the individual characteristics of each device, such as security settings, latency time, operating system, different classes of Bluetooth antennas (range and transfer rate), and different user mobility patterns. Several simulation scenarios are analyzed in order to study the spreading dynamics of Bluetooth-based worms, considering the location where the outbreak begins, and the different types of antennas integrated into the smart devices. Simulation results indicated that the proposed model is appropriate for studying how the users' demographics affect the worm's propagation dynamics in time and space. Moreover, the model permits an analysis of the impact of users' awareness about the risks inherent in using smart devices in Bluetooth networks, based on the acceptance of incoming communication and the effects of recovery and immunity to threats. Finally, the proposed model preserves simplicity and computational efficiency, with the possibility of extending beyond Bluetooth in order to include other transmission media.

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