Abstract
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.
Highlights
Mobile telephony use is growing rapidly around the world
This paper focuses on worm-type malware, which can propagate through Bluetooth antennas by making copies of itself and sending them to other devices in its proximity without any action or knowledge of the infected smartphone owner
For high-density environments, a larger population of infected devices is achieved with Straight Line (SL) movement, because smartphone users tend to move across larger routes than with the Random Walk (RW) pattern, which is not favored by the reduced spaces existing between devices
Summary
Mobile telephony use is growing rapidly around the world. According to Statista [1], the number of mobile phone users was forecasted to reach 2.87 billion by 2020. The following new features are considered in the definition of the dynamics of the proposed model and its behavior: 1) Different Bluetooth antenna classes were considered that implied different ranges and transmission rates which affect the time to transmit the worm payload; in other words, a worm can propagate faster in some devices; 2) Renewal factors to simulate existing devices moving out of the area under study and new devices moving in; 3) The influence of different types of device mobility. From an Interrupted to a Susceptible State This state transition represents the situation in which a smartphone was connected to an infected device and one of the two devices left the range of the Bluetooth antenna before worm transmission ended.
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