IoT security vulnerabilities and predictive signal jamming attack analysis in LoRaWAN

Internet of Things (IoT) gains popularity in recent times due to its flexibility, usability, diverse applicability and ease of deployment. However, the issues related to security are less explored. The IoT devices are light weight in nature and have low computation power, low battery life and low memory. As incorporating security features are resource expensive, IoT devices are often found to be less protected and in recent times, more IoT devices have been routinely attacked due to high profile security flaws. This study aims to explore the security vulnerabilities of IoT devices particularly that use low power wide area networks (LPWANs). In this work, long range wide area network (LoRaWAN) based IoT security vulnerabilities are scrutinised and loopholes are identified. An attack was designed and simulated with the use of a predictive model of the device data generation. The study demonstrated that by predicting the data generation model, the jamming attack can be carried out to block devices from sending data successfully. This research will aid in the continual development of any necessary countermeasures and mitigations for LoRaWAN and LPWAN functionality of IoT networks in general.