Secure LoRa Firmware Update with Adaptive Data Rate Techniques

Derek Heeger,Eirini Eleni Tsiropoulou,Maeve Garigan,Jim Plusquellic

doi:10.3390/s21072384

Derek Heeger, Eirini Eleni Tsiropoulou + Show 2 more

Open Access

https://doi.org/10.3390/s21072384

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Abstract

Internet of Things (IoT) devices rely upon remote firmware updates to fix bugs, update embedded algorithms, and make security enhancements. Remote firmware updates are a significant burden to wireless IoT devices that operate using low-power wide-area network (LPWAN) technologies due to slow data rates. One LPWAN technology, Long Range (LoRa), has the ability to increase the data rate at the expense of range and noise immunity. The optimization of communications for maximum speed is known as adaptive data rate (ADR) techniques, which can be applied to accelerate the firmware update process for any LoRa-enabled IoT device. In this paper, we investigate ADR techniques in an application that provides remote monitoring of cattle using small, battery-powered devices that transmit data on cattle location and health using LoRa. In addition to issues related to firmware update speed, there are significant concerns regarding reliability and security when updating firmware on mobile, energy-constrained devices. A malicious actor could attempt to steal the firmware to gain access to embedded algorithms or enable faulty behavior by injecting their own code into the device. A firmware update could be subverted due to cattle moving out of the LPWAN range or the device battery not being sufficiently charged to complete the update process. To address these concerns, we propose a secure and reliable firmware update process using ADR techniques that is applicable to any mobile or energy-constrained LoRa device. The proposed system is simulated and then implemented to evaluate its performance and security properties.

Highlights

Internet of Things (IoT) devices continue to proliferate across consumer, industrial, and agricultural sectors as advances in mobile computing and networking make intelligent automation and sensing both technically feasible and cost-effective
In prior work [19], we address challenges associated with adaptive data rate (ADR) in Long Range (LoRa) ad-hoc networks
The firmware update process described in the prior section was simulated and implemented on the cattle monitoring sensor

Summary

Introduction

Internet of Things (IoT) devices continue to proliferate across consumer, industrial, and agricultural sectors as advances in mobile computing and networking make intelligent automation and sensing both technically feasible and cost-effective. A primary limitation of wireless IoT devices is energy consumption as they are typically powered by low-capacity batteries. These devices connect to the Internet directly through Wi-Fi or cellular, or through a gateway for radio frequency (RF) communication protocols, such as Zigbee, Long Range (LoRa), and Bluetooth. LoRaWAN is built on top of LoRa, which is a closed source protocol that uses chirped spread spectrum to enable long range communications while sacrificing data rates. LoRaWAN has three classes of operation (A, B, and C) that allow devices to optimize their performance at the expense of battery power when communicating to a LoRa Gateway. Class C consumes significant power but allows for advanced operations like mesh networking and is always able to receive data. Challenges with ADR for mobile devices were covered in [18]

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