Design and implementation of a secure LoRaWAN protocol used in critical applications in the IoT domain

Abstract

Of the available wireless transmission technologies, LPWANs (Low Power Wide Area Networks) are attracting increasing attention, not least because of their long radio range and low energy consumption. However, trying to minimize power consumption can sometimes compromise the resilience of data transmission in the face of environmental disturbances (interference, obstacles) and the mobility of connected objects. However, attempting to reduce power consumption can occasionally compromise the mobility of linked items and the robustness of data transmission against environmental disruptions (obstacles, interference). Additionally, each node’s duration occupancy of the frequency band is limited by the long radio range (e.g. duty cycle limited to 1%). We concentrate on LoRa/LoRaWAN technologies in this thesis. LoRaWAN may be able to accommodate a wide range of IoT applications and situations because to its numerous adjustable characteristics. It can converge to an ideal configuration to save energy due to its ADR (Adaptive Data Rate) function. More recently, LoRa and LoRaWAN have also drawn interest from applications utilizing mobile nodes. This thesis’s first contribution is its presentation of how mobility affects LoRaWAN performance. To achieve this, the research consists of two (02) parts: In the first part, we present an in-depth analysis of LoRaWAN performance evaluation in a mobility context. To do this, we consider several scenarios and performance evaluation measures using the NS − 3 simulator, based on the three mobility models most widely used in the literature, such as the Gauss Markov Mobility Model, the Random Waypoint Mobility model and the Constant Position Mobility Model. The new study presents the influence of these three models on energy consumption, PDR, network size and Radius. In order to validate the simulation results, in the second part we carried out numerous experiments with the Lora CubeCell HTCC-AB01 in various scenarios, analyzing the RSSI (Received Signal Strength Indicator) level in urban and rural areas using a large number of trajectories. The maximum distance obtained in a rural area is 1310 meters of line of sight, while in an urban area, the distance is equal to 966.97 meters of line of sight. In terms of energy consumption, the results show that the GM model is 0.1 J, and for the RWP and CP it is 0.4 J, which equals 9.6 J in 24 hours, which makes the GM model four times more efficient. The GM model with Alpha = 1 performs better than the other two models, and Alpha = 0.5 performs even better in terms of PDR. At the same time, the RWP demonstrates positive results regarding delays. In order to find the best combination for packet transmission, we provide a second contribution in this thesis to the description of the SFs allocation scheme for Lorawan. Furthermore, even though the various simulations carried out and the results obtained, we consider it more appropriate to use mathematical and logical methods to validate the ADR mechanism, and this was the subject of our third contribution. We used Event-B (the formal method) to model the protocol layers and their properties, and Event-B invariants to ensure protocol consistency, and we’ll add more guarantees to the validity of the protocol, focusing on the formal validation of the ADR mechanism on the network server side. The security aspect is studied, by presenting the physical structure of Lora packet, the Mac message types and the different LoraWan Mac commands, followed by the two activation modes of Lora End Devices including OTAA and ABP Mode. In all the literature, to our knowledge, currently the deployment of cryptography using the NS-3 simulator has not yet achieved, this is the subject of our main and last contribution, our goal is the implementation of AES-128 bits algorithm under the NS-3 simulator, and to assess the performance of the LoRaWAN network in terms of energy consumption, transmission latency, packet delivery rate, and CPU utilization. The findings indicate a shift in the transmission delay from 0.25 ms to 1.7 ms for a packet of 12 bytes and 216 bytes respectively