Deep Learning based Radio Frequency Fingerprint Identification (DL-RFFI) systems are emerging as a vital technology for Internet-of-Things (IoT) device authentication at the physical layer. It exploits the hardware impairments in the analog front-end components of the transmitter as the identifying features. However, the DL-RFFI system struggles to generalize in unseen domains, i.e., when trained at closer distances and tested at longer distances, the DL-RFFI shows significant performance degradation. In this paper, we design a 1D Convolutional Neural Network (1D-CNN) based DL-RFFI system, mainly focused on a multi-distance scenario. We use Long-Range (LoRa) technology as our case study and collect LoRa RF data at multiple distances from 5 to 30m. We train our model using several signal representation methods, namely, raw In-phase and Quadrature (IQ), frequency domain (FFT), and a combination of both. In addition, we also present a fusion model based on additional features extracted from IQ data using an open-source feature extraction library. Our experimental results show that our fusion model can achieve higher device identification accuracy of over 91% on unseen distance (25 and 30m) data when the model is trained on data from 5 to 20m only.

LoRaWAN devices are secured using traditional cryptographic methods. However, the end devices are still vulnerable to security attacks such as impersonation. To counter these attacks, LoRa requires an additional layer of security at the physical level. Deep Learning-based LoRa device identification using Radio Frequency Fingerprinting is currently seen as a key candidate for enhancing LoRa security at the physical layer. However, a more in-depth study of certain aspects of this approach is required. Firstly, the appropriate LoRa signal representation has to be chosen which provides high device identification accuracy. Secondly, there is a need for deep learning models with less computational complexity and high performance. This paper contributes to the state-of-the-art in two ways: (1) we evaluate various signal representations such as raw In-phase Quadrature (IQ), Amplitude and Phase ($A / \phi$), frequency domain (FFT), and time-frequency domain (Spectrogram) (2) we show that an existing complex ResNet model can be optimized into a lightweight model by tuning its parameters without compromising much on the performance. We implement a different lightweight model for IQ, FFT, and $A / \phi$ representations. We show that our optimized ResNet model for spectrogram and proposed lightweight model for sequential data can achieve an accuracy of over $\mathbf{9 7 \%}$.

LoRaWAN is one of the most popular Internet of Things radio communication technologies since it allows data to be transmitted over long distances with low power consumption on unlicensed ISM bands. Devices used with LoRaWAN are often constrained for reasons of manufacturing cost and to save energy as they are most often battery-powered. As a consequence, security mechanisms chosen for such devices must be lightweight. The LoRaWAN standard relies on AES-128 for encryption and authentication, using a pre-shared key. With the increasing amount of computational power at hand and the advent of quantum cryptography, the use of short AES keys without renewal for long periods of time is a potential weakness. However, using longer keys in LoRaWAN impacts end devices in terms of processing time and energy consumption. It might also require adaptations in the protocol design. This paper investigates the cost of using different AES key sizes with different payload sizes on an off-the-shelf LoRaWAN platform. Our results show that costs in terms of delay and energy consumption are moderate and using longer key sizes is a practical solution to increase the security of LoRaWAN.

Industrial IoT (IIoT) networks must provide reliability, determinism and security. In terms of security, ensuring an efficient authentication is still a challenging task. Most of the authentication approaches adopted in IIoT wireless communication protocols rely on the existence of a pre-shared key (PSK) between each joining node and the central authority of the network. How to share the PSK is however not specified in their standards. In this paper, we propose a new zero-touch mutual authentication and key establishment protocol for IIoT. In our protocol, the network coordinator authenticates a new joining node using certificates. Then, the joining node authenticates the network coordinator through a novel consensus achieved among nodes that are already in the network. Our novel consensus is based on Shamir secret sharing, and allows each new node to build its trust based on the knowledge of a group of nodes that are already in the network. Finally, our protocol allows to securely establish a common key between new joining nodes and the network coordinator over a public channel. In addition to the theoretical aspects, we evaluate the performance of our protocol under two attack scenarios where 33% of the nodes in the network are malicious. We show in all cases that we efficiently ensure authentication with high success probabilities, by establishing a consensus including a limited number of nodes in the network.

The IPv6 routing protocol for low-power and lossy networks (RPL) was standardized by the IETF to allow multiple resource-constrained devices to interconnect in an IPv6 multihop mesh network. One of its design objectives is the ability to customize the routing objectives according to different application requirements. This is achieved through the support of various routing metrics and constraints that are then used by objective functions to pick the best path. Another objective is the ability to scale to networks composed of hundreds to thousands of devices.In this paper, we focus on the specific topic of multi-instance, a feature discussed in the RPL standard but not investigated through much research, a situation we attribute to a lack of publicly available implementation. We detail the architecture of RPL when operating in a multi-instance environment, clarify parts of the standard related to forwarding packets along a specific instance and present an implementation based on ContikiRPL we developed during the last few years. We detail some of our design choices. Then, using our prototype, we present a first systematic performance evaluation of multi-instance RPL through experiments in a large scale testbed. Our results indeed show a tipping-point when the number of instances becomes excessive but more importantly confirm that a limited number of instances can efficiently cohabit on a common network without negatively impacting the packet delivery ratio and RPL convergence time.

IEEE Std 802.15.4-2015 Time Slotted Channel Hopping (TSCH) is the de facto Medium Access Control (MAC) mechanism for industrial applications. It renders communications more resilient to interference by spreading them over the time (time slotted) and the frequency (channel hopping) domains. The 6TiSCH architecture bases itself on this new MAC layer to enable high reliability communication in Wireless Sensor Networks (WSNs). In particular, it manages the construction of a distributed communication schedule that continuously adapts to changes in the network. In this paper, we first provide a thorough description of the 6TiSCH architecture, the 6TiSCH Operation Sublayer (6top), and the Minimal Scheduling Function (MSF). We then study its behavior and reactivity from low to high traffic rates by employing the python-based 6TiSCH simulator. Our performance evaluation results demonstrate that the convergence pattern of MSF is the root cause of the majority of packet losses observed in the network. We also show that MSF is subject to over-provisioning of the network resources, especially in the case of varying traffic load.

This paper describes our work on a flexible centralized controller for scheduling wireless networks. The context of this work encompasses wireless networks within the wider Internet of Things (IoT) field and in particular addresses the requirements and limitations within the narrower Industrial Internet of Things (IIoT) sub-field. The overall aim of this work is to produce wireless networking solutions for industrial applications. The challenges include providing high reliability and low latency guarantees, comparable to existing wired solutions, within a noisy wireless medium and using generally computationally- and energy-restrained network nodes. We describe the development of a centralized controller for Wireless Industrial Networks, currently aimed at IEEE Std 802.15.4-2015 Time Slotted Channel Hopping protocol. Our controller takes a high-level network-centric problem description as input, translates it to a low-level representation and uses that to retrieve a solution from a Satisfiability Modulo Theories (SMT) solver, translating the solution back to a higher-level network-centric representation. The advantages of our solution are the ability to gain the added flexibility, higher ease of deployment, and lower deployment cost offered by wireless networks by generating configurable and flexible schedules for these applications.

We consider multi-player games played on graphs, in which the players aim at fulfilling their own (not necessarily antagonistic) objectives. In the spirit of evolutionary game theory, we suppose that the players have the right to repeatedly update their respective strategies (for instance, to improve the outcome w.r.t. the current strategy profile). This generates a dynamics in the game which may eventually stabilise to an equilibrium. The objective of the present paper is twofold. First, we aim at drawing a general framework to reason about the termination of such dynamics. In particular, we identify preorders on games (inspired from the classical notion of simulation between transitions systems, and from the notion of graph minor) which preserve termination of dynamics. Second, we show the applicability of the previously developed framework to interdomain routing problems.

The protocols used in Wireless Sensor Networks are subject to very strict temporal synchronization constraints. Radio Duty Cycle (RDC) protocols in particular are characterized by their very high synchronization accuracy requirements. In these protocols, synchronization errors are primarily caused by the natural clock drift observed in real nodes. The impact of the clock drift on the desynchronization issues can be investigated by the use of low-level node simulators.

Wireless Sensor Networks performing low-power data collection often suffer from uneven load distribution among nodes. Nodes close to the network root typically face a higher load, see their battery deplete first, and become prematurely unable to operate (both sensing and relaying other nodes' data). We argue that opportunistic routing, by making forwarding decision on a per-packet basis and at the receiver rather than the sender, has the potential to better balance the load across nodes. We extend ORPL, an opportunistic version of the standard routing protocol RPL, with support for load-balancing. In our protocol, ORPL-LB, nodes continuously adapt their wake-up interval in order to adjust their availability and attain a deployment-specific target duty cycle. We implement our protocol in Contikiand present our experimental validation in Indriya, a 93-nodestestbed. Our results show that ORPL-LB reduces significantly(by approximately 40%) the worst node's duty cycle, with little or no impact on packet delivery ratio and latency.

As part of a search for a better understanding of MAC/routing interactions in Wireless Sensor Networks, this paper presents an analysis of the behaviour of the AODV routing protocol when combined with a duty-cycle MAC protocol. In particular, the paper focuses on the time it takes for a route request to be answered in presence of increased latency due to the MAC protocol sleep schedule. The paper quantifies how the response time varies with the duty-cycle ratio. Moreover, recommendations are provided to enhance this response time.

In this paper we introduce the concepts of Network Planes and Parallel Internets, with the objective of designing and implementing a lightweight solution for viable end-to-end QoS provisioning. The proposed solution can be deployed with very small incremental additions to the existing best-effort Internet. Through Network Plane engineering and interconnection, mainly by means of intra- and inter-domain routing differentiation, end-to-end service differentiation across the Internet can be achieved.

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