Remotely Exploiting AT Command Attacks on ZigBee Networks

Internet of Things networks represent an emerging phenomenon bringing connectivity to common sensors. Due to the limited capabilities and to the sensitive nature of the devices, security assumes a crucial and primary role. In this paper, we report an innovative and extremely dangerous threat targeting IoT networks. The attack is based on Remote AT Commands exploitation, providing a malicious user with the possibility of reconfiguring or disconnecting IoT sensors from the network. We present the proposed attack and evaluate its efficiency by executing tests on a real IoT network. Results demonstrate how the threat can be successfully executed and how it is able to focus on the targeted nodes, without affecting other nodes of the network

Communications protocols for wireless sensor networks in perturbed environment

This thesis is mainly in the Smart Grid (SG) domain. SGs improve the safety of electrical networks and allow a more adapted use of electricity storage, available in a limited way. SGs also increase overall energy efficiency by reducing peak consumption. The use of this technology is the most appropriate solution because it allows more efficient energy management. In this context, manufacturers such as Hydro-Quebec deploy sensor networks in the nerve centers to control major equipment. To reduce deployment costs and cabling complexity, the option of a wireless sensor network seems the most obvious solution. However, deploying a sensor network requires in-depth knowledge of the environment. High voltages substations are strategic points in the power grid and generate impulse noise that can degrade the performance of wireless communications. The works in this thesis are focused on the development of high performance communication protocols for the profoundly disturbed environments. For this purpose, we have proposed an approach based on the concatenation of rank metric and convolutional coding with orthogonal frequency division multiplexing. This technique is very efficient in reducing the bursty nature of impulsive noise while having a quite low level of complexity. Another solution based on a multi-antenna system is also designed. We have proposed a cooperative closed-loop coded MIMO system based on rank metric code and max−dmin precoder. The second technique is also an optimal solution for both improving the reliability of the system and energy saving in wireless sensor networks

Power line communications over time-varying frequency-selective power line channels for smart home applications

Many countries in the world are developing the next generation power grid, the smart grid, to combat the ongoing severe environmental problems and achieve e�cient use of the electricity power grid. Smart metering is an enabling technology in the smart grid to address the energy wasting problem. It monitors and optimises the power consumption of consumers' devices and appliances. To ensure proper operation of smart metering, a reliable communication infrastructure plays a crucial role. Power line communication (PLC) is regarded as a promising candidate that will ful�l the requirements of smart grid applications. It is also the only wired technology which has a deployment cost comparable to wireless communication. PLC is most commonly used in the low-voltage (LV) power network which includes indoor power networks and the outdoor LV distribution networks. In this thesis we consider using PLC in the indoor power network to support the communication between the smart meter and a variety of appliances that are connected to the network. Power line communication (PLC) system design in indoor power network is challenging due to a variety of channel impairments, such as time-varying frequency-selective channel and complex impulsive noise scenarios. Among these impairments, the timevarying channel behaviour is an interesting topic that hasn't been thoroughly investigated. Therefore, in this thesis we focus on investigating this behaviour and developing a low-cost but reliable PLC system that is able to support smart metering applications in indoor environments. To aid the study and design of such a system, the characterisation and modelling of indoor power line channel are extensively investigated in this thesis. In addition, a exible simulation tool that is able to generate random time-varying indoor power line channel realisations is demonstrated. Orthogonal frequency division modulation (OFDM) is commonly used in existing PLC standards. However, when it is adopted for time-varying power line channels, it may experience signi�cant intercarrier interference (ICI) due to the Doppler spreading caused by channel time variation. Our investigation on the performance of an ordinary OFDM system over time-varying power line channel reveals that if ICI is not properly compensated, the system may su�er from severe performance loss. We also investigate the performance of some linear equalisers including zero forcing (ZF), minimum mean squared error (MMSE) and banded equalisers. Among them, banded equalisers provide the best tradeo� between complexity and performance. For a better tradeo� between complexity and performance, time-domain receiver windowing is usually applied together with banded equalisers. This subject has been well investigated for wireless communication, but not for PLC. In this thesis, we investigate the performance of some well-known receiver window design criteria that was developed for wireless communication for time-varying power line channels. It is found that these criteria do not work well over time-varying power line channels. Therefore, to �ll this gap, we propose an alternative window design criterion in this thesis. Simulations have shown that our proposal outperforms the other criteria

The Environmental Impacts of Radio Frequency and Power Line Communication for Advanced Metering Infrastructures in Smart Grids

In the neighborhood area network (NAN), the advanced metering infrastructure (AMI) enables a bidirectional connection between the smart meter (SM) and the data concentrator (DC). Sensors, such as smart meter nodes or environmental sensor nodes, play a crucial role in measuring and transmitting data to central units for advanced monitoring, management, and analysis of energy consumption. Wired and wireless communication technologies are used to implement the AMI-NAN. This paper delves into a novel approach for optimizing the choice of communication medium, air for radio frequency (RF) or power lines for power line communication (PLC), between the SM and DC in the context of the AMI-NAN. The authors methodically select the specific technologies, RF and NB-PLC (narrowband power line communication), and meticulously characterize their attributes. Then, a comparative analysis spanning rural, urban, and industrial settings is conducted to evaluate the proposed method. The overall reliability performance of the AMI-NAN system requires a packet error rate (PER) lower than 10%. To this end, an efficient approach is introduced to assess and enhance the reliability of NB-PLC and RF for AMI-NAN applications. Simulation results demonstrate that wireless communication is the optimal choice for the rural scenario, especially for a signal-to-noise ratio (SNR) lower than 25 dB. However, in urban environments characterized by higher SNR values and moderately dense networks, NB-PLC gains prominence. In denser networks, it outperforms wireless communication, exhibiting a remarkable 10 dB gain for a bit error rate (BER) of 10−3. Moreover, in industrial zones characterized by intricate network topologies and non-linear loads, the power line channel emerges as the optimal choice for data transmission

Robust wireless sensor network for smart grid communication : modeling and performance evaluation

Our planet is gradually heading towards an energy famine due to growing population and industrialization. Hence, increasing electricity consumption and prices, diminishing fossil fuels and lack significantly in environment-friendliness due to their emission of greenhouse gasses, and inefficient usage of existing energy supplies have caused serious network congestion problems in many countries in recent years. In addition to this overstressed situation, nowadays, the electric power system is facing many challenges, such as high maintenance cost, aging equipment, lack of effective fault diagnostics, power supply reliability, etc., which further increase the possibility of system breakdown. Furthermore, the adaptation of the new renewable energy sources with the existing power plants to provide an alternative way for electricity production transformed it in a very large and complex scale, which increases new issues. To address these challenges, a new concept of next generation electric power system, called the "smart grid", has emerged in which Information and Communication Technologies (ICTs) are playing the key role. For a reliable smart grid, monitoring and control of power system parameters in the transmission and distribution segments are crucial. This necessitates the deployment of a robust communication network within the power grid. Traditionally, power grid communications are realized through wired communications, including power line communication (PLC). However, the cost of its installation might be expensive especially for remote control and monitoring applications. More recently, plenty of research interests have been drawn to the wireless communications for smart grid applications. In this regard, the most promising methods of smart grid monitoring explored in the literature is based on wireless sensor network (WSN). Indeed, the collaborative nature of WSN brings significant advantages over the traditional wireless networks, including low-cost, wider coverage, self-organization, and rapid deployment. Unfortunately, harsh and hostile electric power system environments pose great challenges in the reliability of sensor node communications because of strong RF interference and noise called impulsive noise. On account of the fundamental of WSN-based smart grid communications and the possible impacts of impulsive noise on the reliability of sensor node communications, this dissertation is supposed to further fill the lacking of the existing research outcomes. To be specific, the contributions of this dissertation can be summarized as three fold: (i) investigation and performance analysis of impulsive noise mitigation techniques for point-to-point single-carrier communication systems impaired by bursty impulsive noise; (ii) design and performance analysis of collaborative WSN for smart grid communication by considering the RF noise model in the designing process, a particular intension is given to how the time-correlation among the noise samples can be taken into account; (iii) optimal minimum mean square error (MMSE)estimation of physical phenomenon like temperature, current, voltage, etc., typically modeled by a Gaussian source in the presence of impulsive noise. In the first part, we compare and analyze the widely used non-linear methods such as clipping, blanking, and combined clipping-blanking to mitigate the noxious effects of bursty impulsive noise for point-to-point communication systems with low-density parity-check (LDPC) coded single-carrier transmission. While, the performance of these mitigation techniques are widely investigated for multi-carrier communication systems using orthogonal frequency division multiplexing (OFDM) transmission under the effect of memoryless impulsive noise, we note that OFDM is outperformed by its single-carrier counterpart when the impulses are very strong and/or they occur frequently, which likely exists in contemporary communication systems including smart grid communications. Likewise, the assumption of memoryless noise model is not valid for many communication scenarios. Moreover, we propose log-likelihood ratio (LLR)-based impulsive noise mitigation for the considered scenario. We show that the memory property of the noise can be exploited in the LLR calculation through maximum a posteriori (MAP) detection. In this context, provided simulation results highlight the superiority of the LLR-based mitigation scheme over the simple clipping/blanking schemes. The second contribution can be divided into two aspects: (i) we consider the performance analysis of a single-relay decode-and-forward (DF) cooperative relaying scheme over channels impaired by bursty impulsive noise. For this channel, the bit error rate (BER) performances of direct transmission and a DF relaying scheme using M-PSK modulation in the presence of Rayleigh fading with a MAP receiver are derived; (ii) as a continuation of single-relay collaborative WSN scheme, we propose a novel relay selection protocol for a multi-relay DF collaborative WSN taking into account the bursty impulsive noise. The proposed protocol chooses the N’th best relay considering both the channel gains and the states of the impulsive noise of the source-relay and relay-destination links. To analyze the performance of the proposed protocol, we first derive closed-form expressions for the probability density function (PDF) of the received SNR. Then, these PDFs are used to derive closed-form expressions for the BER and the outage probability. Finally, we also derive the asymptotic BER and outage expressions to quantify the diversity benefits. From the obtained results, it is seen that the proposed receivers based on the MAP detection criterion is the most suitable one for bursty impulsive noise environments as it has been designed according to the statistical behavior of the noise. Different from the aforementioned contributions, talked about the reliable detection of finite alphabets in the presence of bursty impulsive noise, in the thrid part, we investigate the optimal MMSE estimation for a scalar Gaussian source impaired by impulsive noise. In Chapter 5, the MMSE optimal Bayesian estimation for a scalar Gaussian source, in the presence of bursty impulsive noise is considered. On the other hand, in Chapter 6, we investigate the distributed estimation of a scalar Gaussian source in WSNs in the presence of Middleton class-A noise. From the obtained results we conclude that the proposed optimal MMSE estimator outperforms the linear MMSE estimator developed for Gaussian channel

Latency Optimization in Smart Meter Networks

In this thesis, we consider the problem of smart meter networks with data collection to a central point within acceptable delay and least consumed energy. In smart metering applications, transferring and collecting data within delay constraints is crucial. IoT devices are usually resource-constrained and need reliable and energy-efficient routing protocol. Furthermore, meters deployed in lossy networks often lead to packet loss and congestion. In smart grid communication, low latency and low energy consumption are usually the main system targets. Considering these constraints, we propose an enhancement in RPL to ensure link reliability and low latency. The proposed new additive composite metric is Delay-Aware RPL (DA-RPL). Moreover, we propose a repeaters’ placement algorithm to meet the latency requirements. The performance of a realistic RF network is simulated and evaluated. On top of the routing solution, new asynchronous ordered transmission algorithms of UDP data packets are proposed to further enhance the overall network latency performance and mitigate the whole system congestion and interference. Experimental results show that the performance of DA-RPL is promising in terms of end-to-end delay and energy consumption. Furthermore, the ordered asynchronous transmission of data packets resulted in significant latency reduction using just a single routing metric