The emerging Internet of Things (IoT) and bidirectional communications in smart grid are expected to improve smart grid capabilities and electricity management. Because of massive number of IoT devices in smart grid, size of the data to be transmitted increases, that demands a high data rate to meet the real-time smart grid communication requirement. Sub-6 GHz, millimeter-wave (mmWave) technologies, and massive multiple-input multiple-output (MIMO) technologies can meet high data rate demands. However, IoT enabled smart grid is still subject to various security challenges such as eavesdropping, where attackers attempt to overhear the transmitted signals and the jamming attack, where the attacker perturbs the received signals at the receiver. In this paper, our goal is to investigate jamming and eavesdropping attacks while improving secrecy capacity for smart grid communications. Specifically, we propose to employ a hybrid beamforming design for wireless communications in smart energy grid. In previous works, the secrecy capacity is increased by randomly augmenting the source power or setting the system combiners. Unlike state-of-the-art, we design and evaluate the Gradient Ascent algorithm to search for the best combiners/waveform that maximizes the secrecy capacity in smart grid communications. We also study two different optimization scenarios by considering both fixed and variable transmit power. Numerical results are used for performance evaluation and supporting our formal analysis.
The emerging Internet of Things (IoT) and bidirectional communications in smart grid are expected to improve smart grid capabilities and electricity management. Because of massive number of IoT devices in smart grid, size of the data to be transmitted increases, that demands a high data rate to meet the real-time smart grid communication requirement. Sub-6 GHz, millimeter-wave (mmWave) technologies, and massive multiple-input multiple-output (MIMO) technologies can meet high data rate demands. However, IoT enabled smart grid is still subject to various security challenges such as eavesdropping, where attackers attempt to overhear the transmitted signals and the jamming attack, where the attacker perturbs the received signals at the receiver. In this paper, our goal is to investigate jamming and eavesdropping attacks while improving secrecy capacity for smart grid communications. Specifically, we propose to employ a hybrid beamforming design for wireless communications in smart energy grid. In previous works, the secrecy capacity is increased by randomly augmenting the source power or setting the system combiners. Unlike state-of-the-art, we design and evaluate the Gradient Ascent algorithm to search for the best combiners/waveform that maximizes the secrecy capacity in smart grid communications. We also study two different optimization scenarios by considering both fixed and variable transmit power. Numerical results are used for performance evaluation and supporting our formal analysis.
Nowadays, the Internet of Things (IoT) acts as a key enabler for smart cities, intelligent transportation systems, precision medicine, smart grids, etc. However, the computing power of IoT nodes is weak, and encryption algorithms cannot be used to ensure the secure transmission of data because of the high complexity. In recent years, the emerging technologies of wireless powered communication network (WPCN) and physical layer security (PLS) are regarded as potential solutions to allow IoT nodes to harvest energy from radio frequency (RF) and ensure secure data delivery. The secrecy rate, which is defined as the difference of main channel capacity and eavesdropping channel capacity, represents the secure data delivery ability. How to maximize the secrecy rate with the rather limited energy for IoT network is a challenging problem. In this paper, we formulate the secrecy rate maximization problem as an optimization problem. We solve this problem by two steps: using one-dimension research to find the optimal energy harvesting duration and find the closed-form solution for transmission power and transmission duration for every node. Compared with the heuristic algorithm, the proposed algorithm can obtain better performance from secrecy rate perspective.
Backscatter communication (BackCom) is widely adopted in Internet of Things (IoT) thanks to its characteristics of low power consumption and low cost. However, it is vulnerable to jamming due to double channel fading of backscattering signal, and the lack of encryption capability in tags increases the risk of eavesdropping. In this paper, we propose a monostatic BackCom system with a multi-antenna reader under hybrid attack, which leverages artificial noise (AN) to degrade eavesdropper’s channel capacity. We also design the transmit beamforming and the combiner to enhance the secrecy rate of the system. Specifically, we formulate a secrecy rate maximization problem with transmit power constraint, which is difficult to solve due to its non-convexity and coupled variables. Hence, we divide it into two subproblems through decoupling the variables and solve them alternately to obtain an overall suboptimal solution. Finally, our numerical results validate our optimization scheme by comparing it with selected benchmarks and showing the fast convergence speed of the proposed algorithm.
With the exponential increase of interconnected communicating devices which make up the Internet of Things (IoT), securing the network transmission and the fifth generation (5G) systems which is the bedrock for IoT concept actualization is becoming more and more challenging. One of the major attacks which poses a great risk to data transmission is the eavesdropper (Eve) attack which occurs in both single input, single output (SISO), multiple input and multiple output (MIMO) systems. Thus, in this study, our focus is to establish a secured connection in a multiple-antenna transmission when the channel state information (CSI) of Eve is unknown to the network users. Our model comprises a secure wireless communication standard where Eve performs either optimal matched filtering (OMF) or a basic matched filtering (BMF) while the transmitting IoT node employs smart jamming strategy in order to compromise the activities of Eve. With respect to this and in attempt to realize maximum privacy, we examined the design of optimal jamming parameters. In the end, the numerical analysis of our investigation indicates that a substantial privacy advantage is achievable while utilizing only full-duplex jamming against using artificial noise from the transmitter only. However, a joint performance of both results shows a higher privacy improvement.
Integrating the Internet of Things (IoT) in smart grids has revolutionized the energy sector, enabling real-time data collection and efficient energy distribution. However, this integration also introduces significant security challenges, particularly data encryption. Traditional encryption algorithms used in IoT are vulnerable to various attacks, and the advent of quantum computing exacerbates these vulnerabilities. To address the above challenges, this paper proposes a novel encryption mechanism, the Quantum-Resistant Hybrid Encryption for IoT (QRHE-IoT), designed to enhance the security of communications in IoT-enabled smart grids. QRHE-IoT combines the strengths of symmetric and asymmetric encryption algorithms and incorporates quantum-resistant algorithms to provide robust security. This paper explains the QRHE-IoT mechanism, its theoretical basis, and how it addresses the security challenges in smart grid communications. It also presents the results of tests conducted to evaluate the effectiveness of QRHE-IoT in a simulated smart grid environment. The proposed QRHE-IoT mechanism presents a promising solution to these challenges, offering robust security for smart grid communications in the face of emerging threats, including quantum computing.
In this article, we consider physical-layer security (PLS) of the Internet-of-Things (IoT) communications based on hybrid automatic repeat request (HARQ) protocols in multiple-input single-output single-eavesdropper (MISOSE) channels. Owing to the reciprocity of wireless channels, a negative acknowledge frame can be used to obtain the channel state information (CSI) from a source with multiple antennas to an IoT destination device, and this CSI of a legitimate link is used for beamforming for the next transmission round (TR). Therefore, a higher secrecy rate can be expected from retransmissions with beamforming based on the CSI as compared to the first TR without CSI. To evaluate the secrecy throughput under time-invariant and time-varying channels, connection and secrecy outage probabilities (OPs) are derived. By exploiting the characteristics of the OPs, we suggest an approximated secrecy throughput. We then consider the optimization of the approximated secrecy throughput considering the rate parameters for legitimate and eavesdropping links. With an alternating optimization approach, an algorithm to find convergent system parameters, i.e., the rates for legitimate and eavesdropping links, is proposed. Moreover, an asymptotic analysis with the large number of transmit antennas indicates an interesting behavior of the secrecy rate with regard to the number of TRs. The analytical results are verified by rigorous numerical simulations and they can serve as a useful guideline to those involved in the design of secure IoT communication systems with HARQ in MISOSE channels.
Physical-layer security (PLS) has attracted much attention in wireless communications and has been considered one of the main candidates for enhancing wireless security in future 6G networks. Recent studies in the PLS area have focused on investigating and analyzing the characteristics of secure transmissions in multiuser networks (e.g., the massive number of Internet of Things (IoT) devices in 6G networks). Due to the difficulty of obtaining the exact secrecy capacity region in wireless multiuser networks, several alternative methods are used to characterize the secrecy performance of multiuser networks. For example, we can analyze the secrecy sum-rate scaling in terms of the number of users based on multiuser diversity (MUD). In this paper, we propose an opportunistic user scheduling scheme that achieves optimal MUD gain, combined with a power control mechanism for reducing information leakage to multiple eavesdroppers in wireless networks. The proposed scheme considers multiuser transmissions in one scheduling time slot by adopting orthogonal random beamforming at the receiver to exploit the full degrees-of-freedom gain with an assumption that each user (or IoT device) is equipped with a single antenna, and base station and eavesdroppers have multiple antennas. The main contribution of this paper is to derive the analytic result of the achievable secrecy sum-rate scaling in a high signal-to-noise ratio (SNR) regime. We evaluate the performance of the proposed scheduling scheme with a power control mechanism through simulations with both internal and external eavesdropping scenarios. We further discuss the extensibility of our analysis to various applications such as satellite communications and IoT networks.