The Internet of Things (IoT) depicts a bright future, where any devices having sensorial and computing capabilities can interact with each other. Among all existing technologies, the techniques for the fifth generation (5G) systems are the main driving force for the actualization of IoT concept. However, due to the heterogeneous environment in 5G networks and the broadcast nature of radio propagation, the security assurance against eavesdropping is a vital yet challenging task. In this paper, we focus on the transmission design for secure relay communications in IoT networks, where the communication is exposed to eavesdroppers with unknown number and locations. The randomize-and-forward relay strategy specially designed for secure multi-hop communications is employed in our transmission protocol. First, we consider a single-antenna scenario, where all the devices in the network are equipped with the single antenna. We derive the expression for the secrecy outage probability of the two-hop transmission. Following this, a secrecy-rate-maximization problem subject to a secrecy-outage-probability constraint is formulated. The optimal power allocation and codeword rate design are obtained. Furthermore, we generalize the above analyses to a more generic scenario, where the relay and eavesdroppers are equipped with multiple antennas. Numerical results show that the proper use of relay transmission can enhance the secrecy throughput and extend the secure coverage range.

Cyber-physical system (CPS), regarded as the next generation of engineered system, has the capability to interact with the real physical world. Applications of CPS span various fields such as medical monitoring, traffic control, and smart grid. With such widespread applications, privacy assurance is becoming more and more important since what the CPS connects are people and the real world. Any leakage of private information will cause serious consequences. In this paper, we focus on enhancing the secrecy of wireless communications in CPS by use of physical layer security techniques. Specifically, we study an amplify and forward (AF) relay network where all devices are equipped with a single antenna. We propose a privacy-enhanced waveform design approach aided by artificial noise (AN) to enhance the communication secrecy in a wireless environment with multipath receptions. First, we consider the case with perfect eavesdropper's channel state information (CSI). We optimize the AF coefficient for forwarding the informationbearing signal and the AN covariance to maximize the achievable secrecy rate. The optimal solution is obtained by solving a series of semidefinite programs. Then, a more practical scenario with imperfect eavesdropper's CSI is studied. We develop a robust waveform design method and obtain the lower bound of the achievable secrecy rate. Numerical results are presented to show the effectiveness of our proposed algorithms.

In this paper, we propose a high-altitude platform (HAP) and unmanned aerial vehicles (UAVs) collaboration framework in non-orthogonal multiple access (NOMA)-enabled Internet of Things (IoT) networks with the presence of an eavesdropping UAV. For the considered framework, we investigate the uplink secure transmission by optimizing channel allocation from UAVs to HAP, users’ power, and UAVs’ three-dimensional (3D) position. To solve this non-convex problem, we adopt the K-means cluster pair algorithm to divide paired users into different groups and each cluster can be served by a corresponding UAV. Then, the formulated optimization problem is decoupled into three subproblems and tackled iteratively based on the block coordinate descent (BCD) algorithm. Finally, simulation results verify that the proposed network architecture can achieve a higher secure rate, faster convergence evolution, and lower complexity in comparison with the current works.

Based on the concept of constructive interference (CI), multiuser interference (MUI) has recently been shown to be beneficial for communication secrecy. A few CI-based secure precoding algorithms have been proposed that use both the channel state information (CSI) and knowledge of the instantaneous transmit symbols. In this article, we examine the CI-based secure precoding problem with a focus on smart eavesdroppers that exploit statistical information gleaned from the precoded data for symbol detection. Moreover, the impact of correlation between the main and eavesdropper channels is taken into account. We first modify an existing CI-based precoding scheme to better utilize the destructive impact of the interference. Then, we point out the drawback of both the existing and the new modified CI-based precoders when faced with a smart eavesdropper. To address this deficiency, we provide a general principle for precoder design and then give two specific design examples. Finally, the scenario where the eavesdropper's CSI is unavailable is studied. Numerical results show that although our modified CI-based precoder can achieve a better energy-secrecy trade-off than the existing approach, both have a limited secrecy benefit. On the contrary, the precoders developed using the new CI-design principle can achieve a much improved tradeoff and significantly degrade the eavesdropper's performance.

Industrial Internet of Things (IIoT), regarded as an important technology for Industry 4.0, has the capability to connect massive IoT devices anywhere and at anytime in manufacturing industry. Enabling such a huge network requires message delivering among sensors, actuators, controllers, and the remote control to be seamless and reliable. However, IIoT wireless environment typically faces challenges such as blockage caused by IoT obstacles. To tackle the above issue, the unmanned aerial vehicle (UAV) and the reconfigurable intelligent surface (RIS) are exploited in this paper, which can provide favorable air-to-ground links and further rebuild the wireless channels. Moreover, the device-to-device (D2D) communication technique is introduced to enable direct information exchange between IoT devices. Specifically, we consider both the communication between the UAV and the cellular users (e.g., fixed IoT infrastructures) as well as the communication between D2D users (e.g., mobile IoT devices). Instead of only considering throughput, we focus on energy efficiency optimization for D2D users while guaranteeing the quality of service for cellular users, since energy-efficient transmission or green communication is important for IIoT scenarios. The transmit power, channel allocation parameters, and RIS’s reflection coefficients are jointly optimized to maximize energy efficiency for D2D users. To solve the formulated optimization problem, both centralized and distributed optimization algorithms based on deep neural networks are provided. Simulation results show that the introduction of RIS can significantly improve system performance. Moreover, the proposed algorithms can approximate the optimal solutions without the need of exhaustive search.

Among the plenty of studies on physical layer security, multi-antenna signal processing and nodes cooperation are two widely adopted techniques. However, in practical systems there are many single-antenna devices that do not support cooperative transmission either. To guarantee the information security in this scenario, we propose a novel transmission strategy that exploits the temporal characteristics of a multipath fading channel. Specifically, we apply this strategy to a time-reversal-based communication system. We consider a joint design of signal waveform and artificial noise. Based on this approach, specific transmission schemes are designed for the cases with and without eavesdropper's channel state information (CSI), respectively. The numerical results show the superiority of our proposed schemes in terms of security enhancement even when the eavesdropper's CSI is unavailable.