In this paper, we study a secure integrated sensing and communication (ISAC) system employing a full-duplex base station with sensing capabilities against a mobile proactive adversarial target—a malicious unmanned aerial vehicle (M-UAV). We develop a game-theoretic model to enhance communication security, radar sensing accuracy, and power efficiency. The interaction between the legitimate network and the mobile adversary is formulated as a non-cooperative Stackelberg game (NSG), where the M-UAV acts as the leader and strategically adjusts its trajectory to improve its eavesdropping ability while conserving power and avoiding obstacles. In response, the legitimate network, acting as the follower, dynamically allocates resources to minimize network power usage while ensuring required secrecy rates and sensing performance. To address this challenging problem, we propose a low-complexity successive convex approximation (SCA) method for network resource optimization combined with a deep reinforcement learning (DRL) algorithm for adaptive M-UAV trajectory planning through sequential interactions and learning. Simulation results demonstrate the efficacy of the proposed method in addressing security challenges of dynamic ISAC systems in 6G, i.e., achieving a Stackelberg equilibrium with robust performance while mitigating the adversary’s ability to intercept network signals.

This paper presents a secrecy performance study of a wiretap communication system with finite blocklength (FBL) transmissions over Rayleigh fading channels, based on the definition of an average information leakage (AIL) metric. We evaluate the exact and closed-form approximate AIL performance, assuming that only statistical channel state information (CSI) of the eavesdropping link is available. Then, we reveal an inherent statistical relationship between the AIL metric in the FBL regime and the commonly-used secrecy outage probability in conventional infinite blocklength communications. Aiming to improve the secure communication performance of the considered system, we formulate a blocklength optimization problem and solve it via a low-complexity approach. Next, we present numerical results to verify our analytical findings and provide various important insights into the impacts of system parameters on the AIL. Specifically, our results indicate that i) compromising a small amount of AIL can lead to significant reliability improvements, and ii) the AIL experiences a secrecy floor in the high signal-to-noise ratio regime.

Short-packet communication (SPC) and unmanned aerial vehicles (UAVs) are anticipated to play crucial roles in the development of 5G-and-beyond wireless networks and the Internet of Things (IoT). In this paper, we propose a secure SPC system, where a UAV serves as a mobile decode-and-forward (DF) relay, periodically receiving and relaying small data packets from a remote IoT device to its receiver in two hops with strict latency requirements, in the presence of an eavesdropper. This system requires careful optimization of important design parameters, such as the coding blocklengths of both hops, transmit powers, and the UAV’s trajectory. While the overall optimization problem is nonconvex, we tackle it by applying a block successive convex approximation (BSCA) approach to divide the original problem into three subproblems and solve them separately. Then, an overall iterative algorithm is proposed to obtain the final design with guaranteed convergence. Our proposed low-complexity algorithm incorporates robust trajectory design and resource management to optimize the effective average secrecy throughput of the communication system over the course of the UAV-relay’s mission. Simulation results demonstrate significant performance improvements compared to various benchmark schemes and provide useful design insights on the coding blocklengths and transmit powers along the trajectory of the UAV.

Physical-layer security (PLS) is a promising technique to complement more traditional means of communication security in beyond-5G wireless networks. However, studies of PLS are often based on ideal assumptions such as infinite coding blocklengths or perfect knowledge of the wiretap link’s channel state information (CSI). In this work, we study the performance of finite blocklength (FBL) transmissions using a new secrecy metric — the average information leakage (AIL). We evaluate the exact and approximate AIL with Gaussian signaling and arbitrary fading channels, assuming that the eavesdropper’s instantaneous CSI is unknown. We then conduct case studies that use artificial noise (AN) beamforming to analyze the AIL in both Rayleigh and Rician fading channels. The accuracy of the analytical expressions is verified through extensive simulations, and various insights regarding the impact of key system parameters on the AIL are obtained. Particularly, our results reveal that allowing a small level of AIL can potentially lead to significant reliability enhancements. To improve the system performance, we formulate and solve an average secrecy throughput (AST) optimization problem via both non-adaptive and adaptive design strategies. Our findings highlight the significance of blocklength design and AN power allocation, as well as the impact of their trade-off on the AST.

In this paper, we propose a secure short-packet communication (SPC) system involving an unmanned aerial vehicle (UAV)-aided relay in the presence of a terrestrial passive eavesdropper. The considered system, which is applicable to various next-generation Internet-of-Things (IoT) networks, exploits a UAV as a mobile relay, facilitating the reliable and secure exchange of intermittent short packets between a pair of remote IoT devices with strict latency. Our objective is to improve the overall secrecy throughput performance of the system by carefully designing key parameters such as the coding blocklengths and the UAV trajectory. However, this inherently poses a challenging optimization problem that is difficult to solve optimally. To address the issue, we propose a low-complexity algorithm inspired by the block successive convex approximation approach, where we divide the original problem into two subproblems and solve them alternately until convergence. Numerical results demonstrate that the proposed design achieves significant performance improvements relative to other benchmarks, and offer valuable insights into determining appropriate coding blocklengths and UAV trajectory.

Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in the Internet of Things (IoT). On the other hand, terahertz (THz)-enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G (B5G) wireless communications that promise a broad range of data-demand applications. In this article, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) toward multiple ground user equipments (UEs) in IoT networks. Specifically, the AP intends to send data to the scheduled UE, while unscheduled UEs may behave as potential adversaries. To protect information messages from the privacy preservation perspective, we aim to devise an energy-efficient multi-UAV covert communication scheme, where the UIRS is for reliable data transmissions, and an extra UAV is utilized as an aerial cooperative jammer, opportunistically generating artificial noise (AN) to degrade unscheduled UEs detection, leading to communication covertness improvement. This poses a novel max-min optimization problem in terms of minimum average energy efficiency (mAEE), aiming to improve covert throughput and reduce UAVs’ propulsion energy consumption, subject to satisfying some practical constraints such as the covertness requirements for which we obtain analytical expressions. Since the optimization problem is nonconvex, we tackle it via the block successive convex approximation (BSCA) approach to iteratively solve a sequence of approximated convex subproblems, designing the binary user scheduling, AP’s power allocation, maximum AN jamming power, IRS beamforming, and both UAVs’ trajectory and velocity planning. Finally, we present a low-complex overall algorithm for system performance enhancement with complexity and convergence analysis. Numerical results are provided to verify the analysis and demonstrate significant outperformance of our design over other existing benchmark schemes concerning the mAEE performance.

In this study, the authors investigate the security and the reliability performance of a two‐way relay‐based network, where a source–destination pair establishes secured communication through a wireless‐powered untrusted amplify‐and‐forward relay while employing a friendly jammer. The relay utilises the harvested energy from radio‐frequency signals sent by the sources to forward the received data; however, the friendly jammer employs that to generate and transmit noise‐like signals to confuse the curious relay. Two power transmission protocols, namely variable power transmission (VPT) and constant power transmission (CPT) at the jammer and relay are adopted. As a benchmark to highlight the performance advantages of employing a jammer, they also considered the case of zero power transmission (ZPT), where there is no jammer in the network. For the three scenarios, the intercept probability (IP) and the connection outage probability (COP), as well‐known secrecy criteria associated with the successful transmission are mathematically examined. Finally, the derived expressions are confirmed by comparison with Monte–Carlo simulations and furthermore, numerical examples are provided to demonstrate the effects of system parameters on the IP and the COP metrics. Specifically, they find that jammer's artificial noise distribution plays a paramount role in the secrecy performance of the considered system.

In this paper, we propose a self-dependent two-way secure communication where two sources exchange confidential messages via a wireless powered untrusted amplify-and-forward (AF) relay and friendly jammer (FJ). By adopting the time switching (TS) architecture at the relay, the data transmission is accomplished in three phases: Phase I) Energy harvesting by the untrusted relay and the FJ through non-information transmissions from the sources, Phase II) Information transmission by the sources and jamming transmissions from the FJ to reduce information leakage to the untrusted relay; and Phase III) Forwarding the scaled version of the received signal from the untrusted relay to the sources. For the proposed system, we derive a new closed-form lower bound expression for the ergodic secrecy sum rate (ESSR). Numerical examples are provided to demonstrate the impacts of different system parameters such as energy harvesting time, transmit signal-to-noise ratio (SNR) and the relay/FJ location on the secrecy performance. The numerical results illustrate that the proposed network with friendly jamming (WFJ) outperforms traditional one-way communication and the two-way without friendly jamming (WoFJ) policy.