We examine a secure wireless communication system that is enabled by unmanned aerial vehicles (UAVs) in this research. In the wireless communication system with an eavesdropping UAV, we deploy a relay UAV to facilitate the transmission of confidential signals from the source station (denoted asS) to ground users. Additionally, we select an idle relay UAV to act as a cooperative jamming UAV, sending interference signals to the eavesdropping UAV. It is quite feasible that the eavesdropping UAV will leverage its mobility to improve the quality of its eavesdropping, making its trajectory unpredictable. First, to address the worst-case scenario for the ground user’s security performance, we assume the eavesdropping UAV approaches at the closest distance.We aim to maximize the worst secrecy rate under perfect CSI via designing the flight trajectory and transmission power of both the relay UAV and the jamming UAV. Second, we investigated the performance of the system’s secrecy outage probability under imperfect CSI. The presence of eavesdropping UAVs and the unpredictable nature of their environment makes traditional convex optimization methods mathematically complex for solving the trajectory optimization problem of the relay and jamming UAVs. To address this, we propose the Multi-Agent joint design trajectory and power (MAJDTP) algorithm based on the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm to optimize the flight trajectory and transmission power of both UAVs. During the design and training process, the relay and jamming UAVs are treated as agents to derive their optimal flight paths and transmission energy. Finally, our approach surpasses the benchmark algorithm, as demonstrated by the simulation results.

Ensuring signal confidentiality against eavesdroppers is particularly challenging, especially with imperfect channel state information (CSI). To address this, we propose a novel approach leveraging reconfigurable intelligent surfaces (RISs) to enhance security and optimize transmission performance. This paper focuses on secure communication in symbiotic radio (SR) systems by investigating cooperative jamming-assisted transmission with RISs, providing a robust solution to these challenges. RIS-I, acting as a secondary transmitter (STx), multicasts confidential signals from the primary transmitter (Alice) to a primary user (Bob), protecting against eavesdropping by Eve. Additionally, RIS-I transmits its own signals to a secondary user (SU) using backscattering radio technology. Meanwhile, RIS-II serves as a cooperative jammer, converting received confidential signals from Alice into jamming signals by strategically adjusting its reflection coefficients to disrupt Eve’s reception. These RISs can operate cooperatively; when RIS-II transmits as an STx, RIS-I functions as a cooperative jammer. We explore two scenarios: 1. With perfect CSI for the wiretap channel, we propose a joint SDR(Semi-definite relaxation)+MM(Minorization-maximization) optimization algorithm to simultaneously optimize Alice’s beamforming vector and the RISs’ reflection coefficients. 2. With imperfect CSI, we derive the secrecy outage probability formula and evaluate the scheme’s performance across different scenarios. Numerical results demonstrate that RIS-assisted cooperative jamming significantly enhances the secrecy rate and reduces the secrecy outage probability for Bob, outperforming traditional RIS-assisted SR systems.

This paper investigates a centralized cooperative cognitive radio network (CCRN) where a primary base station (PBS) transmits a message to a primary user while a secondary user transmitter (SU-Tx) function as a friendly jammer. The jammer sends jamming signals to protect the PBS’s messages from a potential eavesdropper (Eve). However, the SU-Tx also attempts to covertly transmit its own messages to a secondary user receiver using the allocated spectrum resource, contravening the PBS regulations. To address this issue, the PBS requests its partner CBS to help detect jammer’s behavior. Specifically, we propose a generative adversarial network (GAN) optimization framework that models the strategic game between the CBS monitoring and the covert transmission of cooperative jammers. We introduce a novel GAN-based beamforming design algorithm, termed GAN-BD, to determine the power allocation at the jammer for covert communication. Additionally, we develop the detection error probability (DEP) at the CBS and derive its expression using a hypothesis testing problem. Through extensive simulation results, we demonstrate that the proposed GAN-BD algorithm can achieve near-optimal solutions for conducting covert communication, leveraging knowledge of the current network environment and exhibiting rapid convergence capabilities. The simulation results highlight the effectiveness of our GAN-BD algorithm.

This paper examines integrating jamming and secondary signals for covert communications in cognitive radio networks (CRNs), aiming to enhance covertness by using jamming and secondary signals in an overlay cooperative CRN. The scenario involves a primary base station (PBS) transmitting to a primary user (PU), with a secondary user transmitter (SU-Tx) acting as a cooperative jammer to obscure the message from a malevolent secondary user named “Willie.” During idle intervals on the primary channel, the SU-Tx opportunistically accesses it to transmit secondary signals, reinforcing the covert communication of primary signals. The study quantifies the detection error probability (DEP) experienced by Willie, considering perfect and statistical channel state information (CSI) scenarios. In the perfect CSI scenario, optimization has two phases. Phase I aims to maximize the signals-to-interference-plus-noise ratio (SINR) of the PU, subject to the warden DEP exceeding a specified threshold. Phase II uses an iterative search algorithm to optimize beamforming vectors, enhancing SINR. In the statistical CSI scenario, the goal is to maximize effective transmission throughput (ETT), measuring the information transmitted from PBS to PU under covert constraints. Numerical results validate the theoretical analysis.

In this paper, we propose a trustworthy friendly jammer selection scheme with truth‐telling for wireless cooperative systems. We first utilize the reverse auction scheme to enforce truth‐telling as the dominant strategy for each candidate friendly jammer. Specifically, we consider two auction cases: (1) constant power (CP) case and (2) the utility of the BS maximization (UBM) case. In both cases, the reverse auction scheme enforces truth‐telling as the dominant strategy. Next, we introduce the trust category and trust degree to evaluate the trustworthiness of each Helper transmitter (Helper‐Tx). Specifically, an edge controller calculates the reputation value of each Helper‐Tx periodically using an additive‐increase multiplicative‐decrease algorithm by observing its jamming behavior. With the historical reputation values, the edge controller (EC) classifies a Helper‐Tx into one of four trust categories and calculates its trust degree. Then, the EC selects the best Helper‐Tx based on the trust category and trust degree. Lastly, we present numerical results to demonstrate the performance of our proposed jammer selection scheme.

In this paper, we investigate how to select a trust-worthy Helper as a friendly jammer in a wireless cooperative system (WCS). The selected Helper sends out artificial noise to interfere with an eavesdropper. To ensure that the selected Helper is trustworthy, we design a Dirichlet reputation-based framework and adopt the reputation score to evaluate the trustworthiness of a Helper. To calculate the reputation scores, we develop an artificial noise detection method based on the energy detection with multiple thresholds. According to the multiple-threshold energy detection method, we provide ratings with multiple graded levels (e.g., good-average-bad). In the Dirichlet reputation-based framework, the graded ratings are directly expressed and reflected in the derived reputation scores. Firstly, the a posteriori reputation score is computed by combining the a priori reputation score with the new ratings. Next, a point value is assigned to each rating and the normalized reputation score is computed. Finally, we adopt the normalized reputation score to select a trustworthy Helper as a friendly jammer. Numerical results are presented to demonstrate the performance of our proposed Dirichlet reputation-based framework.

Friendly jamming is an unconventional approach to secure wireless communications. Specifically, a friendly jammer transmits jamming signals to an eavesdropper while a legitimate transmitter is sending data. The jamming signals only interfere with the eavesdropper, and thus, prevent data from being disclosed to unintended parties. Mainstream jamming schemes adopt a continuous jamming strategy (CJS), where the jammer is required to constantly transmit jamming signals in the entire duration of the legitimate transmission. In certain scenarios, however, the CJS may lead to excessive jamming, and cause a waste of energy and the degradation of jamming efficiency. To address the drawbacks of the CJS, we propose the concept of an intermittent jamming strategy (IJS), where a jammer alternates between jamming and non-jamming modes during the legitimate transmission. In this paper, we study the feasibility of the IJS for physical layer security. We first introduce a new metric to jointly measure security requirements and energy costs. Next, we formulate and solve an optimization problem with respect to the jamming duration proportion and the jamming power. Finally, we verify the feasibility of the IJS through extensive simulation experiments under different modulation methods.

An underlay cognitive radio network (CRN) with non- orthogonal multiple access (NOMA) is a promising multiple access scheme to solve the problem of scarce spectrum. This novel NOMA-enabled underlay CRN can also enhance the transmission secrecy via employing the deliberately introduced interference. In this paper, we intend to investigate the secrecy capacity of a pair of primary users (PUs) and randomly deployed secondary users (SUs) in the NOMA- enabled underlay CRN. Considering an existing eavesdropper in the network, we derive a closed-form expression of the secrecy sum rate (SSR) of all SUs. Then, we further formulate an SSR optimization problem for both PUs and SUs and design a simulated annealing algorithm to find the optimal power allocation. Simulation results demonstrate that the secrecy performance of all NOMA-enabled SUs is higher than that of SUs with frequency division multiple access (FDMA). In other words, the use of the NOMA technology can improve the secrecy performance of the cognitive radio system.

In this paper, we investigate secure communications in energy harvesting enabled cooperative cognitive radio networks (CCRNs). In such CCRNs, a pair of primary users (PUs) can only communicate with each other through a relay. To protect data transmission between PUs, we propose a cooperative jamming strategy with energy harvesting technology. In the first phase, a PU as the source (PU-S) broadcasts signals, while another PU as the destination (PU-D) sends artificial noise (AN) and all secondary uses (SUs) harvest energy from the received mixed signals. In the second phase, one SU selected as a relay (SU-R) uses its harvested energy to forward PU's signals, while another SU selected as a jammer (SU-J) employs its harvested energy to send AN. According to this, we formulate a non-convex problem aiming to improve the secrecy rate of PUs and divide this problem into three optimization subproblems. Finally we provide a feasible joint solution by a two-tiered iterative algorithm. Numerical results demonstrate the secrecy performance of our proposed jamming strategy.

An online social network (OSN) is a platform that makes people communicate with friends, share messages, accelerate business, and enhance teamwork. In the OSN, privacy issues are increasingly concerned, especially in private message leaks in word‐of‐mouth. A user’s privacy may be leaked out by acquaintances without user’s consent. In this paper, an integrated system is designed to prevent this illegal privacy leak. In particular, we only use the method of space vector model to determine whether the user’s private message is really leaked. Canary traps techniques are used to detect leakers. Then, we define a trust degree mechanism to evaluate trustworthiness of a communicator dynamically. Finally, we set up a new message publishing system to determine who can obtain the message of publisher. Secrecy performance analysis is provided to verify the effectiveness of the proposed message publishing system. Accordingly, a user in social networks can check whether other users are trustworthy before sending their private messages.

A Mobile Social Network (MSN) is a typical Delay Tolerant Network (DTN) composed of mobile nodes with social characteristics. Routing design and optimization are difficult because of the fast topology changes in such network. However, realistic mobility trace shows that mobile nodes in MSNs generally visit a few locations called homes, frequently, while other locations are visited less frequently. In order to evaluate the influence of the home on the routing design and improve the delivery success ratio, we propose two novel home-based multi-copy routing protocols, HBMRZ and HBMR. In HBMRZ, we assume that the message holder has zero-knowledge about the destination when it delivers the message, while in HBMR, the message holder not only knows its own homes but also the destination. Nevertheless, both of the protocols can broadcast message on the basis of the known home information. In addition, extensive simulations are conducted. Numerical simulation demonstrates that it is important to exploit home factor in routing protocols for delivering the message accurately. By using home characteristic, HBMRZ and HBMR achieve a better performance on the delivery success ratio than existing MSN routing algorithms, including Epidemic and Spray&Wait.