Minimum Secrecy Rate Research Articles

Rate splitting multiple access for UAV Secure Communication Systems with Friendly Jamming

A rate splitting multiple access (RSMA)-based dual-unmanned aerial vehicle (UAV) secure communication system is proposed in this paper, where one UAV is deployed to communicate with ground users, while the other UAV is dispatched to transmit the jamming signal to a ground eavesdropper. Considering the limited energy of UAV batteries, the minimum secrecy rate is maximized via optimizing RSMA precoding matrix and trajectories of UAVs under the constraint of UAV energy consumption. To address the complexity arising from coupled variables, the optimization problem is decomposed into two equivalent subproblems: precoding matrix optimization and UAV trajectory design. This decomposition is achieved using the block coordinate descent method. Next, the subproblems are transformed into convex forms by using semidefinite relaxation and successive convex approximation techniques, which are iteratively solved until convergence. Simulation results show that the secrecy performance of RSMA scheme is superior to that of the benchmark schemes, Specifically, the average secrecy rate of the RSMA scheme is approximately 22% and 10.8% higher than that of the NOMA and TDMA schemes, respectively.

Secure Transmission in NOMA-Enabled Industrial IoT With Resource-Constrained Untrusted Devices

The security of confidential information associated with devices in the industrial Internet of Things (IIoT) network is a serious concern. This article focuses on achieving a non-orthogonal multiple access (NOMA)-enabled secure IIoT network in the presence of untrusted devices by jointly optimizing the resources, such as decoding order and power allocated to devices. Assuming that the devices are resource-constrained for performing perfect successive interference cancellation (SIC), we characterize the residual interference at receivers with the linear model. Firstly, considering all possible decoding orders in an untrusted scenario, we obtain secure decoding orders that are feasible to obtain a positive secrecy rate for each device. Then, under the secrecy fairness criterion, we formulate a joint optimization problem of maximizing the minimum secrecy rate among devices. Since the formulated problem is non-convex and combinatorial, we first obtain the optimal secure decoding order and then solve it for power allocation by analyzing Karush-Kuhn-Tucker points. Thus, we provide the closed-form global-optimal solution of the formulated optimization problem. Numerical results validate the analytical claims and demonstrate an interesting observation that the conventional decoding order and assigning more power allocation to the weak device, as presumed in many works on NOMA, is not an optimal strategy from the secrecy fairness viewpoint. Also, the average percentage gain of about <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$22.75\%$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$50.58\%$</tex-math></inline-formula> , <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$94.59\%$</tex-math></inline-formula> , and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$98.16\%$</tex-math></inline-formula> , respectively, is achieved by jointly optimized solution over benchmarks ODEP (optimal decoding order, equal power allocation), ODFP (optimal decoding order, fixed power allocation), FDEP (fixed decoding order, equal power allocation), and FDFP (fixed decoding order, fixed power allocation).

Improved physical layer secrecy fairness in a realistic indoor NOMA VLC network under users’ mobility

This paper investigates the improvement of the secrecy rate fairness in a cellular non-orthogonal multiple access (NOMA) visible light communication (VLC) network. We formulate the users’ secrecy rate by taking into account the users (legitimate and illegitimate) mobility according to the random way-point (RWP) model. We propose an optimization problem to maximize the minimum secrecy rate for two legitimate users per cell, and then we generalize it for an arbitrary number of users. Moreover, utilizing secrecy considerations, we customize two well-known power allocation methods of fixed power allocation (FPA) and gain ratio power allocation (GRPA) as benchmarks for comparison of the proposed maximization power allocation method. Our numerical results demonstrate the superiority of the proposed power allocation algorithm compared with FPA and GRPA methods. Moreover, for the higher number of users, our results indicate the advantages of the proposed algorithm over modified FPA and GRPA methods. Finally, we investigate the effect of the optical receiver’s field of view fluctuations on the performance of the VLC network.

Security-Reliability Tradeoff in RSMA-Based Communications Against Eavesdropper Collusion

This work exploits secure beamforming for achieving security-reliability tradeoff in rate splitting multiple access (RSMA)-based communications against eavesdropper collusion. Considering user fairness, we maximize the minimum secrecy rate (MSR) among all legitimate users subject to the quality of service (QoS) constraints and transmit power constraint. A feasibility check problem is first presented to avoid infeasible cases. Then, a successive convex approximation-based algorithm is proposed to iteratively optimize the beamforming design. Numerical results show that the proposed RSMA-based design outperforms the baseline design in terms of MSR within certain QoS requirement ranges to trade security for reliability by balancing the power allocated to the common stream and private streams. And the performance advantage enlarges as the number of collusive eavesdroppers increases.

Secure Resource Allocations for Polarization-Enabled Multiple-Access Cooperative Cognitive Radio Networks With Energy Harvesting Capability

We address secure communications over energy-harvesting based orthogonal frequency-division multiple-access (OFDMA) cooperative cognitive radio networks, where one primary user (PU) cooperates with several size-limited secondary users (SUs) in terms of both information transmission and energy harvesting. To improve spectrum utilization and ensure that SU transmitters can harvest as much energy as possible, we let the size-limited SUs be equipped with orthogonally dual-polarized antennas (ODPAs). Based on these setting-ups, we propose the polarization-enabled two-phase cooperative framework, where SU transmitters first apply the power splitting technique to harvest energy from radio frequency (RF) signals radiated by the PU, and then use the harvested energy to concurrently transmit their own and the PU’s data over the same subcarriers. Under our proposed framework, we develop three secure resource allocation schemes for scenarios when SUs are untrusted users, which implies that each SU may overhear the PU’s and the other SUs’ confidential information. For these scenarios, which has hardly been studied, we jointly optimize the allocation of relays, subcarriers, power splitting ratios, and powers when SUs adopt the decode-and-forward (DF) strategy or the amplify-and-forward (AF) strategy to relay the PU’s information, with the objective to maximize the total secrecy rate of all SUs while guaranteeing the PU’s minimum secrecy rate. Finally, we validate and evaluate our proposed cooperative framework and secure resource allocation schemes through numerical analyses.

Jamming-Enhanced Secure UAV Communications With Propulsion Energy and Curvature Radius Constraints

A multi-unmanned aerial vehicles (UAVs)-aided secure communication network is studied, where multiple information UAVs carrying temporary aerial base stations transmit confidential information to multiple authorized receivers (ARs), and a jammer UAV is employed to send artificial noise to multiple unauthorized receivers (URs) for mitigating information leakage. Some practical constrains including the inter-UAV interference among the information UAVs and the jammer UAV, the maximal available propulsion energy at UAVs, and the curvature radius limitations of UAVs' trajectories are concurrently taken into account. In order to maximize the minimum secrecy rate among the ARs, the AR scheduling, the UAVs' power allocation and the trajectories of UAVs are jointly optimized by formulating a multi-variable optimization problem. To solve the non-convex problem efficiently, we present a block coordinate descent (BCD)-based approach, where the penalty dual decomposition (PDD)-based algorithm is designed to optimize the AR scheduling, and successive convex approximation (SCA)-based algorithm is proposed to optimize the UAVs' power allocation and the trajectories of UAVs. The complexity of the presented BCD-based approach is analyzed, which achieves polynomial complexity. Simulation results show that imposing curvature radius limitations on the UAVs' trajectory design is effective to avoid sharp turning of UAVs. Moreover, as curvature radius increases, the system max-min secrecy rate decreases. Besides, the secrecy rate performance of the system can be enhanced by exploiting one jammer UAV to interfere with the URs.

Minimum secrecy rate maximization for multiple peer-to-peer communications in two-way relaying networks

We investigate physical layer security for multi-user peer-to-peer relay networks, where a secure user pair and other unclassified users exchange information only through a multi-antenna relay in the presence of a multi-antenna eavesdropper. Our aim is to obtain the optimal values for variables of user transmit power and the relay beamforming matrix by solving the minimum secrecy rate maximization problem under specific constraints. We assume scenarios in which the eavesdropper’s channel state information is and is not available. Mathematically, the optimization problem raised in the first scenario is nonlinear and non-convex. The relay adopts a null space beamforming technique to facilitate the problem and guarantee secrecy. Also, we decouple it into two subproblems and solve them using inequality semi-definite programming and nonlinear optimization techniques to find solutions for variables. Also, the complexity of the proposed algorithms is analyzed and its convergency is proved by simulation. In the second scenario, we utilize an artificial noise-aided secure relay beamforming scheme. The problem is equivalent to the problem of assigning maximum power to the artificial noise evaluated by the secrecy outage probability concept. Finally, simulations demonstrate the validity of the proposed methods.

Rate-Splitting Multiple Access for Intelligent Reflecting Surface-Aided Secure Transmission

In this letter, we study a rate-splitting multiple access (RSMA)-based intelligent reflecting surface (IRS)-aided multi-user multiple-input single-output (MISO) secure communication system with a potential eavesdropper (Eve). Aiming to maximize the minimum secrecy rate (SR) among all the legitimate users (LUs), a design problem for jointly optimizing the transmit beamforming with artificial noise (AN), the IRS beamforming, and the secrecy common rate allocation is formulated. Since the design problem is highly non-convex with coupled optimization variables, we develop a computationally efficient algorithm based on the alternating optimization (AO) technique to solve it suboptimally. Numerical results demonstrate that the proposed design can significantly improve the max-min SR over the benchmark schemes without IRS or adopting other multiple access techniques. In particular, employing the RSMA strategy can substantially reduce the required numbers of IRS elements for achieving a target level of secrecy performance compared with the benchmark schemes.

IRS-Assisted Physical Layer Security for 5G Enabled Industrial Internet of Things

5G is a key enabler of Industrial Internet of Things (IIoT) that provides seamless connectivity between machines, sensors and computing servers. Security and privacy are major concerns for 5G enabled IIoT. Physical Layer Security (PLS) is a promising technique that can enhance the security of 5G enabled IIoT. In this paper, we present an IRS-assisted PLS scheme for 5G enabled IIoT that improves the weighted secrecy sum-rate (WSSR) of the industrial wireless network, where eavesdroppers are present around the facility. The key idea is to jointly optimize active and passive beamforming vectors to increase the secrecy rate at the user. To maximize WSSR, we use the stable matching algorithm that optimally assigns IRSs for secure data sharing between industrial units. Simulation results show that the proposed scheme enhances the WSSR performance by 40% and minimum secrecy rate by 25% as compared to the random and maximum weight matching schemes, respectively.

SecBoost: Secrecy-Aware Deep Reinforcement Learning Based Energy-Efficient Scheme for 5G HetNets

In this paper, we propose a secrecy-aware energy-efficient scheme for a two-tier heterogeneous network (HetNet), consisting of a sub-6 GHz macrocell and multiple millimeter wave (mmWave) picocells. Each picocell is assumed to have several users and an eavesdropper (Eve) which intercepts the signal of the picocell users. In the proposed scheme, firstly, to maximize the secrecy energy-efficiency (SEE) of picocell users, a joint optimization problem of power control, channel allocation, and beamforming is formulated by considering the minimum secrecy rate and signal-to-interference-plus-noise ratio (SINR) constraints. Due to the non-convex nature of the aforementioned optimization problem in a highly dynamic HetNet environment, we transform it into a reinforcement learning (RL) problem using the Markov decision process (MDP). Then, a multi-agent reinforcement learning (MARL) technique is used to obtain the maximum long-term reward. Moreover, we propose a multi-agent cooperative deep reinforcement learning (DRL) scheme known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SecBoost</i> to solve the MDP with large number of action and state spaces. It uses the dueling and double-Q architecture of dueling double deep Q-network (D3QN) to optimize power control, channel allocation, and beamforming vectors to maximize the SEE of picocells. Also, prioritized experience replay is used to increase the sampling efficiency of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SecBoost</i> . The SEE performance of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SecBoost</i> is compared with MARL, multi-agent deep Q-network (MA-DQN), state-of-the-art joint beamforming based secrecy energy efficiency maximization (JBF-SEEM) scheme, and one-time pad based encrypted data transmission (O-EDT). Simulation results demonstrated that the proposed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">SecBoost</i> scheme achieves 14.7%, 8.33%, 30%, and 69% better average SEE in comparison to MARL, MA-DQN, JBF-SEEM, and O-EDT schemes, respectively, which reveals its effectiveness in improving SEE of picocells.

Interference Alignment for Physical Layer Security in Multi-User Networks With Passive Eavesdroppers

We investigate the physical layer security (PLS) in multi-user interference networks. In particular, we consider secure transmission from a legitimate source (Alice) to a legitimate destination (Bob), coexisting with multiple passive eavesdroppers (Eves), as well as multiple legitimate transceivers. By assuming that only statistical channel state informations (CSIs) of Eves and local CSIs of legitimate users are available, we propose an artificial noise (AN) assisted interference alignment (IA) for security enhancement. Unlike traditional IA based security approaches which may result in secret signal cancellation, we design a modified alternating minimization (AM) scheme to overcome this threat, by incorporating the max-eigenmode beamforming (MEB) for secure transmission. Moreover, by partitioning the IA equation into three independent subsets and their combinations, a much tighter necessary condition for IA feasibility is established. We also provide guiding insights into the practical system designs, including useful guidelines for the selection of the dimension of AN. Furthermore, the power allocation ratio between the secret signal and the AN signal is optimized to minimize the secrecy outage probability (SOP), subject to a minimum secrecy rate constraint. Numerical results demonstrate that our design can enhance both quality and security of the secret signal, and thus is suitable and reliable for PLS in interference networks.

Secure wireless communications in the multi-user MISO interference channel assisted by multiple reconfigurable intelligent surfaces

This paper exploits reconfigurable intelligent surfaces (RIS) to enhance physical layer security (PLS) in a challenging radio environment. By adjusting the reflecting coefficients, RIS can provide a programmable wireless environment so that the electromagnetic wave can propagate in the desired way. Specifically, we consider a scenario where multiple user pairs communicate simultaneously over the same channel in a multiuser MISO interference channel and each pair of transceivers keeps their confidential information secret from other receivers. We investigate the secrecy rate balance of the system aided by multiple RISs and exploit the additional design degrees of freedom provided by the coordinated RISs to increase the secrecy capacity, achieving secrecy transmission. In particular, we adopt cooperative beamforming among the collaborative transmitters to maximize all users' minimum secrecy rate, achieving the secrecy rate balance. Due to the non-convexity of the formulated optimization problem, we propose alternating optimization (AO) to solve it iteratively and optimize active the transmit beamforming at the transmitters and passive phase shifts at the RISs based on positive semi-definite relaxation (SDR) and successive convex approximation (SCA). In each iteration, we solve a semi-definite programming (SDP) problem and finally get the optimal local solution to the optimization problem. Finally, the simulation results validate that the proposed algorithm is effective and the introduced RISs can significantly enhance the system secrecy performance compared to conventional baseline schemes.

Physical-Layer Security for Cache-Enabled C-RANs via Rate Splitting

This letter proposes a rate splitting (RS)-based secure transmit approach against multiple eavesdroppers in cache-enabled cloud radio access networks (C <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> -RANs). Unlike existing secure schemes, our approach uses the common stream for dual purposes, serving as the desired message for legitimate users (LUs) and artificial noise (AN) for eavesdroppers. We jointly optimize message splitting, remote radio head (RRH) clustering, and beamforming to maximize the minimum secrecy rate among all LUs and to meet the fronthaul capacity and transmit power per RRH constraints. We transform the formulated problem into two-tier alternating optimization by constructing accurate surrogates for the non-convex objective functions and constraints. We solve the outer-tier and inner-tier problems with the semi-closed-form expressions and the convex framework, respectively. The proposed transmit approach achieves significant gains over existing schemes.

Securing NOMA Networks by Exploiting Intelligent Reflecting Surface

This paper investigates the security enhancement of an intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) network, where a base station (BS) serves users securely with the assistance of distributed IRSs. Considering that eavesdropper’s instantaneous channel state information (CSI) is challenging to acquire in practice, we utilize secrecy outage probability (SOP) as the security metric. A problem of maximizing the minimum secrecy rate among users, by jointly optimizing transmit beamforming at the BS and phase shifts of the IRSs, is formulated. For a special case with a single-antenna BS, we derive the closed-form SOP expressions and propose a novel <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ring-penalty</i> based successive convex approximation (SCA) algorithm to design transmit power and phase shifts jointly. For a general multi-antenna BS case, we develop a Bernstein-type inequality based alternating optimization (AO) algorithm to solve the challenging problem. Numerical results demonstrate the advantages of the proposed algorithms over the baseline schemes. The results also show that: 1) the maximum secrecy rate is achieved when distributed IRSs share the reflecting elements equally; and 2) the distributed IRS deployment does not always outperform the centralized IRS deployment, due to the tradeoff between the number of IRSs and the reflecting elements equipped at each IRS.

Secure Transmission in NOMA-Aided Multiuser Visible Light Communication Broadcasting Network With Cooperative Precoding Design

In this paper, we study the secrecy performance of non-orthogonal multiple access (NOMA) enabled visible light communication (VLC) broadcast channels in the presence of an active eavesdropper (Eve). The considered VLC system consists of multiple separately distributed light-emitting diodes arrays and multiple randomly located users (UEs) in an indoor room. User clustering is conducted to reduce the implementation complexity of successive interference cancellations. Two cooperative precoding strategies based on zero-forcing (ZF) and maximum ratio transmission (MRT) are designed using the effective channel of each cluster. Based on each precoding strategy, a sum secrecy rate maximization problem is developed to obtain the near-optimal power allocation (PA) to strengthen UEs&#x2019; confidential transmission and degrade Eve&#x2019;s reception under minimum secrecy rate requirement, peak amplitude, non-negativity, and power constraints. To tackle the challenging non-convex problem for each precoding strategy, equivalent transformations and arithmetic-geometric mean approximation are conducted to convert the original problem into a series of geometric programming (GP) problems. Based on the reformulated problems, iterative algorithms are proposed to obtain near-optimal solutions by solving the GP problems through successive convex approximations. The convergence and complexity analysis of the proposed algorithms are studied. Simulation results show that the sum security performance of the proposed PA approach outperforms the conventional PA approaches in both ZF-based and MRT-based precoder schemes. The effectiveness of applying NOMA compared with the orthogonal multiple access-based scheme is also validated for the proposed system.

Intelligent Reflecting Surface-Aided Secure Broadcasting in Millimeter Wave Symbiotic Radio Networks

This paper investigates secure broadcast communications in intelligent reflecting surface (IRS)-aided millimeter wave (mmWave) symbiotic radio (SR) networks, where the IRS and the base station (BS) are cooperating. Specifically, the IRS assists secure broadcasting for the BS by smartly reconfiguring the phase shifts of the signals from the BS, while delivering its own information to an Internet-of-Things device (IoD). We aim at maximizing the minimum secrecy rate of multiple users by jointly designing the hybrid precoder at the BS and the passive beamformer at the IRS, subject to the rate constraints of both the multiple users and the IoD. The design is formulated as a non-convex optimization problem, which is intractable. To handle it, we develop a computationally efficient iterative algorithm based on the successive convex approximation, the efficiency and superiority of which have been validated by simulation results.

Maximizing the minimum secrecy rate of two-way relay networks

This paper concerns maximizing the minimum achievable secrecy rate in a two-way multi-antenna relay network in which two single-antenna nodes aim at exchanging their confidential messages with the help of some multi-antenna relays incorporating the Amplify and Forward (AF) strategy, while a single-antenna passive eavesdropper attempts to overhear the exchanged information. The communication is carried out in two hops. During the first hop, two source nodes transmit their information, hence, the relays get a combination of transmitted signals. Then, throughout the second hop, each relay applies a beamforming matrix to its received signal vector and broadcasts the resulting signal vector to the transmitting ends. Also, the eavesdropper overhears the exchanged information of two hops. The main goal persuaded in the current work is to devise proper beamforming strategies at the relays to improve the minimum secrecy rate. The problem is cast as an optimization problem, where it is shown that the underlying problem is not convex in general. Hence, two suboptimal approaches, called null-space (NS) and interference-leakage alignment (ILA) are devised, where using the so-called semi-definite relaxation (SDR) and Charnes–Cooper transformation techniques, the underlying problems are formulated as semi-definite programming (SDP) problems which can be numerically solved.

Robust Hybrid Precoding Design for Securing Millimeter-Wave IoT Networks Under Secrecy Outage Constraint

Hybrid precoding architecture, as a cost-effective approach for millimeter-wave (mmWave) communications, can achieve an excellent tradeoff between spectrum efficiency and hardware implementation complexity. However, the design of a robust hybrid precoding for improving the physical layer security (PLS), which is insensitive to the uncertainty of eavesdropper's channel state information (CSI), has not been well studied. This article for the first time designs a probabilistically robust hybrid precoding scheme for securing broadcast communications in Internet of Things (IoT) with eavesdropper's imperfect CSI. Specifically, considering the Gaussian CSI error model, we maximize the minimum secrecy rate of multiple IoT devices (IoDs) by jointly designing analog and digital precoders under the constraints in terms of secrecy outage probability and per IoD's information rate. The optimization problem is challenging due to the coupling of the analog and digital precoders, and the secrecy outage constraint. To handle these challenges, we first employ a conservative probability inequality to transform the secrecy outage probability constraint into a deterministic one. Then, by employing the penalty dual decomposition (PDD) method, we develop a novel iterative algorithm to convert the resultant nonconvex problem into a sequence of convex problems, which can guarantee the convergence to its Karush-Kuhn-Tucker (KKT) solution. Simulation results show that the proposed algorithm can achieve significant secrecy performance gains compared with the benchmark algorithm.

Hybrid Analog-Digital Precoder Design for Securing Cognitive Millimeter Wave Networks

Millimeter wave (mmWave) communications and cognitive radio technologies constitute key technologies of improving the spectral efficiency of communications. Hence, we conceive a hybrid secure precoder for enhancing the physical layer security of a cognitive mmWave wiretap channel, where a secondary transmitter broadcasts confidential information signals to multiple secondary users under the interference temperature constraint of the primary user (PU). The optimization problem is formulated as jointly optimizing the analog and digital precoder for maximizing the minimum secrecy rate of all the secondary users under practical constraints. In particular, our design satisfies the constraint on the maximum interference power received by multiple PUs, as well as the secondary users’ minimum quality-of-service (Qos), and the unit-modulus constraint on the analog precoder. Due to the non-convexity of the resultant objective function and owing to the coupling between the analog and digital precoder, the optimization problem formulated is nonconvex and nonlinear, hence it is very challenging to solve directly. Hence, we first transform it into a tractable form, and develop a penalty dual decomposition (PDD) based iterative algorithm to locate its Karush-Kuhn-Tucker (KKT) solution. Finally, we generalize the proposed PDD algorithm to a secure hybrid precoder design relying on practical finite-resolution phase shifters and show that the proposed PDD algorithm can be straightforwardly adapted to handle the scenario, where each PU is equipped with multiple antennas and the CSI of multiple eavesdroppers (Eves) is imperfectly known. Our simulation results validate the efficiency of the proposed iterative algorithm.

UAV Secure Downlink NOMA Transmissions: A Secure Users Oriented Perspective

This paper proposes a secure downlink multi-user transmission scheme enabled by a flexible unmanned aerial vehicle base station (UAV-BS) and non-orthogonal multiple access (NOMA). According to their heterogeneous service requirements, multiple legitimate users are categorized as security-required users (SUs) and quality of service (QoS)-required users (QUs), while these QUs can potentially act as internal eavesdroppers which are curious about the secrecy transmissions of SUs. In such a context, our goal is to maximize the achievable minimum secrecy rate among SUs through the joint optimization of user scheduling, power allocation, and trajectory design, subject to the QoS requirements of QUs and the mobility constraint of UAV-BS. Due to the non-convexity of the problem, an efficient iterative algorithm is firstly proposed, based on the alternative optimization (AO) and successive convex approximation (SCA) methods and along with a penalty-based algorithm to deal with the introduced binary integer variables, to obtain a sub-optimal solution. Then, we propose an SUs-oriented low-complexity algorithm by taking advantage of the inherent characteristics of the optimization problem, which can efficiently reduce the computational complexity and can act as a reasonable initial solution for the previous iterative algorithm to achieve better performance. Finally, the superiority of our proposed scheme compared with the conventional orthogonal multiple access (OMA) one is validated by numerical simulation results.