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arXiv:2407.13973 · IEEE Internet of Things Journal

Joint Information and Jamming Beamforming for Securing IoT Networks With Ratesplitting

Bin Qiu, Wenchi Cheng, Wei Zhang

Published Sep 11, 2023• 9 citations
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Abstract

The goal of this paper is to address the physical layer (PHY) security problem for multi-user multi-input single-output (MU-MISO) Internet of Things (IoT) systems in the presence of passive eavesdroppers (Eves). To this end, we propose an artificial noise (AN)-aided rate-splitting (RS)-based secure beamforming scheme. Our design considers the dual use of common messages and places the research emphasis on hiding the private messages for secure communication. In particular, leveraging AN-aided RS-based beamforming, we aim to maximize the focused secrecy sum-rate (F-SSR) by jointly designing transmit information and AN beamforming while satisfying the desired received constraints for the private messages at IoT devices (IoDs), and per-antenna transmit power constraint at base station. Then, we proposed a two-stage algorithm to iteratively find the optimal solution. By transforming non-convex terms into linear terms, we first reformulate the original problem as a convex program. Next, we recast the optimization problem to an unconstrained problem to obtain the global optimal solutions. Utilizing the duality framework, we further develop an efficient algorithm based on a barrier interior point method to solve the reformulated problem. Simulation results validate the superior performance of our proposed schemes.

DOI
10.1109/jiot.2023.3313870

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A secure downlink transmission system which is exposed to multiple eavesdroppers and is appropriate for Internet of Things (IoT) applications is considered. A worst case scenario is assumed, in the sense that, in order to enhance their interception ability all eavesdroppers are located close to each other, near the controller and collude to form joint receive beamforming. For such a system, a novel cooperative nonorthogonal multiple access (NOMA) secure transmission scheme for which an IoT device with a stronger channel condition acts as an energy harvesting relay in order to assist a second IoT device operating under weaker channel conditions, is proposed and its performance is analyzed and evaluated. A secrecy sum rate (SSR) maximization problem is formulated and solved under three constraints: 1) transmit power; 2) successive interference cancellation; and 3) quality of service. By considering both passive and active eavesdroppers scenarios, two optimization schemes are proposed to improve the overall system SSR. On the one hand, for the passive eavesdropper scenario, an artificial noise-aided secure beamforming scheme is proposed. Since this optimization problem is nonconvex, instead of using traditional but highly complex, brute-force 2-D search, it is conveniently transformed into a convex one by using an epigraph reformulation. On the other hand, for the active multiantennas eavesdroppers’ scenario, the orthogonal-projection-based beamforming scheme is considered, and by employing the successive convex approximation method, a suboptimal solution is proposed. Furthermore, since for single antenna transmission the orthogonal-projection-based scheme may not be applicable a simple power control scheme is proposed. Various performance evaluation results obtained by means of computer simulations have verified that the proposed schemes outperform other benchmark schemes in terms of SSR performance.
In this paper, we consider max-min fairness for a downlink two-user multi-input single-output (MISO) system with imperfect channel state information available at transmitter (CSIT) taking into account the total power constraint and the physical layer security. To handle the worst-case channel uncertainty of a potential eavesdropper (PE), we study the robust secure resource allocation algorithm which maximizes the minimum achieved worst-case secrecy rate among single-antenna legitimate users. In contrast to existing schemes adopted in the literature, we propose a rate-splitting (RS)-based secure transmission scheme, which advocates the dual use of a common message serving both as a desired message and artificial noise (AN) for legitimate users and the PE, respectively. Considering the non-convex resource allocation algorithm design problem, we apply the majorization maximization (MM) method to obtain a suboptimal iterative algorithm. In each iteration, a rank-constrained semi-definite program (SDP) is solved optimally by SDP relaxation (SDR). Simulation results demonstrate that our proposed robust secure beamforming scheme in the MISO-RS secure transmission system outperforms that of several baselines.
This paper considers the physical layer security (PLS) and covertness of the signal transmission in a multiple-input single-output downlink adopting ultra-high reliability and low latency communication (URLLC). In the considered system, Alice transmits confidential signals to Bob in the presence of a multi-antenna eavesdropper (Eve) and a multi-antenna watchful adversary (Willie). Although artificial noise (AN) is a common PLS technique for protecting the confidential signal from wiretapping, it may reduce the communication covertness due to the additional signal emission. For maximizing the achievable secrecy rate, we propose an AN-aided secure and covert communication strategy through optimizing the information carrying beamformer and AN jointly subject to the covertness constraint. To tackle the formulated non-convex design problem, we propose a branch-reduce-and-bound (BRB)-based algorithm to solve the considered problem globally. Simulation results validate its efficiency compared with a benchmark algorithm and unveil the importance of exploiting AN.
In this article, we study a robust beamforming design for multiuser multiple-input–multiple-output secrecy networks with simultaneous wireless information and power transfer (SWIPT). In this system, an access point, multiple Internet-of-Things (IoT) devices under the nonlinear energy harvesting (EH) model with a help of one cooperative jammer (CJ). We employ artificial noise (AN) generation to facilitate efficient wireless energy transfer and secure transmission. To achieve EH fairness, we aim to maximize the minimum harvested energy among users subject to secrecy rate constraint and total transmit power constraint in the presence of channel estimation errors. By incorporating a norm-bounded channel uncertainty model, the original robust problem is transformed into a two-layer optimization problem, where the inner layer problem is reformulated as semidefinite programming (SDP) and the outer layer problem is solved by a one-dimensional (1-D) line search algorithm. In addition, in order to reduce computational complexity, we propose an algorithm based on sequential parametric convex approximation (SPCA). Finally, simulation results show that the proposed SPCA method achieves the same performance as the two-layer algorithm with much lower complexity.
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