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IEEE International Conference on Acoustics Speech and Signal Processing

Secure Backscattering with Non-Colluding Jammer and Eavesdropper

Tianyi Zhang, Deepak Mishra, Jinhong Yuan, Aruna Seneviratne

Published Apr 21, 2026• 0 citations
Publisher

Abstract

Backscatter communication (BackCom) has emerged as a sustainable and green paradigm for large-scale Internet of Things deployments, enabling energy-efficient and low-cost connectivity. However, its open nature makes it highly vulnerable to hybrid attacks combining jamming and eavesdropping. This paper investigates a novel physical-layer security framework for secure data collection in multi-tag monostatic BackCom systems under hybrid attacks. We formulate a joint optimization problem of the transmit precoder, artificial noise, and receive combiner to maximize the sum-secrecy spectral efficiency. To address this, semidefinite relaxation and mixed max-min fractional programming are employed to obtain the optimal precoder and artificial noise, while a closed-form solution is derived for the receive beamformer. By integrating these into a block coordinate descent framework, we develop an iterative algorithm with guaranteed convergence to a near-optimal solution. Simulation results validate the robustness of the proposed design and show substantial performance enhancement, achieving up to 26.45dB gain over conventional benchmarks and 0.47dB over the existing scheme.

DOI
10.1109/icassp55912.2026.11464233

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Backscatter communication (BackCom) has emerged as a sustainable and green paradigm for large-scale Internet of Things deployments, enabling energy-efficient and low-cost connectivity. However, its open nature makes it highly vulnerable to hybrid attacks combining jamming and eavesdropping. This paper investigates a novel physical-layer security framework for secure data collection in multi-tag monostatic BackCom systems under hybrid attacks. We formulate a joint optimization problem of the transmit precoder, artificial noise, and receive combiner to maximize the sum-secrecy spectral efficiency. To address this, semidefinite relaxation and mixed max-min fractional programming are employed to obtain the optimal precoder and artificial noise, while a closed-form solution is derived for the receive beamformer. By integrating these into a block coordinate descent framework, we develop an iterative algorithm with guaranteed convergence to a near-optimal solution. Simulation results validate the robustness of the proposed design and show substantial performance enhancement, achieving up to 26.45dB gain over conventional benchmarks and 0.47dB over the existing scheme.
Backscatter communication (BackCom) is widely adopted in Internet of Things (IoT) thanks to its characteristics of low power consumption and low cost. However, it is vulnerable to jamming due to double channel fading of backscattering signal, and the lack of encryption capability in tags increases the risk of eavesdropping. In this paper, we propose a monostatic BackCom system with a multi-antenna reader under hybrid attack, which leverages artificial noise (AN) to degrade eavesdropper’s channel capacity. We also design the transmit beamforming and the combiner to enhance the secrecy rate of the system. Specifically, we formulate a secrecy rate maximization problem with transmit power constraint, which is difficult to solve due to its non-convexity and coupled variables. Hence, we divide it into two subproblems through decoupling the variables and solve them alternately to obtain an overall suboptimal solution. Finally, our numerical results validate our optimization scheme by comparing it with selected benchmarks and showing the fast convergence speed of the proposed algorithm.
In this paper, we investigate the physical layer secrecy (PLS) performance of a bi-static backscatter communication (BackCom) system, where a tag reliably communicates with a reader node by reflecting the radio frequency (RF) signal emitted by a source, while a malicious eavesdropper (Eve) attempts to intercept the transmission. To enhance the system's security, we propose an artificial noise (AN) injection scheme, in which the RF source transmits AN to confuse Eve while concurrently serving a legitimate communication user (CU). The objective is to maximize the tag's secrecy spectral efficiency (SSE) by jointly optimizing power allocation and beamforming for both the information signal and AN, subject to practical constraints including a minimum spectral efficiency (SE) requirement for the CU and a total power budget at the RF source. To tackle the resulting non-convex optimization problem, we develop an efficient algorithm based on alternating optimization (AO) to obtain a high-quality suboptimal solution. Simulation results confirm that the proposed design significantly improves secrecy performance compared to conventional schemes based on the null-space projection (NSP) technique.
In this paper, we investigate the physical layer security of a full-duplex base station (BS)-aided system in the worst case, where an uplink transmitter (UT) and a downlink receiver (DR) are equipped with a single antenna, while a powerful eavesdropper is equipped with multiple antennas. For securing the confidentiality of signals transmitted from the BS and UT, an artificial noise (AN)-aided secrecy beamforming scheme is proposed, which is robust to the realistic imperfect state information of both the eavesdropping channel and the residual self-interference channel. Our objective function is that of maximizing the worst-case sum secrecy rate achieved by the BS and UT, through jointly optimizing the beamforming vector of the confidential signals and the transmit covariance matrix of the AN. However, the resulting optimization problem is non-convex and non-linear. In order to efficiently obtain the solution, we transform the non-convex problem into a sequence of convex problems by adopting the block coordinate descent algorithm. We invoke a linear matrix inequality for finding its Karush-Kuhn-Tucker (KKT) solution. In order to evaluate the achievable performance, the worst-case secrecy rate is analytically derived. Furthermore, we construct another secrecy transmission scheme using the projection matrix theory for performance comparison. Our simulation results show that the proposed robust secrecy transmission scheme achieves substantial secrecy performance gains, which verifies the efficiency of the proposed method.
In this paper, the physical-layer security of a cooperative wireless system with multi-antenna full-duplex (FD) destination is examined. More specifically, we consider a cooperative transmission scenario in which a source communicates with a destination through a relay in the presence of an eavesdropper. In order to degrade the wiretap channel, the FD destination simultaneously transmits an interference signal towards the eavesdropper, while receiving information from the relay. A joint transmit and receive beamformer design is proposed to maximize the signal-to-interference-plus-noise ratio (SINR) at the destination, while guaranteeing that the SINR at the eavesdropper is below a certain threshold. We reformulate the optimization problem as a semidefinite relaxation problem in terms of a transmit beamforming matrix. To balance the performance and system complexity, we investigate suboptimum beamforming designs based on zero-forcing criterion. We derive exact closed-form expressions for the average secrecy rates of the proposed suboptimum designs. Our results reveal that optimum and suboptimum beamforming schemes along with friendly jamming significantly improve the secrecy performance. Moreover, simulation results demonstrate that the optimum scheme outperforms suboptimum schemes, especially in high transmit power regimes.
In this work, we exploit a multi-antenna cooperative jammer to enable secure short packet communications in Internet of Things (IoT) networks. Specifically, we propose three jamming schemes to combat eavesdropping, i.e., the zero forcing beamforming (ZFB) scheme, null-space artificial noise (NAN) scheme, and transmit antenna selection (TAS) scheme. Assuming Rayleigh fading, we derive new closed-form approximations for the secrecy throughput with finite blocklength coding. To gain further insights, we also analyze the asymptotic performance of the secrecy throughput in the case of infinite blocklength. Furthermore, we investigate the optimization problem in terms of maximizing the secrecy throughput with the latency and reliability constraints to determine the optimal blocklength. Simulation results validate the accuracy of the approximations and evaluate the impact of key parameters such as the jamming power and the number of antennas at the jammer on the secrecy throughput.
This paper exploits the mobility of an unmanned aerial vehicle (UAV) to improve the physical layer (PLS) security against potential eavesdropping scenarios, where the sensitive data transmitted from a ground base station (GBS) to multiple information receivers (IRs) is easily eavesdropped by multiple non-colluding eavesdroppers (Eves). Specifically, the UAV is employed as a friendly jammer to transmit artificial noise to degrade the wiretap channels. By leveraging the UAV's mobility and the possibility of establishing line-of-sight links, the UAV can move close to the Eves and opportunistically jam them. Especially, two practical factors, namely, the imperfect location information of Eves and the existence of no-fly zones are considered. Since only the partial position information of the Eves can be known, as the worst case, the minimum average secrecy rate of IRs is robustly optimized by jointly designing the trajectory and jamming power of the UAV, and the transmission power of the GBS to ensure the security of all IRs. However, the formulated problem with coupled variables is non-convex and intractable. As such, an efficient alternative iterative suboptimal algorithm is proposed to solve this problem by applying the block coordinate descent, successive convex approximation, slack variables, andS\mathcal {S}S-Procedure. Numerical results reveal that the proposed robust algorithm can substantially improve the max-min average secrecy rate, and the effectiveness of the proposed algorithm is further verified by comparing it with three benchmark schemes.