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.
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.
In applications of the Internet of Things (IoT), the use of short packets is expected to meet the stringent latency requirement in ultra-reliable low-latency communications; however, the incurred security issues and the impact of finite blocklength coding on the physical-layer security are not well understood. This paper investigates the performance of secure short-packet communications in a mission-critical IoT system with an external multi-antenna eavesdropper. An analytical framework is proposed to approximate the average achievable secrecy throughput of the system with finite blocklength coding. To gain more insight, a simple case with a single-antenna access point (AP) is considered first, in which the secrecy throughput is approximated in a closed form. Based on that result, the optimal blocklengths to maximize the secrecy throughput with and without the reliability and latency constraints, respectively, are derived. For the case with a multi-antenna AP, following the proposed analytical framework, closed-form approximations for the secrecy throughput are obtained under both beamforming and artificial-noise-aided transmission schemes. The numerical results verify the accuracy of the proposed approximations and illustrate the impact of the system parameters on the tradeoff between transmission latency and reliability under a secrecy constraint.
In this paper, we propose a best node and friendly jammer (bN-fJ) scheme for secure short-packet multi-hop communications in Internet-of-Things (IoT) networks. Under imperfect channel state information (CSI) conditions, the best IoT node is chosen for data transmission and a friendly jammer is chosen later to confuse the received signals at a multi-antenna eavesdropper. Approximate and asymptotic closed-form expressions for the secrecy throughput of the bN-fJ scheme are obtained, offering valuable insights into the system designs. Numerical results show that the proposed bN-fJ scheme achieves much better performance than benchmarking schemes, especially with 1 more bit/channel use and 9.4 dB enhancement in communication reliability measure. Moreover, under imperfect CSI and large antennas at the eavesdropper, the secrecy throughput and communication reliability of the system can be improved by employing the proposed node selection, e.g., a 12.5 dB improvement at 10 antennas at Eve and the imperfect CSI of 0.8. Finally, the secrecy throughput is presented as a concave curve for the number of hops and blocklengths, which enables us to identify the optimal hops and blocklength for secure multi-hop short-packet transmissions.
Jamming antenna selection (JAS) serves as a low-complexity approach to enhance covert communication in Internet of Things (IoT) networks subject to stringent energy and computational limitations. Unlike conventional JAS strategies that assume a fully cooperative jammer selecting a single antenna for artificial noise transmission, this work investigates the optimal number of selected jamming antennas to maximize covert performance with a limited-cooperation jammer. In the considered scenario, the jammer does not provide the necessary cooperation, which prevents the legitimate receiver from acquiring the jammer–receiver channel state information (CSI). According to the degree of CSI availability at the jammer, two practical JAS schemes, random JAS (RJAS) and minimum JAS (MJAS), are investigated to effectively impair the warden’s detection performance. Closed-form expressions are derived for the warden’s expected minimum detection error probability and the legitimate receiver’s transmission outage probability, with the latter evaluated under interference-limited conditions. Leveraging these results, an optimization framework is developed to jointly determine the transmit power, transmission rate, and number of selected jamming antennas to maximize the effective covert rate. Numerical results illustrate that the effective covert rate under the RJAS strategy increases monotonically with the number of selected antennas, whereas the effective covert rate under the MJAS strategy is maximized when selecting two antennas. Both theoretical analysis and simulation results validate the effectiveness of the proposed schemes and highlight the significant covert performance gains achieved by employing multiple jamming antennas in IoT networks with limited cooperation.
In this paper, we investigate covert communications in data collected IoT with NOMA, where the paired sensor nodes Smand Sntransmit covert messages to a legitimate receiver (Bob) in the presence of a Warden (Willie). To confuse the detection at Willie, an extra multi-antenna friendly jammer (Jammer) has been employed to transmit artificial noise (AN) with random power. Based on the CSI of Willie is available or not at Jammer, three AN transmission schemes, including null-space artificial noise (NAN), transmit antenna selection (TAS), and zero-forcing beamforming (ZFB), are proposed. Furthermore, the closed-form expressions of expected minimum detection error probability (EMDEP) and joint connection outage probability (JCOP) are derived to measure covertness and reliability, respectively. Finally, the maximum effective covert rate (ECR) is obtained with a given covertness constraint. The numerical results show that ZFB scheme has the best maximum ECR in the case of the number of antennas satisfies N > 2, and the same maximum ECR can be achieved in ZFB and NAN schemes with N =3D 2. Moreover, TAS scheme also can improve the maximum ECR compared with the benchmark scheme (i.e., signal-antenna jammer). In addition, a proper NOMA node pairing can further improve the maximum ECR.
Physical layer security is a promising way to secure the wireless communications in the Internet of Things (IoT). Motivated by the fact that the limited feedback resources in the IoT network would degrade the secrecy advantage of the multiple-antenna technique, we attempt to investigate the problem of how many transmit antennas should be utilized to perform secure communications. In particular, we consider the heterogeneous IoT downlink network and design a multiuser secure transmission scheme. In this scheme, the zero-forcing beamforming technique is adopted to serve the IoT legitimate users, and the remaining spatial freedoms are utilized to send artificial noise (AN) for confusing the passive eavesdroppers. Given the secrecy outage constraints, we derive the closed-form expression for the network secrecy throughput and formulate a non-convex optimization problem with multiple parameters, e.g., the number of transmit antennas, the wiretap codes, the feedback bits allocation strategy, and the power allocation ratio between the information bearing signal and the AN. To effectively tackle this problem, we develop an optimization framework involving the block coordinate descent algorithm and the 1-D search method. Simulation results validate the effectiveness of our proposed optimization framework and show that the optimal number of transmit antennas increases as the secrecy outage constraints become stricter, or the feedback resources become scarcer.
This paper studies the secrecy performance of short-packet communications in dual-hop cooperative Internet-of-Things (IoT) networks in the presence of multiple eavesdroppers. The best node selection (BNS) scheme is proposed to select the best IoT node for improving secure packet transmissions from a source to a robot destination under two intercepting scenarios at eavesdroppers such as non-colluding and colluding. Closed-form expressions for the average secrecy block error rate (SBLER) and secrecy throughput (STP) of the BNS scheme are derived, based on which the asymptotic analysis at high signal-to-noise ratio (SNR) regimes is also carried out. Simulation results show that the proposed BNS scheme outperforms the random selection one in terms of SBLER and STP. Moreover, the impacts of average SNR and the number of blocklengths on the system STP are also evaluated.