As the mainstay of the Internet of Things (IoT), data carries the vital memory of the future intelligent society. However, because of the inherent broadcast and open characteristics of wireless channels, transmitting data securely and reliably is a huge challenge for IoT. In this paper, a covert transmission control scheme with high reliability and anti-jamming capability is proposed to deal with the above challenges, by exploiting the artificial noise emitted by cooperative interference sources in the environment. Specifically, with the aim of maximizing the warden's detection error probability, the transmit power and frequency are jointly optimized under the constraints of transmission reliability and channel equivocation. The Block Coordinate Descent (BCD) algorithm is used to solve the formulated optimization problem. Numerical results demonstrate the superiority of our proposed scheme, which can simultaneously achieve high reliability, covertness, and anti-jamming capability.
As the mainstay of the Internet of Things (IoT), data carries the vital memory of the future intelligent society. However, because of the inherent broadcast and open characteristics of wireless channels, transmitting data securely and reliably is a huge challenge for IoT. In this paper, a covert transmission control scheme with high reliability and anti-jamming capability is proposed to deal with the above challenges, by exploiting the artificial noise emitted by cooperative interference sources in the environment. Specifically, with the aim of maximizing the warden's detection error probability, the transmit power and frequency are jointly optimized under the constraints of transmission reliability and channel equivocation. The Block Coordinate Descent (BCD) algorithm is used to solve the formulated optimization problem. Numerical results demonstrate the superiority of our proposed scheme, which can simultaneously achieve high reliability, covertness, and anti-jamming capability.
Covert wireless communications aim to hide the existence of transmission behavior from watchful adversaries to enhance security. In this paper, we propose a spectrum mask based covert communication strategy in Internet of Things (IoT) networks, where the overt channels are leveraged to enhance the covertness. Specifically, the legitimate IoT transmitter superimposes its own message on the overt channel to avoid being detected by the warden. We assume that proper Gaussian signaling (PGS) is adopted at the overt channel, and improper Gaussian signaling (IGS) is adopted at the legitimate transmitter to improve the covert transmission performance. To maximize the covert rate of the legitimate IoT system, a joint transmit power and IGS factor optimization problem is formulated under the constraints of covertness requirement. The metric of minimum error detection probability, that represents the worst-case for the legitimate transmitter, is utilized to measure the covertness. By exploiting the piece-wise monotonic properties of the objective function and the constraints, we derive the optimal transmit power and IGS factor pairs in both the IGS and PGS schemes. Finally, extensive numerical results are presented to demonstrate that the IGS scheme can improve the covert rate compared to the PGS scheme under a given covertness constraint.
Covert communication enhances the security of information transmission by protecting communication behavior, which has been widely investigated in various wireless communication systems. In this paper, we develop a covert Internet of things (IoT) network, where energy-limited IoT nodes selectively transmit information or artificial noise based on channel state information. Specifically, if the channel gains of all legitimate links are less than a given threshold, the energy-limited node emits artificial noise, otherwise, it transmits covert information. Meanwhile, we adopt the strategy of channel inversion power control (CIPC) to hide the location information of the nodes. Then, we derive Willie's detection error probability (DEP), propose an optimization problem for covert throughput, and obtain the optimal threshold and transmission energy. The results indicate that the probability of covert transmission significantly affects Willie's DEP. Moreover, the average covert throughput can be maximized by a relatively small threshold.
Covert communication aims to enhance the security of the wireless communication by hiding the transmission behavior from the eavesdropper. In this paper, a spectrum mask-based multi-antenna covert communication strategy is proposed in Internet of Things (IoT) networks. Specifically, the transmitter superimposes its messages on the existing overt channel to prevent the transmission being detected by the adversary eavesdropper, which can significantly enhance communication covertness without the need for additional spectrum resources. To eliminate the interference cause to the existing overt channel, multi-antenna technology and improper Gaussian signaling (IGS) are leveraged at the covert transmitter. Moreover, maximum ratio transmission (MRT) is adopted at the covert transmitter can fully exploit the additional degrees of freedom (DoF) that the multi-antenna provides to achieve reliable and covert transmission. Firstly, the optimal detection threshold at the eavesdropper is analyzed, and minimum error detection probability is then calculated, which indicates the worst-case from the covert transmitter’s perspective. In this scenario, a joint transmit power and IGS factor optimization problem is proposed to maximize the covert throughput under the covertness constraints. Secondly, the optimization problem is divided into three subproblems based on the power relationship, then the optimal transmit power and IGS factor are solved, respectively. Finally, extensive simulation is executed to demonstrate that under the given covertness constraints, the proposed strategy can effectively improve the covert communication performance of the multi-antenna system in IoT networks.
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.
Internet of Things (IoT) is becoming an emerging paradigm to achieve ubiquitous connectivity, via massive deployment of physical objects, such as sensors, controllers, and actuators. However, concerns on the IoT security are raised due to the wireless broadcasting nature and the energy constraint of the physical objects. In this paper, we study secure downlink transmission from a controller to an actuator, with the help of a cooperative jammer to fight against multiple passive and noncolluding eavesdroppers. In addition to artificial noise aided secrecy beamforming for secure transmission, cooperative jamming (CJ) is explored to further enhance physical layer security. In particular, we provide a secrecy enhancing transmit design to minimize the secrecy outage probability (SOP), subject to a minimum requirement on the secrecy rate. Based on a strict mathematical analysis, we further characterize the impacts of the main channel quality and the minimum secrecy rate on transmit designs. Numerical results confirm that our design can enhance both security (in terms of SOP) and power efficiency as compared with the approach without CJ.
In practice, Internet of Things (IoT) applications may face two different hostile attacks, i.e., overhearing the broadcasted data and detecting the presence of data communication. Previous works have assumed that only one of these attacks is present in the network and have addressed these attacks separately. In this article, we investigate the security of a simple but practical IoT-based point-to-point communication which is facing with the above-mentioned two attacks under some realistic assumptions. In other words, we aim to protect the data against two adversary nodes, namely Eve (who tries to capture the broadcasted data) and warden Willie (who tries to detect the presence of data communication between legitimate nodes). To tackle these attacks, we jointly employ the information-theoretic security and covert communication techniques. To hide information from Willies, we force the source to transmit its message in the selected time slot and the multiple-antennas cooperative jammer to inject jamming during all time slots contentiously which leads to deceive Eves and Willies jointly. To enhance the performance of this security design, we formulate an optimization problem, with the goal of maximizing the secrecy rate subject to power constraints at the source and jammer, while satisfying a covert communication requirement. Since the mentioned optimization problem is nonconvex, we propose an algorithm to solve it. Then, to obtain further insights, we extend our proposed system model to noncolluding and colluding Willies. Next, we study a practical communication scenario, where the source has uncertainty about Willie’s location and knows the channel state information (CSI) of Eves imperfectly. Our numerical results highlight that a more accurate estimation of Willie’s location has a more positive efficacy on the secrecy performance compared to the case with more accuracy of Eves’ CSI estimation.