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IEEE Wireless Communications and Networking Conference

Probabilistic Covert Transmission in IoT Networks

Yahui Zhou, Rui Chen, Zhongling Zhao

Published Apr 21, 2024• 1 citation
Publisher

Abstract

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.

DOI
10.1109/wcnc57260.2024.10571222

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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 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 communications can hide the very existence of wireless transmissions and thus are able to address privacy issues in numerous applications of the emerging Internet of Things (IoT). In this article, we adopt channel inversion power control (CIPC) to achieve covert communications in Rayleigh fading wireless networks, where a transmitter can possibly hide itself from a warden while transmitting information to a receiver. The CIPC can guarantee a constant signal power at the receiver, which removes the requirement that the receiver has to know the channel state information in order to coherently decode the transmitter's signal. Specifically, we examine the performance of the achieved covert communications in terms of the effective covert rate (ECR), which quantifies the amount of information that the transmitter can reliably convey to the receiver subject to the warden's total error probability being no less than some specific value. The noise uncertainty at the warden serves as the enabler of covert communications. For fairness, we also consider noise uncertainty at the legitimate receiver. Our examination shows that increasing the noise uncertainty at the warden and the receiver simultaneously may not continuously improve the ECR achieved in the considered system model.
Covert communication, which can hide the communication behavior, has great potential in guaranteeing the security of information and transmission terminal to the greatest extent. In this paper, we propose a covert communication strategy based on improper Gaussian signaling (IGS) to increase the covert rate in the Internet of Things (IoT) system, in which the existing signals emitted by other transmitters were used as “Spectrum Shelter” to cover the IoT's communication. Specifically, we analyze the system's achievable transmission rate when the IoT node adopts IGS. Then, the optimal detection threshold and the minimum error detection probability of the warden are analyzed. Next, by jointly optimizing the transmission power and circularity coefficient of IGS, we maximize the covert rate under the constraints of the covertness. Finally, the simulation results verify that the proposed scheme can not only guarantee the covertness, but also improve the achievable covert rate.
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.
This article investigates covert communications in a multirelay Internet of Things (IoT) system with multiple energy harvesting jammers, where a transmitter (Alice) attempts to covertly transmit confidential messages to its destination (Bob) through relay forwarding, while a warden (Willie) detects the existence of Alice’s transmission. Specifically, we employ a harvesting-then-jamming protocol with which the jammers first harvest energy from Alice and then send jamming signals to interfere with Willie’s detection. We propose a relay and jammer selection strategy, namely quality of service (QoS)-aware selection, and use the random selection strategy as a comparison strategy. Under these two selection strategies, we derive the optimal detection threshold and minimum detection error probability at Willie, respectively. We then model the covert throughput performance and obtain the maximum covert throughput by jointly optimizing covert transmit power and jamming transmit power. Extensive numerical results are provided to illustrate the impacts of system parameters on covert throughput performance.
In this paper, we study a covert Internet of Things (IoT) system. Compared with conventional IoT systems that apply cryptography and information-theoretic secrecy approaches to secure the transmission, our considered IoT system adopts the covertness technique and intends to hide the legitimate transmission from the observant adversaries. In the IoT system, the IoT devices randomly transmit the collected data to their associated IoT gateways (GWs). In the meantime, the adversaries attempt to detect the existence of legitimate transmission based on their received signal power and launch hostile attacks accordingly. To avoid being detected by the adversaries, the IoT system applies uplink power control to achieve covert legitimate transmission. Moreover, to distort the observation of the adversaries so as to mislead their decisions, we propose an artificial noise (AN)-assisted covert communication design, where the AN is transmitted by in-band full-duplex (IBFD) IoT GWs as a jamming operation. We formulate a Stackelberg game to study the interaction between the adversaries and the legitimate entities including the IoT GWs and IoT devices, where the legitimate entities, as the leaders, decide on the powers of legitimate and AN transmissions at the upper level and the adversaries, as the followers, aim to minimize their detection errors at the lower level. Thereafter, considering the large scale of IoT system, we further cast the Stackelberg game into a mean-field Stackelberg game and incorporate the stochastic geometry and statistical channel model to capture the location heterogeneity and channel dynamics among and of the system entities, respectively. In the performance evaluation, we verify the practicability of the mean-field Stackelberg game. Moreover, we demonstrate the effectiveness of AN in improving the transmission covertness.