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IEEE Internet of Things Journal

Greedy Degree and Jamming Aided Covert Uplink Transmission in Cell-Free IoT Networks

Rui Chen, Zeqing Chen, Shouzhi Xu, Kai Ma, Xiaojun Liu, Liping Fan

Published Jan 1, 2024• 4 citations
Publisher

Abstract

The cell-free (CF) network architecture has promising applications in Internet of Things (IoT) networks due to its dynamic and adaptive nature in resource allocation. However, due to the openness of wireless channels and the information interaction of sensitive data, the security issues of CF IoT networks have become more severe, especially in the case of powerful opponents. In this article, a high-level secure transmission technique is utilized to protect the privacy of users, which is called covert communication. Specifically, in the CF IoT network conceived, one IoT device secretly transmits sensitive information to an access point (AP) under the cover of a selected jammer to avoid being detected by other curious IoT devices, which are regarded as potential eavesdroppers (Eves) and determined by the central processing unit (CPU) based on greedy degree. Then, we analyze the joint impact of jamming and greedy degree on the detection error probability (DEP) for Eve, and determine Eve’s minimum DEP as well as the corresponding optimal threshold. To enhance energy efficiency while ensuring communication security, three jamming scheduling schemes have been proposed, namely, the jamming scheduling for both the receiver (Bob) and Eve (JSBE), the jamming scheduling for Eve (JSE), and the jamming scheduling for Bob (JSB). Numerical results indicate that greedy degree dominates the average minimum DEP for Eve when IoT devices tend to be lightweight. Furthermore, JSBE scheme demonstrates superiority in terms of covert rate, covert outage probability (COP), and covert energy efficiency (CEE), which provides an effective solution for high-security transmission of energy-constrained nodes in CF IoT networks.

DOI
10.1109/jiot.2024.3460052

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The cell-free (CF) network architecture has promising applications in Internet of Things (IoT) networks due to its dynamic and adaptive nature in resource allocation. However, due to the openness of wireless channels and the information interaction of sensitive data, the security issues of CF IoT networks have become more severe, especially in the case of powerful opponents. In this article, a high-level secure transmission technique is utilized to protect the privacy of users, which is called covert communication. Specifically, in the CF IoT network conceived, one IoT device secretly transmits sensitive information to an access point (AP) under the cover of a selected jammer to avoid being detected by other curious IoT devices, which are regarded as potential eavesdroppers (Eves) and determined by the central processing unit (CPU) based on greedy degree. Then, we analyze the joint impact of jamming and greedy degree on the detection error probability (DEP) for Eve, and determine Eve’s minimum DEP as well as the corresponding optimal threshold. To enhance energy efficiency while ensuring communication security, three jamming scheduling schemes have been proposed, namely, the jamming scheduling for both the receiver (Bob) and Eve (JSBE), the jamming scheduling for Eve (JSE), and the jamming scheduling for Bob (JSB). Numerical results indicate that greedy degree dominates the average minimum DEP for Eve when IoT devices tend to be lightweight. Furthermore, JSBE scheme demonstrates superiority in terms of covert rate, covert outage probability (COP), and covert energy efficiency (CEE), which provides an effective solution for high-security transmission of energy-constrained nodes in CF 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.
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.
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.
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.
With the rapid advancement of physical-layer security technology, the covert and secure communication has become crucial in safeguarding wireless communication systems. In this article, we propose a joint covert and secure transmission scheme for simultaneous wireless information and power transfer (SWIPT) assisted cooperative nonorthogonal multiple access (CNOMA) systems. In the CNOMA system, a greedy relay transmits the confidential information to the far user (Carol), with the assistance of the near user (Bob). Meanwhile, as a SWIPT node, Bob is self-sustained by harvesting energy from relay. What is more, a warden (Alice) and noncolluding eavesdroppers (Eves) always attempt to detect and capture the confidential information, respectively. To counteract the attacks from Alice and Eves, a jamming-assisted scheme is employed. For the proposed system model, we derive closed-form expressions for the detection error probability (DEP) and the average minimum detection error probability (AMDEP) of Alice. Additionally, closed-form expressions for the outage probability (OP) of users and the intercept probability (IP) of Eves are obtained. Furthermore, to maximize the effective covert rate (ECR) of Carol, an optimization problem is formulated, subject to covertness and security constraints. Numerical results are provided to demonstrate the impact of the system parameters on covert and secure performance, with the results showing perfect agreement with the theoretical analysis.
As Internet of Things (IoT) has boomed in recent years, many security issues have also been exposed. Focusing on physical layer security in wireless Internet of Things network communication, a series of security methods have been widely studied. Nevertheless, cooperative jamming methods in physical layer security to fight against collusive eavesdroppers have not been thoroughly studied yet. In this article, we study a cooperative-jamming-based physical layer secure transmission scheme for Internet of Things wireless networks in the presence of collusive eavesdroppers. We design a cooperative jamming strategy without knowing the channel state information of eavesdroppers. Considering the cooperation of multiple nodes with multiple antennas, this strategy can maximize the signal-to-interference-plus-noise ratio at an actuator (legitimate receiver). Meanwhile, the generated cooperative jamming signals can reduce the signal-to-interference-plus-noise ratio at eavesdroppers. To explore the theoretical security performance of our strategy, we perform a secrecy outage probability analysis and an asymptotic analysis. In the cases of cooperative jamming and without cooperative jamming, the closed-form expressions of the secrecy outage probability are deduced, and the influence of system parameters on the secrecy outage probability becomes more intuitive through a strict mathematical asymptotic behavior analysis. In addition, considering the energy limitation of Internet of Things devices, we propose a power allocation algorithm to minimize the total transmission power given the security requirements. The numerical results show the effectiveness of our schemes and are consistent with the theoretical analysis.