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.

In this paper, a covert wireless-powered relay (CWPR) system with the aid of a full-duplex receiver is investigated, where the receiver acts as a friendly jammer to protect the subsequent communication activities from being detected, while transmitting radio frequency (RF) energy to charge the relay. Meanwhile, both the transmitter and the relay employ a probabilistic transmission strategy to initiate information transmission based on legitimate link information. In the multi-relay scenario, two relay scheduling schemes are proposed, namely, energy harvesting maximization scheduling (EHMS) scheme and first-hop link priority scheduling (FLPS) scheme. Then, we derive the minimum detection error probability (DEP) of the eavesdropper (Eve) in two phases, and conduct a thorough analysis of the covert performance of each scheme, including covert rate, covert energy efficiency (CEE) as well as covert outage probability (COP), and obtain the optimal transmission prior probability and the optimal jamming power under each scheme. The numerical results show that the proposed probabilistic transmission strategy can significantly enhance CEE compared to the conventional continuous transmission strategy. Moreover, the proposed transmission scheme is indeed effective in enhancing the covert performance, especially when there are significant differences in channel conditions between the two-hop links.

Federated learning (FL) enables the training of a global model using clients' local datasets, leveraging their computing resources for efficient machine learning while preserving user privacy. This paper explores FL in wireless networks, focusing on client selection and bandwidth allocation as key factors impacting latency, covert constraint and energy consumption. We propose the per-round energy drift plus cost (PEDPC) algorithm to address this optimization problem from an online perspective. The performance of the PEDPC algorithm is validated through simulations, evaluating latency and energy consumption under both IID and non-IID data distributions.

In this paper, we develop an energy harvesting covert cognitive radio (EHCCR) network, where multiple power beacons (PBs) provide energy for secondary users with limited energy and transmit artificial noise (AN) to against multi-antenna eavesdropping of eavesdropper (Eve). Unlike conventional research that focuses on ensuring information content security, we consciously protect communication behavior, which also takes secure communication to a new level. Initially, we analyze the detection scheme of Eve from the perspective of legitimate users, and derive Eve's minimum detection error probability (DEP) and the range of optimal detection threshold. Subsequently, we analyze the covert performance of the proposed network, including covert rate as well as covert transmission outage probability (CTOP). Finally, we evaluate the performance of the EHCCR network by exploiting numeral simulations. Through our analysis, we conclude that higher uncertainty level of background noise, and AN does have a positive impact on the interference experienced by Eve, but this can be alleviated by increasing the number of antennas. Interestingly, secondary users are able to achieve a positive covert rate in the presence of Eve's multi-antenna eavesdropping when jamming is large enough.

Covert communications can enhance users's privacy by hiding the existence of communication. In this paper, we analyze a covert cooperative cognitive radio (CCCR) networks, where a primary transmitter (PT) transmits information with the aid of one secondary transmitter (ST). In return, ST attempts to transmit private information by exploiting PT's spectrum in presence of an eavesdropper (Eve). Specifically, a full-duplex secondary receiver (SR) sends jamming signals to the Eve to cause uncertainty by varying the jamming power. Then, the closed-form expression of the minimal detection error probability at Eve, the approximate expression for the optimal transmit power as well as the corresponding covert rate can be obtained under the given constraint. Numerical results show that the jamming signals and noise uncertainty have a significant influence on Eve's minimum detection error probability. Moreover, it can be seen that under the same covert constraints, the joint impact of noise uncertainty and jamming power on Eve's detection error probability, covert rate and covert outage probability (COP) is remarkable when noise uncertainty is large or the self-interference cancellation coefficient is small.

Covert communication is able to provide high-level security by protecting communication behavior. In this paper, we develop a covert cooperative cognitive radio (CCCR) network, where primary transmitter (PT) transmits information with the aid of multiple secondary transmitters (STs). In return, STs are able to transmit private information by exploiting PT's spectrum in presence of a powerful eavesdropper (Eve). Meanwhile, we propose a cognitive user scheduling scheme based on link information and maximum-minimum principle. Moreover, we derive Eve's expected detection error probability and evaluate the covert performance of the novel scheme. Numerical results show that joint impact of self-interference and jamming power of Eve can enable STs to achieve covert transmission. Furthermore, it can be found that the influence of the interference power on Eve's detection error probability and covert performance is significant when the self-interference cancellation coefficient is sufficient large.

Covert communication provides high-level security for protecting users' privacy information. In this paper, we analyze the joint impact of an external jammer and channel uncertainty on covert communication in multi-user cognitive radio networks. Meanwhile, to fairly schedule the covert communication over multi-user cognitive radio networks, we propose a fairness secondary user (SU) scheduling scheme, which enables each SU to have the same probability for sending information covertly with the aid of an external jammer. Then, the closed-form expression for the covert rate of the scheduled SU can be obtained. Our results show that the minimal detection error probability and covert rate of the scheduled SU can be significantly improved by exploiting the channel uncertainty and random variation of interference power. Moreover, the impact of interference power on the probability of detection error and the covert rate is noticeable when channel uncertainty is large.