This study investigates energy-efficient resource allocation for covert vehicular communications with age constraints, where vehicle-to-vehicle (V2V) links leverage spectrum sharing to conceal covert transmissions. Vehicle-to-infrastructure (V2I) links serve as friendly jammers, simultaneously disrupting detection and maintaining connectivity with the base station. To maximize V2V links’ covert energy efficiency (CEE) and V2I links’ throughput under quality of service (QoS), communication covertness, and freshness constraints, a novel matching-based resource allocation framework is proposed. Specifically, we derive the minimum error detection rate and the optimal detection threshold at warden. The transmit probability and power are jointly optimized using the successive convex approximation method. Jamming selection is then modeled as a stable marriage problem, solved via the Gale-Shapley algorithm for stable matching between V2V and V2I links. Additionally, we explore a coalition falsification strategy to further enhance the CEE of certain V2V links without hurting the performance of the rest. Extensive simulations validate the proposed approach, showing significant improvements over existing baselines.

Unmanned aerial vehicles (UAVs) assisted covert communication networks, a significant component of the secure Internet of Things (IoT), comprise highly maneuverable aerial relays, massive ground-based sensor nodes (GNs), legitimate receivers and a warden that integrate signal-sensing and detection capabilities. However, existing works mainly focus on energy-efficient relaying or trajectory optimization for UAV-assisted sensor networks, neglecting the joint impact of limited battery capacity of GNs and the stringent requirement for UAVs to avoid detection by the warden, which will lead to severe energy waste and a low covert rate. To tackle this issue, we propose a stable matching-based two-phase resource allocation framework for multi-UAV-assisted covert communications (STRMC) under symmetric information. Specifically, we introduce the minimum weight stable matching (MWSM) algorithm to derive the energy-optimal and covert-rate-optimal pairings in each phase, leveraging the structural properties of all stable matchings and graph-theoretic techniques. Simulation results show that the proposed STRMC significantly improves both covert throughput and energy efficiency compared with existing works.

Advanced metering infrastructure in smart grids faces critical security challenges from distributed denial of service (DDoS) attacks, while traditional traceback methods suffer from resource constraints that limit their mitigation effectiveness. To address this, we propose a reverse auction-driven fog resource allocation strategy that innovatively employs a reverse auction mechanism to coordinate distributed fog resources for collaborative DDoS attack mitigation. Specifically, the framework is formulated as a 0–1 integer programming model, for which we develop a second-price sealed-bid auction (SPSA) algorithm that reduces computational complexity from factorial to polynomial time while maintaining allocation optimality. Experimental results demonstrate that the SPSA algorithm outperforms existing baseline methods, significantly improving both the efficiency and security of DDoS defenses in smart grid environments.

In the Internet of vehicles, using jammers to assist covert communication can protect the security of vehicular communication in some sensitive or special scenarios. However, the issue of three-party spectrum resource allocation involving multiple coexisting transmitters, receivers, and jammers has rarely been studied. This paper investigates jammer selection and power control in vehicular covert communication. To maximize the utility of spectrum resources, a vehicular covert communication auction model (VCCAM) is established and formulated as a 0-1 integer programming problem. We derive the optimal detection threshold for minimum average detection error probability and corresponding optimal transmit power based on the slow fading statistical channel state information (CSI) of mobile links. We then propose a reverse Vickrey-Clarke-Groves (VCG) auction algorithm that ensures incentive compatibility and individual rationality. However, it lacks computational efficiency. To address this, we introduce the reverse second-price sealed-bid algorithm (SPSA), which reduces the VCG auction’s factorial complexity to polynomial complexity, offering a computationally efficient, suboptimal solution. Extensive simulations verify the effectiveness, communication covertness, computational efficiency, incentive compatibility, and individual rationality of the proposed algorithms, showing that our algorithm significantly outperforms other baselines.