Physical layer security (PLS), as a key technology for ensuring communication security, is widely applied in both point-to-point and multi-user communication scenarios due to its low computational and communicational overhead. However, executing physical layer security in underwater acoustic sensor networks (UASNs) poses considerable challenges in multi-user scenarios where hybrid attackers are present. To enhance the security performance of OFDMA based UASNs, we first model the secrecy capacity under the scenario of hybrid attackers. Then a joint subcarrier and power allocation algorithm named MWOM to maximize the total secrecy capacity of multiple users is proposed. In addition, an overlapping window-based dynamic clustering scheme is applied to reduce the feedback delay of the communication link. Finally, to reduce the complexity of the proposed allocation algorithm, we map the resource allocation problem to a bipartite graph model and derive the sub-optimal solution of the problem by leveraging graph theory. Simulation results verify that the proposed algorithm outperforms conventional algorithms in security performance, with negligible impact on communication performance. More importantly, we conducted actual sea trials in real underwater environments, which consistently confirmed these results.

A persistent risk in many underwater localization solutions is the leakage of position information, since anchor positions are revealed to the sensors performing position estimation. While cryptography-based secure localization mechanisms for underwater acoustic sensor networks (UASNs) can protect the privacy of anchors, varying levels of privacy preservation impact localization accuracy. Therefore, it is necessary to derive a quantitative relationship between privacy preservation levels and localization accuracy. In this paper, we first model the probability density function (PDF) of anchor decoding errors under privacy preservation constraints when anchors adopt an encrypted system to safeguard position information. The model parameters are optimized using the expectation-maximization (EM) algorithm. Next, based on the ranging PDF and anchor decoding error PDF distribution, we derive the position error bound (PEB) function that links privacy preservation levels with target localization accuracy. Simulation and field experiment results validate the effectiveness of the theoretical model.

Underwater acoustic sensor networks (UASNs) constitute the primary infrastructure for the Internet of Underwater Things (IoUT), but they face constraints in high-rate reliable transmission due to the complex underwater acoustic (UWA) channel characteristics and the scarce pilot resources. Orthogonal frequency division multiple access (OFDMA) has been widely adopted in UASNs owing to its capability for multi-user parallel transmission and flexible resource allocation. However, the severely limited and non-uniformly distributed pilots pose significant challenges for multi-user channel estimation in OFDMA-based UASNs. To address these challenges, this paper establishes a compressed sensing (CS)-based multi-user channel estimation model for OFDMA-based UASNs. Considering the significant variations in channel conditions among different UWA links, we propose an adaptive pilot allocation method that dynamically optimizes the number of pilots assigned to each user. Building on this, we further propose a bi-objective joint pilot position and power optimization (BOJPO) algorithm, which simultaneously minimizes both the mutual coherence and total coherence of the measurement matrix to enhance estimation accuracy. Simulation and sea experiment results demonstrate that the proposed pilot optimization scheme exhibits superior performance, delivering stable and reliable channel estimation for OFDMA-based UASNs despite severely scarce pilot resources.

Underwater acoustic (UWA) communication faces security challenges owing to the open nature of the UWA channel and the uncertainty of the underwater node deployment environment. Key generation schemes based on physical layer information do not require predefined keys or the introduction of additional assistance nodes, which is feasible in resource-constrained underwater scenarios. This article proposes an underwater key generation scheme that includes a channel probing protocol and a key generation algorithm. Based on the spatio-temporal dynamic characteristics of the UWA channel, the amplitude of and time delay information about the channel impulse responses (CIRs) are combined as channel parameters to generate the raw keys. Further, a synchronous probing approach is designed to decrease the probing time difference between the forward and backward channels to enhance the reciprocity of the measurements. The results of the field experiments demonstrated the effectiveness of the key generation scheme and the performance improvements resulting from synchronous probing.

In response to the increasing demand for marine data transmission, underwater acoustic (UWA) communication is widely recognized as a key technology to support various applications of the Internet of Underwater Things (IoUT). However, due to the narrow bandwidth shared by multiple acoustic systems and the constrained energy of the underwater nodes, it is an urgent problem to design an energy-efficient resource allocation scheme which can avoid interference simultaneously. In this article, we establish a cognitive orthogonal frequency-division multiple access (OFDMA) UWA communication system, where dynamic resource allocation relies on the feedback channel state information (CSI) and spectrum usage of interference. In order to detect interference, a spectrum sensing scheme applicable to the underwater environment is proposed and experimentally verified. Subsequently, the resource allocation problem is mathematically modeled with energy efficiency (EE) as the reasonable optimization objective in UWA communication systems. In order to reduce the computational complexity, the original problem is decomposed into two subproblems and a low-complexity algorithm named acrlong BOSC- acrlong TLI is developed for feasible solutions. Simulation and sea experiment results show that the proposed algorithm outperforms the existing underwater resource allocation schemes.