Recently, many steganalysis approaches improve their feature extraction ability through adding convolutional layers. However, it often leads to a decrease of resolution in the feature map during downsampling, which makes it challenging to extract weak steganographic signals accurately. To address this issue, this paper proposes a multi-resolution steganalysis net (MRS-Net). MRS-Net adopts a multi-resolution network to extract global image information, fusing the output feature map to ensure high-dimensional semantic information and supplementing low-level detail information. Furthermore, the model incorporates an attention module which can analyze image sensitivity based on different channel and spatial information, thus effectively focusing on areas with rich steganographic signals. Multiple benchmark experiments on the BOSSBase 1.01 dataset demonstrate that the accuracy of MRS-Net significantly improves by 9.9% and 3.3% compared with YeNet and SRNet, respectively, demonstrating its exceptional steganalysis capability.

Underwater Wireless Sensor Networks (UWSNs) are widely used in many fields, such as regular marine monitoring and disaster warning. However, UWSNs are still subject to various limitations and challenges: ocean interferences and noises are high, bandwidths are narrow, and propagation delays are high. Sensor batteries have limited energy and are difficult to be replaced or recharged. Accordingly, the design of routing protocols is one of the solutions to these problems. Aiming at reducing and balancing network energy consumption and effectively extending the life cycle of UWSNs, this paper proposes a Hierarchical Adaptive Energy-efficient Clustering Routing (HAECR) strategy. First, this strategy divides hierarchical regions based on the depth of the sensor node in a three-dimensional (3D) space. Second, sensor nodes form different competition radii based on their own relevant attributes and remaining energy. Nodes in the same layer compete freely to form clusters of different sizes. Finally, the transmission path between clusters is determined according to comprehensive factors, such as link quality, and then the optimal route is planned. The simulation experiment is conducted in the monitoring range of the 3D space. The simulation results prove that the HAECR clustering strategy is superior to LEACH and UCUBB in terms of balancing and reducing energy consumption, extending the network lifetime, and increasing the number of data transmissions.