Recently, sensor networks have emerged as a high-impact research area, and a number of high profile applications have been proposed. Although significant progress has already been made on securing basic network protocols, additional research is needed to produce techniques and methods for protecting canonical tasks in wireless sensor networks. In this paper, we propose an effective self-embedding authentication watermarking method for tampered location detection and image recovery. The proposed detection method is classified into block-wise and pixel-wise. In block-wise detection, if the size of the block is small, the false positive rate (FPR) will be low. In pixel-wise detection, when the tampered pixels are detected, only the corresponding pixel area is marked. Therefore, the FPR will be lower than that of the block-wise detection. The experimental results demonstrate that the proposed method was effective, and accurate tamper detection and high-quality recovery can be realized even in highly tampered images.

In recent years, with the widespread use of information networks, a significant amount of important information is transmitted through the internet. However, the data transmission process is prone to hacker attacks, leading to data corruption and tampering. Therefore, the secure transmission of important information has become increasingly crucial. Consequently, it is essential to find ways to prevent hackers from detecting the existence of confidential information. The dual-image data hiding technique involves embedding important information into cover images, which are then transmitted to the data receiver. During the transmission process, the hidden information remains undetected by hackers. Therefore, the methods used to embed secret information into the cover images, ensuring both the quality of the embedding and the amount of hidden data, are crucial. This study proposes a novel data hiding method that employs the Vector Coordinate with Triangular Order Coding (TOC) technique to achieve reversible data hiding (RDH) in dual images. Through the TOC method, coordinate vectors can be converted into a decimal value for extracting secret information. Conversely, a decimal value can be transformed into vector coordinates using the TOC method for embedding secret information. Utilizing the TOC method not only achieves excellent stego image quality and a higher data embedding capacity but also eliminates the need to record any additional data, such as codebooks or location maps, during the embedding and extraction processes. Additionally, this method allows setting the k value based on the amount of secret information, where a larger k value enables embedding a greater amount of data, providing increased flexibility for the information hider. Experimental results indicate that when $k=2$ (1 bpp), the average PSNR is 55.66 dB, and when $k=10$ (2.5 bpp), the PSNR is 34.78 dB. This demonstrates that the proposed method can achieve high-quality stego images, and even at $k=10$ (2.5 bpp), the stego image remains imperceptible to the human eye. Our proposed method strikes a balance between quality and capacity, meeting the stringent requirements for secure transmission.