VQ-based data hiding in IoT networks using two-level encoding with adaptive pixel replacements

Internet of things (IoT) realizes the concept of bringing things connected together. Data are exchanged and controlled within one or more IoT networks. Sensitive data transferred between different IoT networks may also lead to data leakage. One way to reduce the risk of these problems is to employ steganography while delivering secret information over the IoT networks. This paper presents a steganographic scheme that employs vector quantization (VQ) transformation and the least significant bits (LSB) to embed secret data into a cover image. We devise a new technique, namely two-level encoding, to separate the pixels of a VQ-transformed image block into two groups, the LSB group and the secret data group, in the first level. Then we use an indirect approach that embeds VQ indexes in the LSB group and secret data in the secret data group in the second level. The embedded VQ indexes are used to represent the VQ-transformed image blocks, and the secret data are used as the difference values to adjust the VQ-transformed image blocks and to create stego-image blocks, such that the stego-image blocks become more similar to the original image blocks after embedding. Compared with other similar work, the experimental results show that the proposed scheme produces stego-images with slightly better quality in terms of PSNR; the experimental results also indicate that it provides about ten times as large as the embedding capacity of the prior similar schemes. Moreover, the proposed scheme is able to pass the popular detections, such as Chi-square test and AUMP LSB, both to detect whether an image uses LSB for data hiding.