An Automatic Method for Image Steganography Using Jensen Similarity Criterion

An Automatic Method for Image Steganography Using Jensen Similarity Criterion

연구 분야: Strategies

학회: 2022 8th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS)

Steganography, an important component of security systems, plays an essential role in the information security mechanisms. Among various types of steganography, image steganography has attracted lots of attention in the academic community. Despite the increasing development of the image steganography solutions, there are still some concerns about their level of security. In this paper, we propose a new image steganography scheme which is based on Least-Significant-Bit (LSB) substitution and Jensen Similarity Criterion. The proposed method first divides both the LSBs of the input image and the bitstream of the secret message into several blocks. Then, our method employs the Jensen similarity criterion over each block of the message and the reversed message to choose its closest block in the image. We repeat these operations by changing of scroll type of bits in the image until the highest PSNR is obtainedt Finally, each secret message block is hidden into its corresponding image block selected in the previous step. Our experimental results show that our approach achieves a very high level of hiding capacity. Moreover, the results demonstrate that our approach provides around 4.5% higher visual quality compared to the state of the art methods and measured by the Peak Signal-to-Noise-Ratio (PSNR).