Hash and Prediction-Error-Based Reversible Watermarking for Medical Images

In reversible watermarking (RW), the original cover image and the watermarked information are restored without any distortion. A secure RW technique using hybrid prediction and difference pair mapping along with the hashing algorithm is proposed in this paper. The four-stage imperceptible watermarking employed in this technique enlarges the payload capacity with low distortion in stego-image. The data authentication is used for protection of message integrity and validation of originator identification. Mean square error and peak signal-to-noise ratio are used for analyzing the robustness of the watermarked image. The simulation result shows that this method performs better than the other existing state-of-the-art methods.

Data Authentication for Wireless Sensor Networks with High Detection Efficiency Based on Reversible Watermarking

Data authentication is an important part of wireless sensor networks (WSNs). Aiming at the problems of high false positive rate and poor robustness in group verification of existing reversible watermarking schemes in WSNs, this paper proposes a scheme using reversible watermarking technology to achieve data integrity authentication with high detection efficiency (DAHDE). The core of DAHDE is dynamic grouping and double verification algorithm. Under the condition of satisfying the requirement of the group length, the synchronization point is used for dynamic grouping, and the double verification ensures that the grouping will not be confused. According to the closely related characteristics of adjacent data in WSNs, a new data item prediction method is designed based on the prediction-error expansion formula, and a flag check bit is added to the data with embedded watermarking during data transmission to ensure the stability of grouping, by which the fake synchronization point can be accurately identified. Moreover, the embedded data can be recovered accurately through the reversible algorithm of digital watermarking. Analysis and experimental results show that compared with the previously known schemes, the proposed scheme can avoid false positive rate, reduce computation cost, and own stronger grouping robustness.