Blockchain Enabled Interpolation Based Reversible Data Hiding Mechanism for Protecting Records

Abstract

A diagnosis can be made using a lot of the crucial information contained in medical snaps. Medical images have become a target for malicious attacks due to the requirement for regular communication in order to provide flexibility and accurate diagnosis. In order to protect medical images, encryption algorithms are used. Because of this, medical photos are encrypted before being transmitted; yet, this is only one layer of security. Reversible Data Hiding (RDH) techniques have recently been used to incorporate private data into medical images. This enables efficient and safe communication, and the secretly contained information—such as personal and medical records—is highly helpful for making medical diagnosis. However, the limited embedding capacity of current RDH systems continues to limit their usefulness. In this study, a Reversible Data Hiding method based on a histogram shifting and interpolation scheme is highlighted. The achievable embedding capacity (EC) for the suggested technique is one bit per pixel (bpp) for both digital and medical images. A blockchain-based system based on three keys is used to encrypt the images. The proposed blockchain mechanism is secure against outside threats. To verify the utility of the suggested strategy, the outcomes are compared to cutting-edge techniques for both digital and medical photos. Along with the hash value of the actual medicinal snaps, the private information is preserved on the blockchain. Due to this, all medical photos transmitted through the suggested blockchain network may be monitored. The experiments and analysis are shows that the proposed scheme has excellent security has attained during the entire process. It also achieved high embedding capacity, PSNR, rate and low SSIM throughout the process of data concealing.

High Payload Lossless Steganography Using Image Interpolation

“…It is important to note that Table 1 provides a comprehensive evaluation of the proposed RDH method, highlighting its ability to deliver higher PSNR values compared to other IRDH methods. Tis information is further supported by the results illustrated in Figure 6, which demonstrate the Jung & Yoo [1] Chang et al [4] Zhang et al [23] Lee & Huang [9] Tripathi et al [32] Bai et al [33] Proposed [21], Tripathi and Prakash [27], and Bai et al [28], alongside our proposed method. Our proposed approach achieves a remarkable embedding capacity of 4 bits per pixel, surpassing the average 2 bits per pixel ofered by the existing methods.…”

“…It covers all steps of image generation, data embedding, extraction, and recovery for fair comparison. Tripathi and Prakash discuss a reversible data hiding method based on an interpolation scheme and histogram shifting which considers a blockchain-based system to encrypt the images [27]. Bai et al discuss an efcient scheme based on the diferences between interpolation algorithms.…”

“…Tus, it can be clearly stated that our interpolation technique is superior to the existing aforementioned interpolation methods. Now, the presentation of the proposed IRDH method is compared against the existing IRDH methods which include Jung and Yoo [1], Zhang et al [33], Lee & Huang [21], Tripathi and Prakash [27], Bai et al [28], and the proposed method. Jung & Yoo's method [1] embeds secret data bits based on the image region's smoothness and complexity.…”

“…As far as Lee & Huang's [7] embedding capacity is concerned, 3,42,520 to 6,40,938 bits could be hidden. Te embedding capacity of Bai et al [27] is 585225 bits for all the images. It is constant for all images.…”