Blockchain Enabled Interpolation Based Reversible Data Hiding Mechanism for Protecting Records

Autor: null Abhinandan Tripathi, Jay Prakash
Rok vydání: 2023
Předmět:
Zdroj: ICST Transactions on Scalable Information Systems. :e1
ISSN: 2032-9407
DOI: 10.4108/eetsis.v10i4.2934
Popis: 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.
Databáze: OpenAIRE