Diagonal queue medical image steganography with Rabin cryptosystem

被引:6
作者
Jain M. [1 ]
Lenka S.K. [1 ]
机构
[1] Department of Information Technology, Mody University of Science and Technology, Lakshmangarh, Rajasthan
关键词
Brain disease image; Cryptography; Decryption; Diagonal queue; Embedding; Encryption; Steganography;
D O I
10.1007/s40708-016-0032-8
中图分类号
学科分类号
摘要
The main purpose of this work is to provide a novel and efficient method to the image steganography area of research in the field of biomedical, so that the security can be given to the very precious and confidential sensitive data of the patient and at the same time with the implication of the highly reliable algorithms will explode the high security to the precious brain information from the intruders. The patient information such as patient medical records with personal identification information of patients can be stored in both storage and transmission. This paper describes a novel methodology for hiding medical records like HIV reports, baby girl fetus, and patient’s identity information inside their Brain disease medical image files viz. scan image or MRI image using the notion of obscurity with respect to a diagonal queue least significant bit substitution. Data structure queue plays a dynamic role in resource sharing between multiple communication parties and when secret medical data are transferred asynchronously (secret medical data not necessarily received at the same rate they were sent). Rabin cryptosystem is used for secret medical data writing, since it is computationally secure against a chosen-plaintext attack and shows the difficulty of integer factoring. The outcome of the cryptosystem is organized in various blocks and equally distributed sub-blocks. In steganography process, various Brain disease cover images are organized into various blocks of diagonal queues. The secret cipher blocks and sub-blocks are assigned dynamically to selected diagonal queues for embedding. The receiver gets four values of medical data plaintext corresponding to one ciphertext, so only authorized receiver can identify the correct medical data. Performance analysis was conducted using MSE, PSNR, maximum embedding capacity as well as by histogram analysis between various Brain disease stego and cover images. © 2016, The Author(s).
引用
收藏
页码:39 / 51
页数:12
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