Privacy preservation of ROI of medical image using squint pixel and PLSB hiding technique

Techno media is playing an important role on secure information due to rapid growth of the media. In telemedicine while transferring medical images tampers may be happened. As a part of protecting the information from the attacker, steganography is the art of hiding the information inside the cover medium with different carrier formats. In this paper, we propose a novel squint pixel based medical image steganographic technique to avoid easily distortion by an attacker. In this method, Original medical image itself acts as carrier image. A Medical image segmented into three sets of pixels, ROI and RONI and Border Pixels. The authentication data of ROI embedded in Squint Pixels of Border Pixels and information of ROI of medical image embedded in PLSB of squint pixels of RONI. Results of experiments on various medical images show that the proposed method produces high quality stego medical images with high accuracy and recovery of ROI data without loss.

[1]  Ch. Rupa Performance Evaluation of Message Security Using Fractal Sieve with MMD , 2013 .

[2]  Chin-Chen Chang,et al.  A Secret Image Sharing Scheme with High Quality Shadows Based on Exploiting Modification Direction , 2011, J. Multim..

[3]  Colin Boyd,et al.  Utilizing Least Significant Bit-Planes of RONI Pixels for Medical Image Watermarking , 2013, 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA).

[4]  Kevin Curran,et al.  Digital image steganography: Survey and analysis of current methods , 2010, Signal Process..

[5]  Tenkasi V. Ramabadran,et al.  Near-lossless compression of medical images through entropy-coded DPCM , 1994, IEEE Trans. Medical Imaging.

[6]  Rupa Ch. Squint Pixel Steganography: A Novel Approach to Detect Digital Crimes and Recovery of Medical Images , 2016 .

[7]  Tian Jun,et al.  Reversible Watermarking by Difference Expansion , 2002 .

[8]  Jun Tian,et al.  Reversible data embedding using a difference expansion , 2003, IEEE Trans. Circuits Syst. Video Technol..

[9]  Said Nabi,et al.  An Analysis of Application Level Security in Service Oriented Architecture , 2014 .

[10]  Nikolay N. Ponomarenko,et al.  Image visual quality metrics verification by TID2013: Exploring of mean square error drawbacks , 2014, 2014 5th European Workshop on Visual Information Processing (EUVIP).

[11]  E. Fatemizadeh,et al.  A LOW-DEGRADATION STEGANOGRAPHY MODEL FOR DATA HIDING IN MEDICAL IMAGES , 2004 .

[12]  Krishna Asawa,et al.  A Secure Hash Function MD-192 With Modified Message Expansion , 2010, ArXiv.

[13]  Ch. Rupa,et al.  A Digital Image Steganography using Sierpinski Gasket Fractal and PLSB , 2013 .

[14]  Shailender Gupta,et al.  Information Hiding Using Least Significant Bit Steganography and Cryptography , 2012 .

[15]  Osamah M. Al-Qershi,et al.  Authentication and Data Hiding Using a Reversible ROI-based Watermarking Scheme for DICOM Images , 2009 .

[16]  Atallah M. Al-Shatnawi A New Method in Image Steganography with Improved Image Quality , 2012 .

[17]  Hayat Al-Dmour,et al.  Quality optimized medical image information hiding algorithm that employs edge detection and data coding , 2016, Comput. Methods Programs Biomed..

[18]  Kevin Curran,et al.  An evaluation of image based steganography methods , 2006, Multimedia Tools and Applications.

[19]  Rajiv Kumar,et al.  A STUDY OF GENETIC ALGORITHM TO SOLVE TRAVELLING SALESMAN PROBLEM , 2012 .

[20]  Ch. Rupa Squint Pixel Steganography: A Novel Approach to Detect Digital Crimes and Recovery of Medical Images , 2016, Int. J. Digit. Crime Forensics.