Encryption and watermark-treated medical image against hacking disease - An immune convention in spatial and frequency domains

Digital Imaging and Communications in Medicine (DICOM) is one among the significant formats used worldwide for the representation of medical images. Undoubtedly, medical-image security plays a crucial role in telemedicine applications. Merging encryption and watermarking in medical-image protection paves the way for enhancing the authentication and safer transmission over open channels. In this context, the present work on DICOM image encryption has employed a fuzzy chaotic map for encryption and the Discrete Wavelet Transform (DWT) for watermarking. The proposed approach overcomes the limitation of the Arnold transform-one of the most utilised confusion mechanisms in image ciphering. Various metrics have substantiated the effectiveness of the proposed medical-image encryption algorithm.

[1]  Bo Du,et al.  Exploiting Interslice Correlation for MRI Prostate Image Segmentation, from Recursive Neural Networks Aspect , 2018, Complex..

[2]  Jianting Guo,et al.  Secure watermarking scheme against watermark attacks in the encrypted domain , 2015, J. Vis. Commun. Image Represent..

[3]  Rengarajan Amirtharajan,et al.  Networked hardware assisted key image and chaotic attractors for secure RGB image communication , 2017, Multimedia Tools and Applications.

[4]  Akram M. Zeki,et al.  A robust watermark embedding in smooth areas , 2011 .

[5]  Bin Wang,et al.  Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking , 2015 .

[6]  D. Ravichandran,et al.  DNA Chaos Blend to Secure Medical Privacy , 2017, IEEE Transactions on NanoBioscience.

[7]  Ali A. Elrowayati,et al.  Digital Image Watermarking Based On Joint (DCT-DWT) and Arnold Transform , 2016 .

[8]  Adrian-Viorel Diaconu,et al.  Circular inter-intra pixels bit-level permutation and chaos-based image encryption , 2016, Inf. Sci..

[9]  Tariq Shah,et al.  An efficient chaotic image encryption scheme , 2014, Neural Computing and Applications.

[10]  Bo Du,et al.  Shape prior constrained PSO model for bladder wall MRI segmentation , 2017, Neurocomputing.

[11]  Tiegang Gao,et al.  A Novel Encryption Frame for Medical Image with Watermark Based on Hyperchaotic System , 2014 .

[12]  Youwei Wang,et al.  Novel robust multiple watermarking against regional attacks of digital images , 2013, Multimedia Tools and Applications.

[13]  Rengarajan Amirtharajan,et al.  Hybrid image crypto system for secure image communication- A VLSI approach , 2017, Microprocess. Microsystems.

[14]  Jiwu Huang,et al.  A reversible data hiding method with contrast enhancement for medical images , 2015, J. Vis. Commun. Image Represent..

[15]  J. Fridrich.  Symmetric Ciphers Based on Two-Dimensional Chaotic Maps , 1998 .

[16]  Rengarajan Amirtharajan,et al.  Chaos based crossover and mutation for securing DICOM image , 2016, Comput. Biol. Medicine.

[17]  Ran Tao,et al.  A Comprehensive Analysis of Digital Watermarking , 2006 .

[18]  Chinchen Chang,et al.  A reversible image authentication scheme based on fragile watermarking in discrete wavelet transform domain , 2016 .

[19]  Bo Du,et al.  Deeply-supervised CNN for prostate segmentation , 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

[20]  Obaid Ur-Rehman,et al.  Fuzzy Image Authentication with Error Localization and Correction , 2015 .

[21]  Zhiliang Zhu,et al.  An image encryption scheme using nonlinear inter-pixel computing and swapping based permutation approach , 2015, Commun. Nonlinear Sci. Numer. Simul..

[22]  Ali Kanso,et al.  An efficient and robust image encryption scheme for medical applications , 2015, Commun. Nonlinear Sci. Numer. Simul..

[23]  L. Kocarev.  Chaos-based cryptography: a brief overview , 2001 .

[24]  Seyed Mojtaba Mousavi,et al.  Watermarking Techniques used in Medical Images: a Survey , 2014, Journal of Digital Imaging.

[25]  S. Agaian,et al.  NPCR and UACI Randomness Tests for Image Encryption , 2011 .

[26]  H. K. Huang,et al.  PACS and Imaging Informatics: Basic Principles and Applications , 2004 .

[27]  Georgios Ch. Sirakoulis,et al.  Game of Life variations for image scrambling , 2017, J. Comput. Sci..

[28]  Jiankun Hu,et al.  A pixel-based scrambling scheme for digital medical images protection , 2009, J. Netw. Comput. Appl..

[29]  In-Kwon Lee,et al.  Chaotic image encryption using pseudo-random masks and pixel mapping , 2016, Signal Process..

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

[31]  Gokcen Cetinel,et al.  Chaotic digital image watermarking scheme based on DWT and SVD , 2015, 2015 9th International Conference on Electrical and Electronics Engineering (ELECO).

[32]  Rengarajan Amirtharajan,et al.  Medical data sheet in safe havens - A tri-layer cryptic solution , 2015, Comput. Biol. Medicine.

[33]  Shujun Li,et al.  Breaking a modified substitution-diffusion image cipher based on chaotic standard and logistic maps , 2009, ArXiv.

[34]  Bin Wang,et al.  Evaluating the permutation and diffusion operations used in image encryption based on chaotic maps , 2016 .

[35]  Oussama Benrhouma,et al.  Digital images watermarking and partial encryption based on DWT transformation and chaotic maps , 2015, 2015 IEEE 12th International Multi-Conference on Systems, Signals & Devices (SSD15).

[36]  Thomas Martin Deserno,et al.  DICOM for Clinical Research: PACS-Integrated Electronic Data Capture in Multi-Center Trials , 2015, Journal of Digital Imaging.

[37]  Steve G. Langer.  DICOM Data Warehouse: Part 2 , 2015, Journal of Digital Imaging.

[38]  Nidaa A. Abbas,et al.  Image encryption based on Independent Component Analysis and Arnold’s Cat Map , 2016 .

[39]  C. K. Michael Tse,et al.  An efficient and secure medical image protection scheme based on chaotic maps , 2013, Comput. Biol. Medicine.