Abstract
Background: Medical imaging encloses different imaging techniques and processes to
image the human body for medical diagnostic and treatment purposes. Hence it plays an important
role to improve public health. The technological development in biomedical imaging specifically
in X-ray, Computed Tomography (CT), nuclear ultrasound including Positron Emission Tomography
(PET), optical and Magnetic Resonance Imaging (MRI) can provide valuable information
unique to a person.
Objective: In health care applications, the images are needed to be exchanged mostly over a wireless
medium. The diagnostic images with confidential information of a patient need to be protected
from unauthorized access during transmission. In this paper, a novel encryption method is proposed
to improve the security and integrity of medical images.
Methods: Chaotic map along with DNA cryptography is used for encryption. The proposed
method describes a two-phase encryption of medical images.
Results: The performance of the proposed method is also tested by various analysis metrics. The robustness
of the method against different noises and attacks is analyzed.
Conclusion: The results show that the method is efficient and well suitable for medical images.
Keywords:
Medical images, chaotic encryption, 2D Zaslavski map, DNA cryptography, histogram analysis, robustness test.
Graphical Abstract
[3]
Dongare AS, Alvi AS, Tarbani NM. An efficient technique for image encryption and decryption for secured multimedia application. Int Res J Eng Technol 2017; 04(04): 3186-90.
[5]
Hamza R, Faiza T. A novel sensitive image encryption algorithm based on the Zaslavsky chaotic map. Inform Secur J 2016; 25(4-6): 162-79.
[6]
Abd El-Samie FE, Ahmed HEH, Elashry IF, et al. Image encryption, a communication perspective. Taylor Francis group 2014; 418 p.
[7]
Borislav S, Krasimir K. Novel zaslavsky map based pseudorandom bit generation scheme. Appl Math Sci 2014; 8(178): 8883-7.
[8]
Rukhin A, Soto J, Nechvatal J, et al. A statistical test suite for random and pseudorandom number generators for cryptographic applications. Booz-Allen and Hamilton Inc Mclean Va 2001; 2010: 800-22.
[9]
Ramadan N, Ahmed HE, Elkhamy SE, Abd El-Samie FE. Chaos-based image encryption using an improved quadratic chaotic map. Am J Signal Process 2016; 6(1): 1-13.
[11]
Ahmad J, Ahmed F. Efficiency analysis and security evaluation of image encryption schemes. Int J Video Image Process Network Secur IJVIPNS-IJENS 2012; 12(04): 18-31.
[14]
Hor A, Ziou D. Image quality metrics: PSNR vs. SSIM. 2010 20th International Conference on Pattern Recognition. 2010; Istanbul, Turkey.
[15]
Elashry I, Faragallah OS, Abbas AM, El-Rabaie EM, Abd El-Samie FE. Homographic image encryption. J Electron Imaging 2009; 18(3): 033022.
[16]
Rajput Y, Gulve AK. A comparative performance analysis of an image encryption technique using extended hill cipher. Int J Comput Appl 2014; 95(4): 16-20.
[17]
Kumar R, Rattan M. Analysis of various quality metrics for medical image processing. Int J Adv Res Comput Sci Softw Eng 2012; 2(11): Corpus ID: 16571920.
[19]
Kendhe AK, Agrawal H. A survey report on various cryptanalysis techniques. Int J Soft Comput Eng 2013; 3(2): 287-93.