  Healthcare is an essential application of e-services, where for diagnostic
testing, medical imaging acquiring, processing, analysis, storage, and
protection are used. Image ciphering during storage and transmission over the
networks used has seen implemented using many types of ciphering algorithms for
security purpose. Current cyphering algorithms are classified into two types:
traditional classical cryptography using standard algorithms (DES, AES, IDEA,
RC5, RSA, ...) and chaos cryptography using continuous (Chau, Rossler, Lorenz,
...) or discreet (Logistics, Henon, ...) algorithms. The traditional algorithms
have struggled to combat image data as compared to regular textual data.
Whereas, the chaotic algorithms are more efficient for image ciphering. The
Significance characteristics of chaos are its extreme sensitivity to initial
conditions and algorithm parameters. In this paper, medical image security
based on hybrid/mixed chaotic algorithms is proposed. The proposed method is
implemented using MATLAB. Where the image of the Retina of the Eye to detect
Blood Vessels is ciphered. The Pseudo-Random Numbers Generators (PRNGs) from
the different chaotic algorithms are implemented, and their statistical
properties are evaluated using the National Institute of Standards and
Technology NIST and other statistical test-suits. Then, these algorithms are
used to secure the data, where the statistical properties of the cipher-text
are also tested. We propose two PRNGs to increase the complexity of the PRNGs
and to allow many of the NIST statistical tests to be passed: one based on
two-hybrid mixed chaotic logistic maps and one based on two-hybrid mixed
chaotic Henon maps, where each chaotic algorithm runs side-by-side and starts
with random initial conditions and parameters (encryption keys). The resulting
hybrid PRNGs passed many of the NIST statistical test suits.
