Research On Multimedia Encryption Evaluation

Multimedia encryption evaluation as an important part of information security, for theactual network information environment, study the new image encryption evaluation is ofpositive significance, selected topic for there is a historic role in the development of colorimage encryption assessment.In this paper, on the basis of gray image encryption, according to the principle of RGBcolor image extended to color image encryption algorithm through the experiment, thecolor image R, G, B three layer corresponding to integrate the entropy of the pulse coupledneural network (PCNN) extraction sequence and3d binary sequence structure entropy intospace vector observation the effect; By introducing concept of image space distance todefine the scrambling degree, calculate the space vector space distance and use of thismethod through the experiment of scrambling degree built a color image encryption systemof the assessment.Extracted using pulse coupled neural network space vector calculated as imageencryption effect of scrambling degree of evaluation criterion, to compare the performanceof the color image encryption algorithm. First through the Arnold scrambling encryptionalgorithm and chaotic encryption algorithm to encrypt image, and then by using PCNN toextract the image of3d binary entropy sequence of space vector,3d space distance as theimage scrambling degree, and evaluate the efficacy of the image encryption. Experimentalresults show that in the same pixel size color image after a large number of iterations, bythe method of chaotic encryption is the scrambling degree than Arnold transform is biggerand more robust. The evaluation algorithm can be applied to the objective evaluation of avariety of color image encryption algorithm.This article innovation point is to put forward a new system for color image encryptionassessment model, this model to extract the original color images and color imagesencryption sequence of three dimensional binary entropy as the eigenvector of theassessment, and use the system model is verified by the experimental feasibility assessmentof color images.