Security and Privacy of Cloud- and IoT-Based Medical Image Diagnosis Using Fuzzy Convolutional Neural Network

Algorithm 1

Medical image encryption and decryption.

	Input: image of size m × n, number of hidden layers (L), number of hidden nodes (h), compression rate (C)
	For n = 1: number of pixels
	Partition the image
	H = decompose the input image
	End
	Normalise all the subimage block matrices
	NET =  create backpropagation neural network (L, h, C)
	Get compressed data
	Scrambled image = extended zigzag algorithm (input image, NET)
	Generate chaotic sequences.
	S1, S2 = chaotic random sequences
	Diffuse pixel values by xor algorithm
	C1 = encrypted image
	//Decryption
	Input = C1
	S1, S2 = chaotic random sequences
	Diffuse pixel matrices
	Inverse zigzag algorithm
	Recovery of pixel blocks
	I = decrypted image