Compression-Encryption Model for Digital Images Based on GAN and Logistic Map

The problem of digital image transmission lies on the size of the image which tends to get bigger, and how to satisfy the confidentiality aspects when images are transmitted via unsecured channels. To solve this problem, a cryptosystem model is proposed, using a combination of compression and cryptography methods. This research proposes the development and performance measurement of compression-encryption models, Which consists of Generative Adversarial Network and logistic map encryption. The test results also showed that this scheme is better than other color image compression-encryption algorithms, With the SSIM values above 0.97 and compression ratio above 94%.