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Utilizing reverse genetic algorithms and fractal theory for encrypting images

机译:利用反向遗传算法和用于加密图像的分形理论

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Many digital services require a reliable security for saving and sending images. Security of images has attracted the attention of many because of the rapid growth of the Internet in today's digital world. In this study a new combined model of encrypting images was used that is made of genetic algorithm and Mandelbrot algorithm. In the early proposed stages, by combining original image with built Mandelbrot algorithm a number of encrypted images were created and these images were used as initial population for the genetic algorithm in following stages. At each stage of the genetic algorithm the response of the previous iteration was optimized until we reach the best encrypted image. Also in our proposed method we can reach to the encrypted image from a reverse operation of genetic algorithm. The best encrypted image is an image with high entropy and low correlation coefficient. Considering the entropy and correlation coefficient that is obtained from our proposed method compared to other methods, our method had better results.
机译:许多数字服务需要保存和发送图像的可靠安全性。由于互联网在今天的数字世界中,图像的安全性引起了许多人的注意。在本研究中,使用了一种新的加密图像的组合模型,其由遗传算法和Mandelbrot算法制成。在早期提出的阶段中,通过将原始图像与构建的Mandelbrot算法组合,创建了多个加密图像,并且这些图像被用作以下阶段的遗传算法的初始群体。在遗传算法的每个阶段,先前迭代的响应在我们达到最佳加密图像之前进行了优化。同样在我们所提出的方法中,我们可以从遗传算法的反向操作达到加密图像。最佳加密图像是具有高熵和低相关系数的图像。考虑到从我们所提出的方法获得的熵和相关系数与其他方法相比,我们的方法具有更好的结果。

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