An Enhanced Security in Medical Image Encryption Using Dynamic Chaotic Fuzzy Based Technique

Abstract

As IoT and cloud computing have grown in popularity, medical images are now often transmitted between devices or accessed directly from the cloud. With this, the security is always a concern as these images are prone to many types of attack. We have proposed a proven method that is efficient in terms of security, time complexity, and integrity in order to be cloud-friendly so that it may be launched into the cloud and made accessible to users at any time. The goal of the work is to create a dynamic key that, depending on fuzzy values, alters the reproduction rate parameters with each repetition. By applying the last chaotic value created from the previous iteration, the fuzzy triangular membership function has been used in this manner to generate the reproduction rate parameter. The uniqueness and major benefit of the suggested strategy are that it can increase the security of the algorithm that makes use of a chaotic map and a static key. The method has been put forth when designing algorithms so that it should not only demonstrate security against different attacks but also provide efficiency towards computational complexity. The technique has been tested against a set of images and an existing algorithm using a variety of security metrics, including the correlation coefficient, Number of Pixel Change Rate (NPCR), Unified Average Changing Intensity (UACI), and entropy. It has been determined from the comparative analysis that the proposed approach can make the existing algorithm more secure.