Protecting Sensitive Images with Improved 6-D Logistic Chaotic Image Steganography

Abstract

In the digital age, strong methods for safeguarding sensitive data are essential. Image steganography is a practical technique for data protection that hides information inside seemingly authentic images. The proposed method increases security by using chaotic based image encryption and decryption. Encryption approaches based on chaotic logistic theory present an abundance of attractive and novel opportunities for developing secure image encryption methods. Nevertheless, these maps are frequently used for specific, unpredictable starting parameters. This problem is addressed by the research's Tabu search optimisation method. This method optimises chaotic map initial settings using a fitness function with numerous objectives. For image encryption, the most efficient methods are used to produce confidential keys. The input picture undergoes horizontal and vertical diffusion and permutation during encryption. These operations further scramble the image data, making it even more difficult to detect the hidden information. The primary goal is to develop a safe method for encrypting both color and grayscale images. Two common grayscale and color images that are accessible to the public were used to test the suggested strategy. compare our method with key existing works, specifically on the basis of Number of Pixels Change Rate (NPCR), Unified Average Changing Intensity (UACI), Peak Signal-to-Noise Ratio (PSNR) and speed, respectively, our approach improves upon these studies. Our results demonstrate that 7.9981, 99.8245, 35.6507, and 78.871 are the greatest values of entropy, NPCR, UACI, and PSNR, respectively. Whereas the respective speeds of encryption and decryption increase to 0.8433 and 1.4387 seconds. This innovative approach presents a powerful tool for applications requiring secure image steganography