Enhanced Image Encryption Using Chaotic Systems and Rubik’s Cube Transformations: A Comparative Performance Analysis

With the increasing demand for secure image transmission and storage, image encryption has become a crucial aspect of digital security. Traditional encryption techniques, such as AES and DES, often struggle with the large size and redundancy of image data, necessitating more advanced approaches. This study explores various image encryption techniques, with a particular focus on chaotic systems and Rubik’s Cube transformations. The experimental evaluation is conducted using MATLAB, analyzing five encryption algorithms: the Rubik’s Cube Algorithm, Bit-Level Image Encryption using Chaotic Maps, Modified Henon Map with Hybrid Chaotic Shift Transform, Modified Rubik’s Cube Algorithm, and 6D Hyper-Chaotic System with DNA Encoding. Performance metrics such as Unified Average Changing Intensity (UACI), entropy, Number of Pixel Change Rate (NPCR), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity Index Measure (SSIM) are used to assess encryption strength and randomness. Results indicate that the Modified Rubik’s Cube Algorithm and Bit-Level Chaotic Map encryption exhibit superior encryption performance, offering high security and robustness against cryptographic attacks. Additionally, future implementations can leverage hardware accelerations like FPGAs and SoCs for real-time applications.