Multi-layer color image encryption using random matrix affine cipher, RP2DFrHT and 2D Arnold map

Abstract

Confidentiality, integrity, authenticity, non-repudiation and storing and transmitting images over the unsecured channel has become a challenging task nowadays. In this scenario, a robust image encryption technique over open network has grasped a great deal of attention. In this paper to meet this challenge, we have established a new multi-layer robust color image encryption using random matrix affine cipher (RMAC), reality preserving two dimensional discrete fractional Hartley transform (RP2DFrHT) and two dimensional Arnold map. The first stage of encryption is designed through RMAC. RMAC provides security in co-ordinate domain as well as in geometrical domain. So if a hacker has knowledge about all the pixels of an image, but has no information about the mechanism of co-ordinate domain he/she cannot steal any information. The second stage of encryption is obtained incorporating the concept of RP2DFrHT. The reality preserving transform eliminates the complex-valued coefficients and provides the real-valued coefficients of encrypted image. The real-valuedness of data provides convenient platform for display, storage and transmission in digital domain. The third stage of encryption is done using 2D Arnold map, which not only enhances the security but also enlarges key space. Therefore, the proposed technique provides security in geometrical, co-ordinate, frequency and time domains simultaneously. The security of our proposed technique depends upon the secret keys as well as their correct arrangements. Simulation analysis provides the complete visual results of all stages of encrypted and decrypted images. Sensitivity analysis validates that our proposed technique is highly sensitive towards its secret keys and their arrangements. Statistical analysis such as histogram analysis, MSE, PSNR, correlation coefficient, entropy analysis and resistivity of classical attacks validates the effectiveness and feasibility of our proposed work. Moreover, comparison analysis testifies that our proposed technique functions significantly well as compared to existing similar techniques.