An Efficient & Secure Encryption Scheme for Biometric Data Using Holmes Map & Singular Value Decomposition

In the recent past we have been facing security challenges towards the transmission of biometric data over unsecured data channels. A lot of techniques have been developed and implemented for the secure transmission of the data. Taking the security concept in mind we introduce an efficient method based on chaotic theory for secured data transmission. The core idea of the proposed method is to shuffle the adjacent pixel correlation using the combination of Arnold Cat Map, Holmes Map and Singular Value Decomposition (SVD). The pixel values are scrambled using the Arnold Cat Map and further Holmes Map and SVD are used to alter the pixel values to complicate the relationship. Finally, decryption method is proposed to reconstruct the original data from encrypted data. Performance of proposed algorithm has been experimentally analyzed using statistical attack analysis, key sensitivity analysis and Peak Signal to Noise Ratio (PSNR). Experimental results shows that the proposed algorithm is lossless in nature, robust against statistical attacks and has high key sensitivity. Further low PSNR values indicate that the proposed algorithm provides a high level of perceptual security for the biometric data.