Decryption of noisy encrypted images by statistical analysis

Cryptographic techniques are used to secure confidential data from unauthorized access, but these techniques are very sensitive to noise. A single bit change in encrypted data may have catastrophic impact over the decrypted data. This paper addresses the problem of removing bit error in visual data which are encrypted using AES algorithm by block. In order to remove the noise, three statistical analyses are proposed which are based on Global variance, Mean local variance and Sum of squared derivative. These methods exploit local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to correct the errors. Experimental results show that the proposed approaches can be used at the receiving end for the possible solution for error correction in visual data in encrypted domain.