Contemporary proven cryptographic algorithms, like the Advanced Encryption Standard (AES), are used in many secure data storage systems. Cipher data when written or read might be subject to noise. Classical error detection and correction methods are not suitable for encrypted data. In this paper, error detection and correction is performed at the receiver end, without any changes to the encryption algorithm. One of the properties of encrypted information is that all encrypted blocks have a minimum hamming distance from each other. This property is exploited to obtain the exact correct block. When error correction based on the encrypted data cannot be performed, natural language properties of plaintext data are used to eliminate noise. The plaintext blocks surrounding the noisy plaintext block are used to generate possible candidates. In case a unique solution is not achieved, n-gram properties of the plaintext language are used to rank the possibilities and promote the best fit.