Modified AES Cipher Round and Key Schedule

In this paper, Advanced Encryption Standard was modified to address the lowdiffusion rate at the early rounds by adding additional primitive operationssuch as exclusive OR and modulo arithmetic in the cipher round. Furthermore,byte substitution and round constant addition were appended to the keyschedule algorithm. The modified AES was tested against the standard AESby means of avalanche effect and frequency test to measure the diffusion andconfusion characteristics respectively. The results of the avalanche effectevaluation show that there was an average increase in diffusion of 61.98% inround 1, 14.79% in round 2 and 13.87% in round 3. Consequently, the resultsof the frequency test demonstrated an improvement in the randomness of theciphertext since the average difference between the number of ones to zeros isreduced from 11.6 to 6.4 along with better-computed p-values. The resultsclearly show that the modified AES has improved diffusion and confusionproperties and the ciphertext can still be successfully decrypted and recoverback the original plaintext

Denoising and error correction in noisy AES-encrypted images using statistical measures

International audienceCryptography based techniques are used to secure confidential data from unauthorized access. These techniques are very good for the security and protection of the data but are very sensitive to noise. A single bit change in encrypted data can have a catastrophic impact on the decrypted data. This paper addresses the problem of removing bit errors in visual data which are encrypted using the AES algorithm in CBC mode (Cipher Block Chaining). We propose a noise removal approach based on the statistical analysis of each block during the decryption process. Three statistical measures are proposed, i.e. the global variance method (GVM), the mean local variance method (MLVM) and the sum of the squared derivative method (SSDM) for error correction. The proposed approach uses local statistics of the visual data and confusion/diffusion properties of the encryption algorithm to remove errors. Experimental results show that the proposed approach gives better results in removing noise and can be used for noise removal in visual data in the encrypted domain