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

作者：

Highlights：

• This paper addresses the problem of removing bit errors in visual data which are encrypted using the AES algorithm in CBC mode.

• 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.

摘要

Highlights•This paper addresses the problem of removing bit errors in visual data which are encrypted using the AES algorithm in CBC mode.•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.

论文关键词：Cryptosystem,Image denoising,AES encryption,Image encryption

论文评审过程：Received 18 May 2015, Revised 6 November 2015, Accepted 6 November 2015, Available online 30 November 2015, Version of Record 11 December 2015.

论文官网地址：https://doi.org/10.1016/j.image.2015.11.003