Secure medical image sharing for smart healthcare system based on cellular neural network
Conghuan Ye, Cong Chen
Abstract
Abstract The smart healthcare system (SHCS) facilitates the healthcare process with the widespread use of medical data through the internet of medical things (IoMT). Widespread use of medical data, especially medical images can also lead to privacy issues. Traditional encryption algorithms can address some problems; however, they cannot deter the redistribution of decrypted content. To prevent the decrypted content from being used illegally, the paper proposes a combination scheme of encryption and fingerprinting based on the game of life (GOL) and singular value decomposition (SVD) with the purpose of protecting medical images. First, medical images are performed with discrete wavelet transform (DWT). Second, the highest coefficients bit planes of the approximation component are selected to confuse with GOL. Third, the other bit planes and other detail components are chosen to embed fingerprints. Finally, all subbands are diffused with SVD computing. The proposed privacy protection scheme, as far as we know, is the first privacy protection scheme for the SHCS using GOL and SVD based on a chaotic cellular neural network (CNN). The proposed scheme can provide double-level privacy protection for the SHCS. The experimental results and discussion verify it is effective for the privacy protection of the SHCS.