Secure medical data transmission using a fusion of bit mask oriented genetic algorithm, encryption and steganography
Authors: Pandey, H.M.
Journal: Future Generation Computer Systems
Volume: 111
Pages: 213-225
ISSN: 0167-739X
DOI: 10.1016/j.future.2020.04.034
Abstract:This paper presents a bit mask oriented genetic algorithm based secure medical data transmission mechanism. A bit mask oriented genetic algorithm (BMOGA) is utilized to reduce the replication of medical tests data which are transferred across organizations. Medical data is considered very sensitive, therefore secure medical data transmission is must. BMOGA is a variant of the traditional genetic algorithm. Literature reveals that it can avoid premature convergence – a situation when optimization algorithms get stuck at local optimum. BOMGA utilizes Boolean based mask-fill operators and performs reproduction operations in two different phases that helps to avoid premature convergence. Cryptographic features are integrated with the BMOGA for secure data transmission. The encrypted data is embedded into the medical images through 1-level and 2-level Discrete Wavelet Transform (DWT). The reverse process of the BMOGA is implemented for the extraction of secret message from the encrypted one. Numerical experiments are conducted to determine the performance of the proposed algorithm. Results reveals that the proposed algorithm is capable of secure data transmission. Performance comparison is done with the state-of-the-art algorithm with respect to the datasets. Comparative results indicated the superiority of the proposed algorithm in terms of various statistical measures such as peak signal to noise ratio (PSNR), correlation, structural content (SC), structure similarity (SSIM) and mean square error (MSE) to report the results.
Source: Scopus
Secure medical data transmission using a fusion of bit mask oriented genetic algorithm, encryption and steganography
Authors: Pandey, H.M.
Journal: FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
Volume: 111
Pages: 213-225
eISSN: 1872-7115
ISSN: 0167-739X
DOI: 10.1016/j.future.2020.04.034
Source: Web of Science (Lite)