Protein Key Generation for Secure CT-Chest Images Encryption | ||||
| International Journal of Intelligent Computing and Information Sciences | ||||
| Article 6, Volume 22, Issue 1, February 2022, Page 76-87 PDF (1.35 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/ijicis.2021.82820.1108 | ||||
 View on SCiNiTO | ||||
| Author | ||||
Sara A Shehab 
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| Computer Science Dep, Faculty of Computer and Artificial Intelligence, Sadat city, Egypt | ||||
| Abstract | ||||
| Nowadays, one of the most complex problems in telemedicine and E-health is the preservation of patient data due to the integration between the development of technology and the medical sector. To protect patient privacy, the transmission of the secured medical image requires adequate techniques. This study aims at encrypting COVID-19 images of Computed Tomography (CT) chest scan into secured and sensitive cipher images for the infected patient. To achieve a high degree of security in the encryption process, protein key generation for the encryption process has been proposed. This study aims to encrypt images using 2 round AES plus Protein key. The histogram has been used to estimate the degree of security for the proposed method. Four criteria have been selected to evaluate the degree of security for the proposed method Number of Pixel Change Rate, Correlation coefficient, Entropy, and Unified Average Changing Intensity. The result indicated that the proposed method has 99.5% and above NPCR, Correlation coefficient close to zero, UACI above 30%, and Entropy near to 8. The results confirm that the proposed method achieves a high level of security and sensitivity when compared with previous work. Therefore, the proposed method can be considered as a successfully applied algorithm to satisfy the security requirements of transmitting CT images for COVID-19 patients. | ||||
| Keywords | ||||
| Protein; Number of Pixel Change Rate; Histogram; Entropy; Unified Average Changing Intensity | ||||
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