Secure CT-Image Encryption for COVID-19 Infections Using HBBS-Based Multiple Key-Streams

Area of Science:

• Medical Imaging and Informatics
• Cybersecurity in Healthcare
• Cryptography and Data Security

Background:

• The increasing use of telemedicine and electronic health (e-health) systems necessitates advanced methods for securing patient data.
• Protecting patient privacy during the transmission of sensitive medical images, such as Computed Tomography (CT) scans for Coronavirus (COVID-19), is critical.

Purpose of the Study:

• To develop and evaluate a novel encryption scheme for securing COVID-19 CT chest scan images for safe data transmission.
• To enhance patient data privacy and ensure the integrity of medical information using a secure key-stream generator.

Main Methods:

• A hashing version of the Blum Blum Shub (BBS) generator, named Hash-BBS (HBBS), was developed to create multiple secure key-streams.
• The statistical properties of the generated key bit-strings were rigorously analyzed using the NIST-test-suite.
• An encryption scheme was designed and applied to four COVID-19 CT images using the HBBS-generated key-streams.

Main Results:

• The HBBS generator produced key bit-strings with excellent randomness and uniform distribution properties.
• The proposed encryption scheme achieved a high degree of confidentiality and integrity for transmitting medical data.
• Performance analysis indicated that the HBBS generator outperforms existing security methods in securing medical image transmission.

Conclusions:

• The developed Hash-BBS generator provides a robust solution for encrypting COVID-19 CT images, ensuring secure data transmission.
• The proposed method effectively addresses the security requirements for transmitting sensitive medical data in e-health environments.