Medical Image Encryption Techniques: A Review

Abstract

In the majority of hospitals and clinics, doctors currently employ medical images, including brain MRIs, ultrasounds, and X-ray images, to diagnose a variety of severe diseases. Image encryption is critical for safeguarding data confidentiality from fraudulent use and illegal access in eHealth applications. Chaos is an exceptionally powerful cryptographic resource since its inception in image-encryption methods.  This work offers a comprehensive overview of the evolution of algorithms for image encryption based on chaos theory, including both symmetric and asymmetric approaches. This research is distinguished from previous review research, which addressed many varied methods of chaos-based image encryption and focused on theoretical aspects only; these techniques could be used in digital medical records of hospital patients and telemedicine communication. This analysis revealed that the most favorable outcomes were presented in the method using the Blum-Goldwasser Cryptosystem (BGC) and Elliptic Curve Cryptography (ECC) with NPCR of 99.6901% and UACI of 33.694%. The review demonstrated that these algorithms offer robust security and intricacy regarding keys. However, certain studies have identified challenges associated with the complexity of keys and the time required for implementation in real-time. The paper suggests that the efficacy of algorithms should be enhanced and evaluated on a broader scale than image types. It begins with a comprehensive introduction to image encryption, which addresses the fundamental concepts. Then, it conducts a thorough examination of chaos-based image encryption, that encompasses a variety of methods and approaches within this field.