Secure transmission of medical images is increasingly becoming important as digital communication continues to evolve, particularly with the rise of telemedicine and online healthcare services. Recent research has introduced a novel lightweight encryption scheme intended to protect sensitive medical images from unauthorized access during their transmission. This scheme employs sophisticated cryptographic techniques to provide strong data security and integrity.
The newly proposed method leverages keys derived from the Lorentz attractor for diffusion and integrates a 16-bit Linear Feedback Shift Register (LFSR) for pseudo-random confusion processes. Enhancements to the encryption output are achieved through the Cipher Block Chaining (CBC) method, which builds complexity by altering each data block based on the previous block's output.
To maintain the integrity of the data, the study implements a 512-bit hashing scheme using the Whirlpool algorithm. This hashing technique is instrumental for verifying data integrity, condensing large volumes of data from secure images and producing shorter strings known as hashes. Significantly, the advancement proposes securing these hash values before transmission using lightweight symmetric key encryption, addressing concerns over data tampering.
During testing, the research team observed impressive performance metrics, showcasing the encryption’s robustness. There was an average entropy value of 7.99752, indicating high randomness efficiency, and the generated encrypted DICOM images demonstrated meaningful values such as Peak Signal-to-Noise Ratio (PSNR) of 5.872 dB, Number of Pixel Change Rate (NPCR) of 99.66128%, and Unified Average Change Intensity (UACI) of 33.55964%. These figures suggest the encryption method not only secures sensitive medical information but does so without significant degradation of image quality.
Through implementing this lightweight encryption process on Xilinx PYNQ-Z1 System on Chip (SoC) boards, the research team created user interaction enabled by custom-designed Graphical User Interfaces (GUI), enhancing usability for real-time applications and ensuring seamless interaction with the system for users.
The push for stronger security mechanisms within medical imaging is not unfounded. The healthcare sector increasingly relies on digital imaging for diagnostics and patient management, and with this shift, the risk of unauthorized access and breaches has escalated. Previous works cited have demonstrated various cryptographic techniques and chaotic systems used, reflecting the rich discussion on methods to secure sensitive data.
Specifically, the integration of chaotic systems and advanced S-box algorithms, as detailed by previous researchers like Vivek Verma and Xenxi Chai, emphasizes the growing importance of resilience against cybersecurity threats.
The impact of this research could reverberate across telemedicine, improving patient confidentiality and data integrity assurance, fundamentally enriching the trustworthiness of remotely shared medical information. Safeguarding health data through encryption is anticipated to become standard practice as the sector continues to digitize.
With the ability to demonstrate effective image encryption, this study paves the way for future innovations. Future studies could explore how to bolster robustness against noise attacks, which could potentially disrupt encrypted data transmissions, ensuring the continued protection of sensitive medical images. The emphasis is on researching lower operational noise susceptibility across methodologies to reinforce the security framework.
All the data generated or analyzed during this study are included within the published article, reinforcing transparency and credibility within scientific communication. The advancements here highlight the growing intersection between data security and healthcare technology, hinting at hopeful developments on the horizon for secure medical image sharing.