Security and Privacy Protection of Medical Images Using Pascal’s Triangle Chaotic Scheme in Cloud Storage

With the development of digital technology in recent years, cloud storage has become an inevitable way to store and share data. Cloud computing has accelerated the growth of the IT sector. Cloud orchestration is becoming impressive and capable of handling a large quantity of information in emerging trends. Online medical image transfer tools enable healthcare professionals to create stronger and deeper social networks, which results in higher volumes and a more flexible working environment. Therefore, cloud platforms can act as a central repository for medical data and as an exchange platform for use by all healthcare organizations. However, cloud storage security is still a significant issue, particularly when it comes to private data like medical images. Massive reports produced by modern medical technology, such as electronic patient records and scanned medical images, must be safely saved for future use. One way to guarantee the security of data saved in the cloud is through encryption, but due to image data’s large size and intricate structure, conventional encryption techniques might not be appropriate. This research paper aims at a highly secured full-image encryption system dedicatedly designed for cloud environments. Pascal's Triangle Transform (PTT), an innovative chaotic transform, is employed. Pascal's Triangle has the advantage of providing an image cryptographer with a huge variety of patterns. As disordered maps, these patterns are beneficial. The transform matrix is periodic due to the square matrix's unimodular property, making it a suitable candidate for image scrambling. The rigidness of the proposed system is tested and verified with statistical analysis like histogram, correlation, and entropy analysis also with differential attack analysis. The proposed values for the image “Lena” are entropy = 7.99, NPCR = 99.5743, and UACI = 34.47. The findings of the experiment demonstrated that this method offers robust security and is effective enough for actual use in cloud storage. This study can help create more effective and secure ways to safeguard image data stored in the cloud, which will be helpful for a variety of applications.