Securing Medical Images in the Cloud: A Hybrid Approach Using Adaptive Strength Control and Content-Aware Watermarking
Deepak Kumar, Amit Wadhwa, Payal Garg · 2025
The field of healthcare data storage on the cloud, which is fast expanding, protecting sensitive medical pictures including X-rays, CT scans, and MRIs while maintaining computing efficiency and image quality top priority is a huge challenge. This work introduces a novel approach to securely store medical images kept in the cloud by combining adaptive strength control with content-aware watermarking. Using adaptive strength control allows one to protect important diagnostic sections while lowering distortion in less important areas by varying the watermark intensity in line with image content. We then precisely place the watermark in the image using content- aware watermarking. In this sense, we can quickly identify modification without sacrificing the visual quality of the image. We hash every image using SHA-256 to maintain the hash result for future use, therefore providing additional peace of mind. Photographs are encrypted and kept on a virtual cloud following their hashed and watermarked treatment. Recalculating and comparing the hash value helps users to verify the presence of the watermark and guarantees the integrity of the image, therefore regulating access to these pictures. The hybrid approach balances security, visual quality, and computing economy. Experimental data supports the system's capacity to preserve visual quality, function in a cloud storage environment, and properly protect photographs from modification. Medical professionals may be relieved that strict data privacy regulations and depending on the quality of preserved images help to safely guard sensitive healthcare data with this approach.