Secure Medical Data Hiding Using DWT, QPSO, and Lightweight Encryption

With the ever-increasing demand for secure transmission and storage of medical records in a healthcare system, quick and effective data protection techniques are required. In this paper, a new approach of using Speck-Cipher, Discrete Wavelet Transform (DWT), and Quantum-based Particle Swarm Optimization (QPSO) is proposed for the security of embedded medical data in medical images. The technique can also maintain good image quality and offers Speck-96bit to safeguard sensitive medical data with high noise & compression attack resistance (CR = 0.95). The results showed that the proposed method performs better, with a Peak Signal-to-Noise Ratio (PSNR) of 46.0 dB (Max = 62.5) and a Structural Similarity Index Measure (SSIM) of 0.98, revealing minimal distortion between itself and the original cover image. In addition, it provides excellent compression robustness (0.94), which ensures that the quality of the hidden data remains intact even under aggressive compression. Encryption time 12.25 ± 1.8ms avg (10 runs/image) shows the efficiency of the Speck cipher and shows that the results are applicable to real-time healthcare in an IoT environment. Furthermore, the method shows an NCC of Normalized Cross-Correlation) near 1, meaning data can be retrieved accurately; high-quality post-compression retention (0.95) that guarantees hidden data integrity with aggressive compression; and a computational efficiency of 90 img/s (Max = 95) that is suitable for real-time IoMT (90 img/s on Raspberry Pi 4). The results obtained prove that the proposed technique is computationally efficient and enhances data confidentiality, respectively, for real-world healthcare systems.